University of Southern California Dissertations and Theses

Multivalent smart elastin-like polypeptide therapeutics with drug delivery and biosensing applications.

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Multivalent smart elastin-like polypeptide therapeutics with drug delivery and biosensing applications.

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Content MULTIVALENT SMART ELASTIN-LIKE POLYPEPTIDE THERAPEUTICS WITH
DRUG DELIVERY AND BIOSENSING APPLICATIONS

by

Jugal Dhandhukia

A Dissertation presented to the
Department of Pharmacology and Pharmaceutical Sciences
University of Southern California
Faculty of the USC Graduate School
In fulfillment of the
Requirements for the degree
DOCTOR OF PHILOSOPHY
PHARMACEUTICAL SCIENCES

August 2017

Copyright 2017 Jugal Dhandhukia
ii

Acknowledgments
I would like to thank Dr. Andrew MacKay for his constant belief, support and guidance
during my academic tenure. I would also like to thank my committee members - Dr. Curtis
Okamoto, Dr. Alan Epstein and Dr. Sarah Hamm-Alvarez for their critique and valuable
suggestions. I am grateful to all the past members of MacKay lab for training me and
current members - Zhe Li, Santosh Peddi, Shruti Kakan, David Tyrpak, Aida Kouhi, Arjun
Mehta, Jordan Despanie, Dab Brill and Isaac Weitzhandler for contributing data to my
thesis and publications. Lastly, I would like to thank my family members for guiding and
motivating me without which it would have been difficult to cope up with the academic
and research challenges.

iii

Table of Contents

Acknowledgements…………………………………………………......................... ii
List of Tables…………………………………………………………………………… viii
List of Figures…………………………………………………………………............. ix

Chapter 1: Multivalent Smart Protein Polymers with Drug Delivery and
Biosensing Applications……………………………………………………………...
1.1 Abstract…………………………………………………………………...
1.2 Introduction……………………………………………………………….
1.3 Genetically Engineered Protein Polymers for Drug
Delivery……………………………………………………………………
1.3.1 Triple Negative Breast Cancer……………………………………..
1.3.2 Rapalogues…………………………………………………………..
1.3.3 Cognate drug receptors for rapalogue drug delivery…………….
1.4 Bioresponsive Therapeutics………………………………………........
1.4.1 Genetically engineered protein polymers for biosensing
applications…………………………………………………………..
1.5 Conclusion……………………………………………………………….
Chapter 2: Berunda Polypeptides: Multi-headed Fusion Proteins for
subcutaneous delivery of rapamycin to breast cancer in vivo...……………..
2.1 Abstract…………………………………………………………………..
2.2 Introduction………………………………………………………………

1

1

2

4

7

9

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16

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17

iv

2.3 Materials and Methods…………………………………………………
2.3.1 ELP gene design and cloning……………………………………..
2.3.2 FKBP-ELP expression and purification……………………………
2.3.3 ELP physicochemical characterization……………………………
2.3.4 Isothermal titration calorimetry of Rapa interactions with FKBP-
ELPs…………………………………………………………………….
2.3.5 Drug loading and formulation preparation for in vivo
administrations………………………………………………………..
2.3.6 Drug retention and formulation stability using extended dialysis...
2.3.7 Tumor regression studies……………………………………………
2.3.8 Protein extraction and tumor western blot analysis………………
2.3.9 Histopathological tissue examination of Rapa treated mice….....
2.3.10 In vivo imaging of fluorescently labelled FKBP-ELPs……………
2.4 Results and Discussion…………………………………………………
2.4.1 Characterization of FKBP-ELP carriers………………………......
2.4.2 FAF binds two Rapa molecule with a similar affinity to FA and
FSI…………………………………………………………………....
2.4.3 FA and FAF architectures extend stability and drug retention
compared to FSI nanoparticles……………………………………
2.4.4 FAF-Rapa formulation demonstrates superior tumor growth
suppression following SC administration…………………………
21

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38

40

v

2.4.5 SC treatment with Rapa loaded FKBP-ELPs inhibits a
downstream target of the AKT-mTORC1 axis in MDA-MB-468
solid tumors…………………………………………………………
2.4.6 Free Rapa treatment is toxic at the site of SC injection………..
2.4.7 Soluble FA and FAF tumor accumulation is greater than FSI
nanoparticles after SC administration…………………………….
2.5 Conclusion……………………………………………………………….
2.6 Acknowledgements……………………………………………………..
Chapter 3: Switchable Elastin-Like Polypeptides That Respond to Chemical
Inducers of Dimerization……………………………………………………………..
3.1 Abstract…………………………………………………………………..
3.2 Introduction………………………………………………………….......
3.3 Materials and Methods…………………………………………………
3.3.1 FKBP-ELP fusion gene design and synthesis…………………...
3.3.2 FKBP-ELP protein expression and purification………………….
3.3.3 FKBP-ELP characterization……………………………………….
3.3.4 FKBP-ELP kinetics and transition temperature
determination………………………………………………………..
3.3.5 MALDI-TOF………………………………………………………….
3.3.6 Bio-Layer Interferometry……………………………………………
3.4 Results and Discussion………………………………………………..
3.4.1 Purification and phase behavior of FKBP-ELP fusion
proteins………………………………………………………………

44

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vi

3.4.2 The ELP transition temperature responds to stoichiometric
additions of CID…………………………………………………….
3.4.3 Reversible switching of FKBP-ELP at isothermal
conditions……………………………………………………………
3.4.4 Quantitative modeling of FKBP-ELP switching
behavior…………………………………………………………….
3.4.5 Modeling results……………………………………………………
3.4.6 Model limitations…………………………………………….........
3.4.7 CID binding kinetics over immobilized FKBP-
ELP……………………………………………………………........
3.5 Conclusion……………………………………………………………..
3.6 Acknowledgements……………………………………………………
Chapter 4: Elastin-Like Polypeptide Switches – A Design Strategy to Detect
Multimeric Proteins……………………………………………………………………
4.1 Abstract…………………………………………………………………..
4.2 Introduction………………………………………………………………
4.3 Materials and Methods…………………………………………………
4.3.1 ELP expression, purification and characterization………………
4.3.2 Biotin labeling and quantification of ELPs………………………..
4.3.3 Biotin-ELP kinetics and transition temperature determination….
4.3.4 Thermodynamics for streptavidin and biotin-ELP assembly……
4.3.5 Particle size measurement using Dynamic Light Scattering……
4.4 Results……………………………………………………………………

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vii

4.4.1 Purification of biotin-ELP and characterization of its phase
behavior……………………………………………………………….
4.4.2 Biotin-ELP associate into dimeric and trimeric complexes with
streptavidin……………………………………………………………
4.4.3 Fine tuning biotin-ELP detection of streptavidin to occur at
physiological temperatures…………………………………………
4.4.4 Biotin-ELP transition temperature responds to multimerization at
different streptavidin ratios…………………………………………
4.5 Discussion……………………………………………………………….
4.6 Conclusion……………………………………………………………….
4.7 Acknowledgements……………………………………………………..
References………………………………………………………………………………

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97

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106

viii

List of Tables
Table 1: Physicochemical properties of ELP protein polymers with and without
FKBP …………………………………………………………………………..

35
Table 2: Thermodynamic parameters of FKBP-ELP interaction with Rapa …….. 38

Table 3: Physical properties of ELP protein polymers with and without FKBP….
Table 4: Fit parameters for temperature vs. interaction of length and
concentration for ELP with and without FKBP fusion protein……………
Table 5: Physical properties of (2VA) ELPs evaluated in Chapter 4……………..
Table 6: Hydrodynamic radii for biotin-ELP complexes with streptavidin………..

67

75

92

99

ix

List of Figures
Figure 1: Optimization of FKBP-ELP architecture to enhance the stability and
efficacy of Rapa delivery.……………………...........................................

20
Figure 2: Physicochemical characterization of FKBP-ELP carriers ………………. 34

Figure 3: Heat release during Rapa binding is observed only with FKBP-ELPs
and not with backbone ELPs.……………………………………………….

36
Figure 4: FAF has twice the drug loading capacity compared to FSI and FA ……

37

Figure 5: The soluble architecture of FA and FAF enhance stability with
extended drug retention compared to FSI nanoparticle ……………........

39
Figure 6: FAF-Rapa demonstrates dose-dependent tumor growth suppression
when injected IV ……………………….……………………………………..

41
Figure 7: FAF-Rapa outperforms other carriers in suppressing tumors when
injected SC ……………………………………………………………………

42

Figure 8: SC treatment with Rapa inhibits downstream target of mTORC1………

45

Figure 9: SC treatment with Rapa at 0.75 mg/kg does not inhibit p-p70 S6K1
and p-4E-BP1 levels ………………………………………………………..

46
Figure 10: FKBP-ELP carrier protects against tissue necrosis during SC
administration ……………………………………………………………….

47
Figure 11: Histopathology of mouse organs evaluated post SC treatment fails to
show evidence of systemic toxicity across any treatment groups …….

48
Figure 12: Cy5.5 labeled FKBP-ELPs retained a stable hydrodynamic radius at
37 °C…………………………………………………………………………

49
Figure 13: FA and FAF show high accumulation in tumor and clearance organs
compared to FSI. …………………………………………………………...

50

Figure 14: Live body scans of SC injected Cy5.5 labeled FKBP-ELPs taken
dorsally…………………………………………………………………….....

51

Figure 15: Cy5.5-FSI injected IV shows greater whole body distribution and
tumor accumulation compared to Cy5.5-FSI injected SC………………

52
x

Figure 16: Reversible switching of FKBP-ELP fusion proteins by controlled
dimerization …………………………………………………………………

60

Figure 17: Characterization of ELP fusion proteins …………………………………

66

Figure 18: CID homodimerization to FKBP-ELP lowers its phase transition
temperature………………………………………………………………….

68
Figure 19: FKBP-ELP phase transition temperature depends on CID
stoichiometry…………………………………………………………………

69
Figure 20: FKBP-ELP phase separation is fast and reversible under isothermal
conditions ……………………………………………………………………
.

71
Figure 21: FKBP-ELP dimerization occurs via a two-step process ……………….

73

Figure 22: Quantitative model of FKBP-ELP switching behavior ………………….

77

Figure 23: Predicted concentrations of FKBP-ELP species vs. CID
concentration ……………………………………………………………….

79
Figure 24: Binding of CID to FKBP-V72 shows strong association and fast
dissociation kinetics..............................................................................

81
Figure 25: Designing bioresponsive ELPs that phase separate in response to a
model multimeric protein: streptavidin ……………………………..……

86
Figure 26: Identification of a high molecular weight ELP that detects streptavidin
biotin interactions…………………………………………………………..

91

Figure 27: Biotin-ELPs interact with up to three sites on streptavidin…………….

94

Figure 28: Adjustment of the biotin-ELP concentration tunes streptavidin
induced phase separation to physiological temperatures……………..

95

Figure 29: ELP does not respond to streptavidin in the absence of biotin
labeling…………………………………………………………………….. 96

Figure 30: The biotin-ELP transition temperature is minimized when the formation
of multimers with streptavidin is maximized…………………………….. 97

1

Chapter 1
Multivalent Smart Protein Polymers with Drug Delivery and Biosensing
Applications

1.1 Abstract
Rapid clearance, severe potent side effects and poor aqueous solubility are the most
common drawbacks associated with small molecule treatment. Use of specific drug
carriers for systemic delivery of such small molecules has the potential to overcome the
obstacles associated with free drug treatment. Drug carriers sequester small molecules,
mitigate dose limiting toxicities, provide targeting to diseased tissue and prolong drug
circulation times. Similarly, therapeutics that can recognize and respond to specific
environmental cues provide targeting to the diseased tissue sparing healthy cells.
However, designing such drug carriers and bioresponsive therapeutics with high
precision, reproducibility and scale-up manufacturing processes remains difficult. Use of
genetically engineered therapeutics provides an emerging solution to these challenges.
Genetic engineering allows high precision and precise control at the gene level which
further allows fusion of different cargos like peptides, proteins or bioresponsive moieties
which can assemble and adopt different structures and designs. These fusions can be
tailored to suit different applications including drug delivery of small molecules and
biosensing applications. An emerging class of genetically engineered carriers are Elastin-
Like Polypeptides (ELPs) which have shown multi-nanomedicine applications including
as cell trafficking, imaging and targeting agents. This review advances the ELP
applications in drug delivery of small molecules using re-engineered cognate receptor
2

strategy and biosensing applications to specific dimeric small molecules and multimeric
proteins using the phase separation property of ELPs.

1.2 Introduction
Drug delivery to the diseased tissue without causing systemic toxicity to healthy tissue is
the ideal goal of any therapeutic. However, the standard small molecule chemotherapy
treatment produces a wide range of side effects(Moudi et al., 2013; Tacar et al., 2013;
Yared and Tkaczuk, 2012). Delivering small molecules with drug carriers holds promise
in alleviating the side effects observed with free drug administration because drug carriers
sequester the drug from entering healthy tissue, utilize target mediated drug delivery to
the diseased tissue, and facilitate combination treatment by significantly reducing side
effects for one of the drugs. This has been validated by use of drug carriers in the clinic
and have been FDA approved for chemotherapeutics such as albumin loaded paclitaxel
(Abraxane
TM
) and liposomal formulated doxorubicin (Doxil
TM
)(Barenholz, 2012; Hawkins
et al., 2008; Schroeder et al., 2012). To continue developing drug carriers for a specific
class of small molecules, there is an emerging class of protein polymer called Elastin-
Like Polypeptide (ELP) which offers aqueous solubility, monodisperse nature,
biodegradable and biocompatible backbone and amenable to synthesis by genetic
engineering(Despanie et al., 2015). This chapter summarizes the treatment options
available for breast cancer from small molecule chemotherapy to biologics and limitations
associated with it, the current predicament for a subclass of breast cancer patients with
triple negative breast cancer (TNBC), use of rapalogues as promising treatment against
TNBC and employment of cognate drug receptors fused to ELP for rapalogue delivery.
3

Bioresponsive therapeutics offer targeting and drug delivery to the diseased tissue
utilizing specific environmental cues. The environmental cues that have been explored in
the past includes pH (He et al., 2013), heat or magnetic stimuli (Mura et al., 2013), prodrug
based (Giang et al., 2014) or antibody-directed enzyme prodrug therapy (Bagshawe et
al., 2004) and very recently use of bispecific ‘Bites’ therapies that rely on cytotoxic T cells
(Stieglmaier et al., 2015; Suryadevara et al., 2015). However, these approaches rely
heavily on one or the other external factors in achieving drug delivery or target death and
do not target pathological agents that are soluble, non-localized, free flowing in the
systemic circulation and multimeric in nature. For instance, Eosinophila is characterized
by increased amount of dimeric IL-5 in the blood which causes excess production of
eosinophils leading to allergic reactions (Fulkerson and Rothenberg, 2013). Similarly,
neutralizing IgG antibodies against a specific cytokine results in an orphan lung disease
called Pulmonary Alveolar Proteinosis (Trapnell and Whitsett, 2002). There are several
autoimmune diseases such as Systemic Lupus Erythematosus (Choi et al., 2012), Graves
disease (Prabhakar et al., 2003) and Sjögren’s syndrome (Sumida et al., 2012) which are
either caused directly or aggravated by auto-antibodies. Bioresponsive therapeutics that
can target this class of soluble, multimeric ligands remains untapped. To develop
therapeutics that can not only recognize but further respond to these multimeric ligands,
this chapter introduces smart polymers that have ability to phase separate on binding
specifically to these multimeric ligands. Distinguishing biosensing applications of
synthetic polymers from recombinant protein polymers, this chapter describes how ELP
fusion polymers can be designed to detect and respond to proof-of concept multimeric
4

molecules including dimeric small molecule ligands and tetrameric macromolecule
proteins.

1.3 Genetically Engineered Protein Polymers for Drug Delivery
Genetically engineered protein polymers can be defined as polymers with repetitive
amino acid sequence synthesized through recombinant bacterial or mammalian
expression. Compared to synthetic polymers which requires synthetic chemistry and
additional purification steps, genetically engineered polymers due to recombinant
expression are synthesized using cellular expression. This also provides precise control
over chain length and structure and may be easier to scale up (Cappello et al., 1990;
Frandsen and Ghandehari, 2012; Urry et al., 2010). Protein polymers as drug carriers
also offer advantages in providing non-immunogenicity, biocompatibility and
biodegradability due to its amino acid composition. Several protein polymeric drug
carriers have been proposed as drug carriers such as silk-like polypeptides (SLPs)
(Valluzzi et al., 2002), silk-elastin-like polypeptides (SELPs) (Megeed et al., 2002) and
elastin-like polypeptides (ELPs) (Urry, 1997).
ELPs are protein polymers that are derived from human tropoelastin (Urry et al., 1976)
and consists of repetitive amino acid sequence of (VPGXG)l where X is the guest residue
and l represents the number of such repeats. ELPs are also called environmentally
responsive polymers because they exhibit reversible phase separation property above a
transition temperature called Tt, a property not demonstrated by SLPs and SELPs. This
Tt is highly tunable depending upon the nature of X, concentration and number of
pentamer repeats (Mackay et al., 2010; Meyer and Chilkoti, 2004). Another interesting
5

phenomenon that ELPs demonstrate is nanoparticle assembly utilizing diblock copolymer
sequences. These diblocks are generated by fusing an ELP polypeptide having
hydrophobic X (isoleucine) to an ELP polypeptide having hydrophilic X (serine) such as
(VPGIG)n1-(VPGSG)n2 or vice versa. For instance, diblock ELPs with amphiphilic
sequence have been successfully demonstrated to undergo nanoparticle assembly for
different applications including cellular internalization (Sun et al., 2011b), cytosolic co-
assembly and sorting(Shi et al., 2014), drug delivery(Shah et al., 2013; Shi et al., 2013)
and tumor targeting(Simnick et al., 2011). These diblock copolymers remain soluble
below critical micelle temperature (CMT) but assemble into nanoparticles with 50-100 nm
in diameter. Since ELPs are amenable to genetic engineering, they can also be fused
with different functional domains at the genetic level which can be used to study different
applications including cell-trafficking, drug delivery, imaging and targeting (Despanie et
al., 2016). For instance, ELP fused to single chain variable fragment of CD20 targeting
antibody has been demonstrated as a potential therapeutic in a mouse lymphoma mouse
model which outperformed the clinically approved Rituximab (Aluri et al., 2014). A fusion
between ELP and lacritin, a mitogen protein found in tears has been demonstrated to
treat ocular abrasion wounds (Wang et al., 2014). ELP fusions targeting the tumor
vasculature displaying integrin receptors have also been demonstrated. Vicrostatin, a
member of the disintegrin protein family obtained from viper venom when fused to ELP
promoted tumor accumulation in orthotopic breast cancer mouse model compared to
vicrostatin alone (Janib et al., 2014). In contrast to ELPs fused with protein domains, ELP-
drug conjugates have also proved to be potent therapeutics. ELP was generated
recombinantly with eight cysteine residues at the C terminus and conjugated to
6

doxorubicin at Cys residues using heterobifunctional linker resulting in self-assembly of
drug at the core and hydrophilic ELP corona. These self-assembling chimeric
polypeptide-doxorubicin conjugate nanoparticles were demonstrated to abolish tumors
after a single injection compared to free doxorubicin (MacKay et al., 2009). ELPs have
also demonstrated applications in diabetes, cardiovascular diseases and regenerative
medicine. Fusion of ELP to glucagon-like peptide 1 (GLP-1), which promotes insulin
release from pancreatic β-cells was designed as a subcutaneous depot to reduce blood
glucose levels and is currently being evaluated in the clinic (Amiram et al., 2013).
Similarly, fusion between ELP and Vasoactive intestinal peptide (VIP), a ligand for G
protein coupled receptors causing vasodilation has been reported to treat hypertension
(Despanie et al., 2016). ELPs with ability to crosslink into hydrogels when covalently fused
with QK peptide, an angiogenic peptide mimicking the receptor-binding region of vascular
endothelial growth factor (VEGF), promoted human umbilical vein endothelial cell
(HUVEC) proliferation with over 100% viability compared to HUVECs supplemented with
soluble QK peptide (Cai et al., 2014). These applications show strong precedents for ELP
fusions in different nanomedicine applications.
SLPs are protein polymers derived from silk producing silkworms and spiders. Two of the
most extensively studied SLPs are silkworm silk fibroin from Bombyx mori with amino acid
sequence [GAGAGS]n and spider silk fibroin from Nephila clavipes with amino acid
sequence [SGRGGLGGQGAGAAAAAGGAGQGGYGGLGSQGT]n (Numata and Kaplan,
2010). Silk nanoparticles from Bombyx mori with 50 nm particle radius have been
reported as a carrier for delivery of model drug curcumin to mesenchymal stem cells
without any cytotoxic effects (Perteghella et al., 2017). Similarly, silk-fibroin particles have
7

been used as carriers for delivery of proteins such tyrosinase and horseradish peroxidase
(Kim et al., 2017) and small molecules such as rhodamine B and crystal violet
(Mottaghitalab et al., 2015). Similarly, spider silk block copolymers generated by fusing
spider silk motif with cell targeting motifs, cell penetrating peptides, signal peptides of
virus and/or tumor-homing peptides have been demonstrated for drug delivery
applications (Numata and Kaplan, 2010).
SELPs are recombinant protein polymers with motifs containing both silk-like repeats
(GAGAGS)n and elastin-like repeats (VPGXG)n. Due to the fusion of these silk and
elastin-like repeats, SELPs assemble into micellar-like particles with core made up of less
aqueous soluble silk blocks and corona made up of highly aqueous soluble elastin blocks.
This assembly is highly tunable by varying the ratio of silk-to-elastin blocks (Xia et al.,
2011). SELPs have been demonstrated mostly for intratumoral adenoviral gene delivery.
For instance, SELP mediated virus delivery has been demonstrated in fibrosarcoma S-
180 tumor xenografts in immunocompetent mice and Head and Neck Squamous Cell
Carcinoma (HNSCC) xenografts in nude mice (Gustafson and Ghandehari, 2010).
Similarly, SELP hydrogels with intermittent matrix metalloproteinase (MMP) responsive
sequence have also been reported in mouse tumor model of HNSCC (Price et al., 2015).

1.3.1 Triple Negative Breast Cancer
Breast cancer is the second most common type of cancer with over 1.3 million newly
diagnosed cases worldwide each year (Grayson, 2012). Over the past four decades,
chemotherapeutic drugs have significantly improved breast cancer survival rates from
35% to 77%; however, there remain nearly half-a-million deaths from the disease each
8

year(Demers, 1994; Grayson, 2012; Jordan, 1993; Perry and Wiseman, 1999). Until a
decade ago, cytotoxic chemotherapy remained the primary treatment option for advanced
breast cancer(Foulkes et al., 2010). Chemotherapy requires a balance between dose-
limiting side effects and the opportunity to act on a target to halt or reverse tumor growth.
It has become clear that validated chemotherapeutics, such as paclitaxel and doxorubicin,
benefit from drug carriers that improve this balance between toxicity and
efficacy(Barenholz, 2012; Hawkins et al., 2008; Schroeder et al., 2012). One of the most
successful examples is paclitaxel pre-loaded onto albumin, called Abraxane
TM
. Approved
for breast cancer in 2005, a randomized clinical trial demonstrated that it doubled the
objective response rate and halved the incidence of severe neutropenia. Beyond
Abraxane
TM
, next generation drug carriers offer the opportunity to: i) sequester drug,
thereby reducing side effects; ii) utilize target-mediated delivery and release; iii) direct
multiple modalities tumors (drugs, proteins, imaging agents); and iv) facilitate combination
drug therapies by mitigating dose-limiting toxicity for one agent (Conlin et al., 2010;
Mirtsching et al., 2011). When fully realized, these strategies may revolutionize small-
molecule chemotherapy.
Since approval of Abraxane
TM
, fundamental improvements to breast cancer treatment
have been achieved through the classification of patients into molecular subtypes. For
example, a significant proportion (20-30%) of breast cancer is positive for the HER2
receptor, for which biologics (trastuzumab, approved 2006) and receptor tyrosine kinase
inhibitors (lapatinib, approved 2007) have entered the clinic(Hurvitz et al., 2013).
Alternatively, more than half of breast cancers are positive for the estrogen and/or
androgen receptors(Arpino et al., 2005), which respond to aromatase therapy
9

(exemestane, approved 2005). Although not chemotherapeutics, drugs like trastuzumab
and aromatase inhibitors also have dose-limiting side effects such as cardiovascular
cytotoxicity and endometrial effects (Grilli, 2006; Seidman et al., 2002). While
encouraging, there remain significant populations for which these therapies cannot work.
12 to 17% of breast cancer patients are negative for androgen receptor, estrogen
receptor, and HER2, and these patients are defined by triple-negative breast cancer
(TNBC)(Foulkes et al., 2010). Due to lack of any specific antigens available for targeting,
no specific targeted treatment is available for TNBC. However, a large proportion of TNBC
cases overlaps with a group identified by genomic clustering as ‘basal-like’, which is
associated with two biomarkers: i) epidermal growth factor receptor (EGFR) and/or ii)
cytokeratin 5/6 (Foulkes et al., 2010; Perou et al., 2000; Yunokawa et al., 2012). Most
(94%) ‘basal-like’ TNBC tumors depend on the mammalian target of rapamycin (mTOR)
to mediate proliferation(Yunokawa et al., 2012; Zhang et al., 2014). This observation has
maintained interest in repurposing a cytostatic class of molecules called rapalogues to
treat cancers including TNBC.

1.3.2 Rapalogues
Rapamycin, the first rapalogue, is a potent macrolidic small molecule which was isolated
as a secondary metabolite from soil bacterium Streptomyces hygroscopicus found in
Easter Island(Vezina et al., 1975). Rapamycin possess antifungal properties but exhibits
cell inhibition and immunosuppressive properties in mammalian cellular assays.
Rapamycin’s anti-proliferative mechanism of action was first discovered in yeast via
binding to downstream target of rapamycin, TOR (Heitman et al., 1991). TOR is a large
10

290 kDa Ser/Thr kinase which is highly conserved in eukaryotes from yeast to mammals,
and mammalian target of rapamycin, mTOR was eventually discovered in
humans(Benjamin et al., 2011). There are two functionally distinct mTOR complexes:
mTORC1 and mTORC2 which play a role in different cellular responses. mTORC1
signaling cascade is responsible for mRNA translation of proteins including elongation
factors and ribosomal proteins; and cap dependent protein translation required for G1-to-
S phase transition of cell cycle(Faivre et al., 2006). While mTORC2 is responsible for
actin cytoskeletal organization and cell polarization (Jacinto et al., 2004) which has been
linked to tumor cell mobility and metastasis(Zhou and Huang, 2011). Rapamycin binds to
a cytosolic protein called FK-506 binding protein 12 (FKBP) and the FKBP-rapamycin
complex further binds to and inhibits mTORC1 (not mTORC2) resulting in cell
inhibition(Benjamin et al., 2011). Due to this unique mechanistic action, which is
independent of binding to cell surface antigens, rapamycin has been extensively studied
as anti-cancer drug for treating TNBC. However, Rapa has low solubility(Simamora et al.,
2001) and poor bioavailability(Gabardi and Baroletti, 2010; Stenton et al., 2005)
accompanied with dose-limiting side effects, which include pulmonary and
nephrotoxicity(Marti and Frey, 2005; Pham et al., 2004) which has inspired development
of semi-synthetic rapamycin analogs, collectively called rapalogues with comparatively
improved pharmacokinetic properties. Two of the rapalogues, Temsirolimus (Toricell
TM
)
as IV infusion for renal cell carcinoma and Everolimus (Afinitor
TM
) as oral tablets for
advanced kidney cancer have entered the clinic as FDA approved drugs. A recent clinical
trial of everolimus in breast cancer revealed that 75% of patients experienced adverse
events such as oral sores, pulmonary toxicity, myelosuppression, and renal toxicity that
11

necessitated a reduction in dose and 10% discontinued treatment. Despite these
limitations, everolimus was approved because it doubled progression-free survival (Beck
et al., 2014). While approved for oral delivery, their significant toxicity prevents a number
of patients from maintaining this therapy. Furthermore, Temsirolimus, which is an ester
prodrug of rapamcyin, formulated as an ethanolic, non-aqueous IV infusion to overcome
its poor solubility also promotes dermatological and hypersensitivity reactions(Danesi et
al., 2013; Gomez-Fernandez et al., 2012). Similar to Paclitaxel and Doxorubicin which
are significantly benefited by employing use of albumin (Abraxane
TM
) and liposomes
(Doxil
TM
) as drug carriers respectively, the rapalogues may benefit from advanced drug
carriers.

1.3.3 Cognate drug receptors for rapalogue drug delivery
Fusion between functional protein domains and ELPs have demonstrated significant
advances as cell trafficking agents, therapeutics, theranostic and targeting agents
(Despanie et al., 2016). To further advance this strategy of using fusion hybrids for small
molecule delivery, we have demonstrated re-engineering of cognate drug receptors that
employs the natural drug targets itself for drug delivery. The first demonstration was
successfully shown by fusing FK-506 binding protein 12 (FKBP) to ELP nanoparticle for
intravenous rapamycin delivery(Shi et al., 2013). FKBP is the cytosolic target of
rapamycin and its sister rapalogues (Benjamin et al., 2011), hence, the protein was re-
engineered and attached to ELP at the genetic level for expression and purification of
FKBP-ELP fusion proteins as rapamycin carriers. Apart from exploring FKBP-Rapa
protein-ligand pair, there are several other drug receptor-small molecule interactions
12

existing in nature that can be used for drug delivery applications. The strategy of using
drug receptors for systemic delivery offers several advantages like (i) natural high affinity
towards the small molecule which circumvents the need for any chemical conjugation (ii)
the entire product is made up of natural amino acid composition, which provides
biocompatible and biodegradable nature, (iii) the specificity towards small molecule can
be controlled by using respective drug targets, thus avoiding any non-specific interactions
and (iv) the formulations are equipped of solubilizing the drugs without use of any organic
solvents thereby eliminating vehicle toxicity. Improving upon the FKBP-ELP nanoparticle
for intravenous rapamycin delivery, we have synthesized second generation FKBP-ELP
carriers that exhibit high molecular weight ~ 100 kDa and small particle size ~ 10 nm
radius designed for subcutaneous delivery of rapamycin through lymphatic absorption
from site of injection.

1.4 Bioresponsive Therapeutics
Bioresponsive therapeutics can be defined as agents that can detect a biological cue and
respond to such triggers (Prasad et al., 2016; Takemoto et al., 2014; Wilson and
Guiseppi-Elie, 2014). Such a dual response can be used to reduce the side effects by
designing therapeutics to only respond to cues displayed by diseased tissue or
pathological agents. Biosensing applications have been reported to target cues such as
pH (He et al., 2013), heat or magnetic stimuli (Mura et al., 2013), prodrug based (Giang
et al., 2014) or antibody-directed enzyme prodrug therapy (Bagshawe et al., 2004) and
very recently use of bispecific ‘Bites’ therapies that rely on cytotoxic T cells (Stieglmaier
et al., 2015; Suryadevara et al., 2015). Although effective, these approaches do not target
13

pathological agents that are soluble, free flowing in the systemic circulation and
multimeric in nature. Such multimeric ligands including proteins and antibodies are the
primary pathological agents in several diseased conditions like Pulmonary Alveolar
Proteinosis (Trapnell and Whitsett, 2002) and autoimmune diseases such as Systemic
Lupus Erythematosus (Choi et al., 2012), Graves disease (Prabhakar et al., 2003) and
Sjögren’s syndrome (Sumida et al., 2012). To address this untapped niche, we have
demonstrated a reproducible strategy that takes into account the very multimeric nature
of these ligands as the trigger indicator using protein polymer phase separation.

1.4.1 Genetically Engineered Protein Polymers for Biosensing Applications
Polymer phase separation has been previously explored for various biosensing
applications. Synthetic polymers like poly(N-isopropylacrylamide)(Stayton et al., 1995),
poly(N,N-diethylacrylamide)(Ding et al., 2001) and N-4-
phenylazophenylacrylamide(Shimoboji et al., 2002a) have been reported to respond to
stimuli, such as temperature and light, to control binding of small molecules to target
proteins. In comparison to synthetic polymers, protein-polymers may have added
advantages as smart polymers due to recombinant production that enables their precise
linkage with functional proteins. For example, the ELP protein-polymers are produced
using cellular translation machinery, which promotes control over their design,
arrangement, and reproducibility and can eliminate the need for chemical
bioconjugation(Despanie et al., 2016). ELPs fused with calmodulin have been reported
to undergo phase separation in response to binding of Ca
2+
, which was reversed by
chelation of Ca
2+
by EDTA(Kim and Chilkoti, 2008). An alternative design strategy
14

developed smart ELPs with negatively charged calcium-binding motifs to respond upon
neutralization by divalent Ca
2+
cations(Hassouneh et al., 2013). Despite these innovative
biosensing applications, no approaches have defined a strategy based on multimerization
as a workable strategy to respond to target proteins. To address this untapped niche, we
first demonstrated that ELP dimerization is a viable technique to detect dimeric small
ligand molecules(Dhandhukia et al., 2013). Taking this concept to the next logical step,
we successfully extended this defined ELP crosslinking strategy to detect and respond to
a large multimeric protein. With successful implementation of this strategy to proof of
concept small molecules and proteins, it may become feasible to design ELPs into
diagnostics and therapeutics that respond to multimeric macromolecules such as
antibodies, cytokines, and tyrosine kinase receptors. Due to the adaptability and
specificity of this strategy, these fusion protein polymers may be evaluated for diverse
applications in the detection and treatment of diseases.

1.5 Conclusion
Genetically engineered protein polymers provide multi nanomedicine applications due to
their genetic make-up which enables precise control over fusion of peptides, proteins,
antibody fragments and drug receptors. The recombinant expression and purification
provides easy scale-up and cheap manufacturing costs compared to synthetic polymer
synthesis or biologics from mammalian expression systems. Furthermore, these protein
polymers can be designed to assemble into different structures including nanoparticles
and nanofibers. This dissertation summarizes two of the many applications by protein
polymers – drug delivery and biosensing applications. The use of these recombinant
15

protein polymers for human use has not yet fully developed. However, when fully
translated, the strong pre-clinical applications suggest they may revolutionize current
nanomedicine treatments.

16

Chapter 2
Berunda Polypeptides: Multi-headed fusion proteins for subcutaneous
delivery of rapamycin to breast cancer in vivo

2.1 Abstract
Recombinant Elastin-Like Polypeptides (ELPs) serve as attractive scaffolds for
nanoformulations because they can be charge neutral, water soluble, high molecular
weight, monodisperse, biodegradable, and decorated with functional proteins. We
recently reported that fusion of the FK-506 binding protein 12 (FKBP) to an ELP
nanoparticle (FSI) reduces rapamycin (Rapa) toxicity and enables intravenous (IV)
therapy in both a xenograft breast cancer model and a murine autoimmune disease
model. Rapa has poor solubility, which leads to variable oral bioavailability or drug
precipitation following parenteral administration. While IV administration is routine during
chemotherapy, cytostatic molecules like Rapa would require repeat administrations in
clinical settings. To optimize FKBP/Rapa for subcutaneous (SC) administration, this
chapter expands upon first-generation FSI nanoparticles (Rh ~ 25 nm) and compares
them with two second-generation carriers that: i) do not self-assemble; ii) retain a
hydrodynamic radius (Rh ~ 7 nm) above the renal filtration cutoff; iii) increase tumor
accumulation; and iv) have either one (FA) or two (FAF) FKBP domains per protein.
Carriers were compared for equilibrium binding, drug retention, formulation stability,
toxicity, efficacy, and bio-distribution. Named after the two-headed bird in Hindu
mythology, the ‘Berunda polypeptide’ FAF retained formulation stability for one month,
eliminated toxicity observed with free drug after SC administration, increased tumor
17

accumulation in MDA-MB-468 breast tumor xenografts, decreased phosphorylation of a
downstream target, and suppressed tumor growth. This study demonstrates the versatility
of recombinant protein-polymers to investigate drug carrier architectures; furthermore,
their facilitation of SC administration of poorly soluble drugs, like Rapa, may enable
chronic self-administration in patients.

2.2 Introduction
Systemic delivery of potent and hydrophobic drugs remains challenging due to the
solubility and toxicity profile associated with such molecules (Moudi et al., 2013; Tacar et
al., 2013; Yared and Tkaczuk, 2012). One such drug, sirolimus is the clinical formulation
of rapamycin (Rapa), which is indicated as an oral immunosuppressive for renal allograft
rejection (Dumont and Su, 1996; Kahan, 2000; MacDonald and Group, 2001) and orphan
Lymphangioleiomyomatosis (Moir, 2016; Taveira-DaSilva et al., 2011). Despite approval
for these treatments, Rapa has low solubility (Simamora et al., 2001) and poor
bioavailability (Gabardi and Baroletti, 2010; Stenton et al., 2005) accompanied with dose-
limiting side effects such as pulmonary and nephrotoxicity (Marti and Frey, 2005; Pham
et al., 2004) which limits its ut-most potential. With the discovery that the mammalian
target of rapamycin complex 1 (mTORC1) is inhibited in tumor cells by a complex between
Rapa and the FK-506 binding protein 12 (FKBP), Rapa and its structural analogs were
developed to treat cancer (Benjamin et al., 2011). However, due to poor oral
bioavailability and grade 3-4 adverse events such as skin rashes, anemia, and stomatitis,
maintenance of rapalogue therapy remains a challenge (Danesi et al., 2013; de Oliveira
et al., 2011; Gabardi and Baroletti, 2010; Gomez-Fernandez et al., 2012). Earlier attempts
18

have been made to solubilize and formulate Rapa using organic solvents and emulsions
(Eshleman et al., 2002; Hackstein et al., 2002; Sun et al., 2011c); however, there have
been side effects reported with the vehicle composition (Gelderblom et al., 2001;
Hennenfent and Govindan, 2006). With the goals of improving the solubility and toxicity
profile of Rapa, we recently reported high efficiency drug loading and toxicity-free in vivo
efficacy through a recombinant fusion between its native protein receptor, FKBP, and an
elastin-like polypeptide (ELP) nanoparticle (FSI) (Shah et al., 2013; Shi et al., 2013).
ELPs are genetically-encoded protein polymers derived from human tropoelastin (Urry et
al., 1976) with the amino acid sequence (Val-Pro-Gly-Xaa-Gly)n where Xaa represents
the guest residue and n represents the number of pentameric repeats. ELPs reversibly
phase separate above an inverse transition temperature (Tt), which can drive assembly
of fused peptides (Urry, 1988, 1992). They make attractive scaffolds for drug delivery
applications because they are biodegradable, can be genetically fused with different
protein domains, peptides, or therapeutics, and can be purified from prokaryotic systems
without chemical synthesis (Despanie et al., 2015). In our previous report, FKBP was
attached to an ELP diblock copolymer (SI) comprised of a hydrophilic ELP at the amino
terminus (Xaa = Ser, n = 48 repeats) followed by a hydrophobic ELP (Xaa = Ile, n = 48
repeats) (Table 1). Known as FSI, this fusion protein was purified from E. coli, loaded
with Rapa, and evaluated for efficacy using the MDA-MB-468 tumor xenograft model (Shi
et al., 2013). MDA-MB-468 are triple negative breast cancer cells (TNBCs) lacking
estrogen, progesterone and HER2+ receptors (Chavez et al., 2010). In addition, these
cells are devoid of PTEN phosphatase, which results in extensive phosphorylation of AKT
kinase and highly active mTORC1 signaling (DeGraffenried et al., 2004; Faivre et al.,
19

2006). FSI loaded with Rapa not only improved the solubility of the drug but was also
efficacious in suppressing tumor growth when injected intravenously (IV), without
significant systemic toxicity that was observed with free drug treatment (Shi et al., 2013).
Although FSI-Rapa is efficacious by IV administration, it remained unknown whether the
assembly of a nanoparticle was advantageous for subcutaneous (SC) administration;
furthermore, this article explores how the ELP architecture influences the carrier’s bio-
distribution and toxicity via SC administration. To examine this relationship, two new
second generation carriers were designed for enhanced systemic circulation with a
comparatively higher molecular weight and a smaller hydrodynamic radius. A new FKBP-
ELP carrier was synthesized (FA) by attaching FKBP at the amino terminus of A192 ELP
(Xaa = Ala, n = 192 repeats) that remains soluble at physiological temperature. To
compare the effect of FKBP valency on drug binding and release, a carrier with two-
headed ‘Berunda’ architecture (FAF) was also synthesized with FKBP domain attached
at both the amino and carboxy termini of A192 ELP. The backbone ELP ‘A192’ with MW
of 73.5 kDa was selected to evaluate the soluble FA and FAF formulations due to its
favorable pharmacokinetics determined using micro-PET imaging in orthotopic breast
cancer implanted nude mice when compared to relatively shorter ELPs, nanoparticle ELP
or similar MW ELP with Xaa = Ser (S192)(Janib et al., 2013). The nomenclature, amino
acid sequence and physicochemical properties of all FKBP-ELPs evaluated in this
chapter are shown in Table 1. Unlike FSI, FA and FAF are neither amphiphilic nor do they
assemble into nanoparticles at physiological temperatures. These carriers were
compared for binding thermodynamics, drug retention and stability, in vivo efficacy and
bio-distribution in a human breast tumor xenograft model (Figure 1).
20

Formulating rapalogues for systemic delivery free of adverse effects remains a challenge
(Danesi et al., 2013; de Oliveira et al., 2011; Gabardi and Baroletti, 2010; Gomez-
Fernandez et al., 2012). To address these challenges, multiple materials have been
proposed as advanced drug carriers in cancer models such as poly(lactide-co-glycolide)
nanoparticles (Acharya et al., 2009), polyethyleneglycol-block-poly(ɛ-caprolactone)
nanoparticles (Doddapaneni et al., 2015), albumin-bound nanoparticles (Cirstea et al.,
2010) and multi-drug loaded ‘triolimus’ micelles (Hasenstein et al., 2012). Compared to

Figure 1. Optimization of FKBP-ELP architecture to enhance the stability and efficacy of Rapa
delivery. Rapalogues are potent cytostatic molecules with anti-cancer efficacy; however, their poor
solubility limits their safety and efficacy by oral and IV delivery. This study describes a new protein-
based strategy to deliver Rapa via SC delivery using fusions between the FKBP protein and ELP (Table
1). This side-by-side comparison evaluates soluble ELPs with one (FA) or two (FAF) drug binding
domains with a nanoparticle ELP (FSI). While all three carriers can bind Rapa, reduce injection site
toxicity, and suppress a human breast cancer xenograft (MDA-MB-468), the Berunda polypeptide
named FAF performed best with respect to drug loading, drug retention, formulation stability, tumor
efficacy and bio-distribution following SC administration.

21

these formulations, the carriers evaluated in this chapter differ in two fundamental ways.
First, while other carriers non-specifically carry the drug in a hydrophobic nanoparticle
core or albumin pocket, FKBP-ELP carriers employ Rapa’s biological receptor, which has
high specificity/affinity binding necessary to retain the drug for long durations in the body.
Secondly, both FKBP and ELP are biodegradable and biocompatible polypeptides that
can be produced at high yield and purity through scalable bacterial fermentation. These
FKBP-ELP nanoformulations solubilize the drug free of any excipients or organic
solvents, thereby eliminating injection site toxicity, which occurs with the free drug
formulated using standard emulsions, such as Cremophor-EL. Among the carriers
examined herein, FAF performs with the best combination of high drug loading, long drug
retention, and particle size stability. While facilitating SC administration of Rapa, FAF
further augments tumor accumulation and suppresses tumor growth.

2.3 Materials and Methods
2.3.1 ELP gene design and cloning
FA and FSI cloning was performed as previously described (Dhandhukia et al., 2013).
Cloning of FAF was done by fusing an FKBP gene in frame to the 3’ end of the gene for
FA. To fuse another FKBP gene to the carboxy terminus, a new gene was synthesized
on ampicillin-resistant pIDTsmart vector (Integrated DNA technologies, Coralville, IA) with
three restriction cut sites: XbaI, BseRI and BamHI. This vector was designed such that
the FKBP gene was flanked with cut sites for BseRI and BamHI with XbaI at the 5’ end
and BamHI at the 3’ end of the oligonucleotide. The pIDTsmart vector was double
digested with XbaI and BamHI and the FKBP gene was isolated by 1% agarose gel
22

electrophoresis and purification (28-9034-70, GE Healthcare Life Sciences, Marlborough,
MA). The FKBP gene was then ligated into a pET25b (+) vector (EMD Millipore, Billerica,
MA) double digested with same set of XbaI and BamHI enzymes. In a second cloning
step, the modified pET25b (+) vector containing the FKBP gene was double digested with
BseRI and BssHII and gel purified. The appropriate fragment containing the FKBP gene
was then ligated to the 3’ end of the gel purified FA gene, which was isolated from a
pET25b (+) vector double digested by AcuI and BssHII. Restriction enzymes were
purchased from New England Biolabs®

Inc (Ipswich, MA). The in-frame amino acid
sequence was confirmed by diagnostic digestion and DNA sequencing.

2.3.2 FKBP-ELP expression and purification
The pET25b (+) vectors encoding genes for FSI, FA, or FAF were transfected into BLR
(DE3) E. coli competent cells (69053, EMD Millipore), plated onto agar with 100 µg/mL
ampicillin, and incubated overnight at 37 C for growth of bacterial colonies. A liter of
bacterial culture was expressed by overnight inoculation of bacterial cells at 37°C
obtained by growing a single colony in 50 mL terrific broth starter media (12105, Mo Bio
Laboratories, Carlsbad, CA) supplemented with 100 µg/mL carbenicillin. Protein
harvesting by cell lysis was performed as previously described (Dhandhukia et al.,
2013)and fusion proteins were purified by Inverse Transition Cycling (Hassouneh et al.,
2010). To achieve sterility, the purified protein was filtered through a 200 nm sterile
Acrodisc
®
25 mm filters (PN 4612, Pall Corporation, Port Washington, NY) and assayed
for concentration using Beer Lambert’s law:
Protein concentration (M) =
( 𝐴 280
− 𝐴 350
) × 𝑑𝑖𝑙𝑢𝑡𝑖𝑜𝑛 𝑓𝑎𝑐𝑡𝑜𝑟 𝑀𝐸𝐶 ×𝑙 Eq. 1
23

where M is molar concentration, A280 and A350 are absorbance at 280 and 350 nm
respectively, l is the path length (cm) and MEC is the estimated molar extinction
coefficient at 280 nm: 11,585 M
-1
cm
-1
for FA and FSI and 20,190 M
-1
cm
-1
for FAF (Pace
et al., 1995). Final yields obtained were 50-60 mg/L.

2.3.3 ELP physicochemical characterization.
The purified fusion proteins were characterized for physicochemical properties using
SDS-PAGE, optical density, and dynamic light scattering. 6-12 µg ELPs were mixed with
SDS Laemmli loading buffer (1610747, Bio-Rad, Hercules, CA) containing 10% v/v β-
mercaptoethanol, heated at 90 C for 5 mins before loading onto 4-20% gradient Tris-
Glycine-SDS PAGE gel (58505, Lonza, Walkersville, MD). The gel was stained using 10%
w/v copper chloride and imaged using a ChemiDoc
TM
Touch Imaging system (Bio-Rad)
(Figure 2a). The peak areas per gel lane were calculated using ImageJ (National
Institutes of Health, Bethesda, MD) and purity was estimated using the following equation:
% purity =
𝐴 𝑝𝑒𝑎𝑘 𝐴 𝑡𝑜𝑡 ×100 Eq. 2
where Apeak is the area of the protein band peak and Atot is the total area under all the
peaks per lane.
Temperature-concentration phase diagrams were obtained by measuring optical density
at 350 nm on a UV-Vis DU 800 spectrophotometer (Beckman Coulter, Brea, CA). A
temperature ramp (1 C/min, measured every 0.3 C) was performed for different
concentrations of FKBP-ELPs with and without Rapa loading using thermal mount
microcells (Beckman Coulter). Phase transition temperatures were defined where the first
24

derivative of the optical density vs. temperature was maximal (Figure 2 b, c). The data
points were fit to the dotted line, which followed this relationship:
Tt = b – m [Log10(concentration)] Eq. 3
Where b is the intercept temperature (°C) at a reference concentration of 1 μM and m is
the slope, which can be interpreted as the decrease in Tt upon a 10-fold increase in
concentration.
Particle sizes and stability were evaluated by measuring the hydrodynamic radius (Rh)
using DLS (Figure 2 d, e). 25 µM concentration samples were filtered through 200 nm
sterile Acrodisc
®
13 mm filters (PN 4454, Pall Corporation). 60 µL of each sample was
loaded in triplicate in a 384 well black plate and covered with 20 µL mineral oil. The plate
was gently centrifuged at 15 °C to remove air bubbles and Rh was measured using the
Wyatt Dynapro plate reader (Santa Barbara, CA). The reported values are presented as
mean ± SD (n=3). The particle morphology of A192, FA and FAF was interpreted and
analyzed at room temperature using size exclusion chromatography and multiangle light
scattering (SEC-MALS). About 100 µg protein was injected into a shodex KW-803 size
exclusion column using sterile filtered PBS at the rate of 0.5 ml/min and eluents were
analyzed on a Wyatt Helios light scattering detector (Santa Barbara, CA). Data was fit to
a Debye plot to determine the Rg. The Rg/Rh ratio was used to interpret particle
morphology.

2.3.4 Isothermal titration calorimetry of Rapa interactions with FKBP-ELPs.
The drug binding interactions between Rapa (R-5000, LC Laboratories Inc., Woburn, MA)
and FKBP-ELPs were studied using ITC (Figure 3, 4) on a MicroCal PEAQ ITC (Malvern
25

Instruments Ltd, Worcestershire, United Kingdom). The reference cell of the calorimeter
was filled with water and all binding studies were performed at 37 °C. Reverse titration
were performed with a fixed Rapa concentration in the calorimeter cell and FKBP-ELPs
in the titration syringe. The drug and all the FKBP-ELPs were solubilized in the same
buffer (2.4% v/v DMSO in PBS) to prevent background heat of release due to differences
in buffer composition. Briefly, 300 µl of 8 µM Rapa was carefully loaded into the
calorimeter cell and a titration syringe filled with 50 µM FAF or 100 µM FA/ FSI was
injected (3 µl) into the calorimeter cell 12 times. The resulting isotherm was fitted to a ‘one
set of sites’ binding model in offset mode using the MicroCal PEAQ ITC analysis software
(Malvern Instruments) to estimate affinity (Kd), stoichiometry and thermodynamics (ΔH,
ΔS and ΔG).

2.3.5 Drug loading and formulation preparation for in vivo administration.
Drug loading was performed using two-phase solvent evaporation technique. 200-400 µM
FKBP-ELP (2 mL) in PBS was equilibrated in a glass vial at 35 °C for 10 mins followed
by addition of 200-400 µM Rapa (2mL for FSI loading and 6 mL for FA/FAF loading) in a
hexane/EtOH mixture (70/30 % v/v) to obtain a two-phase mixture of FKBP-ELP in PBS
at the bottom and Rapa in hexane at the top. The organic phase was evaporated under
mild flow of dry N2 gas and the remaining aqueous solution containing Rapa loaded
FKBP-ELPs was centrifuged (13,000 RPM, 10 min, 37 C) to remove free drug pellet.
FSI-Rapa was dialyzed overnight in PBS at 4 °C to remove the fast-eluting drug from the
hydrophobic core, as observed previously (Shi et al., 2013). The supernatant was filtered
using 200 nm sterile Acrodisc
®
25 mm filter (PN 4612, Pall Corporation) and Rapa
26

concentration was determined at 280 nm by C-18 RP-HPLC column (186003033, Waters,
Milford, MA) using a calibrated standard curve. The RP-HPLC run was performed using
mobile phase A (water with 0.1% TFA) and phase B (methanol with 0.1% TFA) using a
gradient from 40% to 95% of phase B. Post quantification, drug-loaded formulations were
diluted in Dulbecco’s sterile PBS buffer (PBL01, Caisson labs, Smithfield, UT) to
concentrations required for the indicated dosage (mg/kg BW) and frozen at -80 °C as
aliquots for single use.

2.3.6 Drug retention and formulation stability using extended dialysis.
Drug loading was performed at room temperature for all FKBP-ELPs to prevent non-
specific binding of drug into the hydrophobic core of FSI nanoparticles (Shi et al., 2013)
and to achieve a ~ 1:1 drug binding ratio of Rapa to FSI. 150 µM Rapa loaded FKBP-
ELPs were dialyzed in 1:650 PBS sink conditions at 37 C using 20 kDa MWCO dialysis
cassettes (87735, Thermo Fischer Scientific, Waltham, MA). PBS sink was supplemented
with Penicillin-Streptomycin (30-002-CI, Corning
®
, Corning, NY) and buffer changes were
performed 2x on day 1 and every 48 h thereafter. 100 µL aliquots were collected from the
cassettes at fixed time intervals and were characterized for Rapa and FKBP-ELP
concentrations at 280 nm using RP-HPLC. The assay was halted upon observation of
turbidity. The data was fit by non-linear regression using a one-phase exponential decay
model with values presented as mean ± SD with 95% CI (n = 3) (Figure 5 a-c). Aliquots
withdrawn were filtered using 200 nm sterile Acrodisc
®
13 mm filters (PN 4454, Pall
Corporation) and evaluated for particle size at ~ 20-25 µM protein concentration using
27

DLS at 37 °C (n ≥ 3). Rh values for particle populations with greater than 90% by mass
are reported as the dominant species (Figure 5 d-f).

2.3.7 Tumor regression studies.
All animal experiments were conducted as per the guidelines of the American Association
of Laboratory Animal Care under approval by the USC Institutional Animal Care and Use
Committee. MDA-MB-468 cells were screened for major mouse pathogens and human
blood borne pathogens (Charles River) prior to implantation. A single injection of 1-2 x
10
6
cells in 100 µL FBS free media supplemented with 4 mg/mL matrigel (354262,
Corning
®
) was implanted into the right mammary fat pad of 7-8 weeks old female athymic
nude mice (Nude-Foxn1
nu
, Envigo Inc, Indianapolis, IN). Mice were randomized into
groups and treatment was started with average tumor size of 50-200 mm
3
. Tumor size
and BW was measured thrice a week and tumor volume was calculated using the
following equation:
Tumor Volume (mm
3
) =
𝑎 2
×𝑏 ×𝜋 6
Eq. 4
where a and b represents smaller and bigger tumor length respectively measured with an
electronic caliper. Two independent IV and SC tumor regression studies were performed.
Tumor implanted mice in the IV study were treated with 100 µL injections of PBS, FSI-
Rapa (0.25 mg/kg) and dose escalation of FAF-Rapa (0.025 - 0.75 mg/kg) which amounts
to 70 µM FSI and 3 - 100 µM FAF in final injections. (Figure 6). Mice displaying ulcerated
tumors were removed from the study. To capture the variability within and between
groups, individual tumors were tracked over the duration of the study as fraction of their
initial volume on day 1. For statistical comparison, the tumor burden by the last day of
28

treatment was compared between treatment groups. Tumor burden was defined by the
area under the growth curve in each mouse using the trapezoidal method as follows:
Tumor Burden = ∑ [
( 𝑓 𝑖 +1
+ 𝑓 𝑖 ) ( 𝑡 𝑖 +1
− 𝑡 𝑖 )
2
]
𝑡 𝑙𝑎𝑠𝑡 𝑖 =1
Eq. 5
where fi is fraction of initial tumor volume observed on day ti. To ensure homogeneity of
variance, the log10 transformed tumor burden (Eq. 5) by the last day of treatment was
compared with 1-way ANOVA between all the 6 groups (α = 0.05 with 95% CI, p = 0.006).
Tukey-Kramer post-hoc analysis was performed to test significance between the
individual groups (Figure 6 g) as reported in the results. Body weights are shown as
mean ± SD (Figure 6 h).
Tumor implanted mice in the SC study were treated with 150-200 µL injections of PBS,
Free Rapa (100% DMSO or DMSO: EtOH: Cremophor-EL: PBS in 1:1:2:6 % v/v ratio),
FAF-Rapa, FA-Rapa and FSI-Rapa all at fixed dose of 0.75 mg/kg which amounts to 125
µM FSI or FA and 62.5 µM FAF in final injections (Figure 7). Cremophor-EL was
purchased from Sigma-Aldrich (C5135). One mouse from the PBS group (M6) was
euthanized on day 40 at the humane end point of 1000 mm
3
tumor volume; therefore, the
fi determined on day 40 for M6 was used to calculate the tumor burden by the last day of
treatment. The study was analyzed by performing 1-way ANOVA on the log10 transformed
tumor burden (Eq. 5) by the last day of treatment, which showed significant differences
among the five 5 groups (α = 0.05 with 95% CI, p = 0.019). Tukey-Kramer post-hoc
analysis was performed to test significance between the individual groups (Figure 7f) as
reported in the results. For Kaplan-Meier survival analysis, tumors reaching four times the
initial volume (fi =4) was defined as the end point. The Log Rank (Mantel-Cox) test
performed on the entire study revealed significant difference between the survival curves
29

(α = 0.05 with 95% CI, p = 0.002). Individual treatment groups were compared to the PBS
treatment group using a Bonferroni correction (α = 0.05/4 comparisons = 0.0125) as
reported in the results. Body weights are shown as mean ± SD (Figure 7h).

2.3.8 Protein extraction and tumor western blot analysis.
24 hours after the last SC in vivo treatment, mice were euthanized and excised tumors
from all the groups were flash frozen in liquid nitrogen and stored at -80 °C until
processing for western blotting. Tumors weighing more than 50 mg from each group (n =
4) were thawed in tissue protein extraction buffer (78510, Thermo Fischer Scientific) in
the presence of protease inhibitor cocktail (P8340, Sigma-Aldrich) and phosphatase
inhibitor cocktail II, III (P0044, P5726 respectively, Sigma-Aldrich). Tumor lysate was
obtained by performing lysis in TriplePure zirconium prefilled tubes (D1032-30,
Benchmark Scientific, Edison, NJ) using Beadblaster
TM
24 Microtube Homogenizer
(D2400, Benchmark Scientific). Supernatant obtained by cold centrifugation of tumor
lysate was quantified for total protein concentration using Pierce BCA protein assay kit
(23227, Thermo Fischer Scientific).
80 µg protein was denatured, loaded onto SDS-PAGE gels as explained in the
physicochemical characterization and protein bands were transferred onto a
nitrocellulose membrane (IB23002, Thermo Fischer Scientific). Membrane was blocked
with 5% w/v nonfat dry milk in tris buffered saline (TBS) supplemented with 0.1% v/v
Tween 20 (TBST - 200 mM Tris, 1.5 M NaCL, pH 7.6) followed by immunoblotting with
primary monoclonal antibodies for p-p70 S6K1, p-4E-BP1, p-rpS6 and GAPDH (9234P,
13443S, 4858S, 5174 respectively, Cell Signaling Technology, Danvers, MA) (Figure 8,
30

9). Antibody dilutions and incubation time was performed as per manufacturers protocol.
After primary immunoblotting, membrane was washed with TBST (3x, 10 min) and
incubated with secondary horseradish peroxidase (HRP)-linked antibody (7074, Cell
signaling Technology) for 90 min at room temperature, washed with TBST (3x, 10 min)
and incubated with HRP substrate (E2400, Denville Scientific, Holliston, MA) for 1 min
prior to imaging using chemiluminescence (ChemiDoc
TM
Touch Imaging system, Bio-
Rad). Membrane was stripped of primary antibodies using stripping buffer (46430,
Thermo Fischer Scientific) for 45 min at room temperature and immunoblotted for GAPDH
which was used as an internal loading control. Protein expression levels were quantified
using Image J analysis (Figure 8a) on 8-bit, inverted images using the following equation:
Normalized intensity =
𝐼 𝑝𝑟𝑜𝑡𝑒𝑖𝑛 𝐼 𝐺𝐴𝑃𝐷𝐻 Eq. 6
where Iprotein is the integrated density of protein band of interest and IGAPDH is the integrated
density of respective GAPDH band. The results were analyzed by performing 1-way
ANOVA on the normalized intensity levels of p-rpS6, which showed a significant
difference among the 5 groups (α = 0.05 with 95% CI, p = 0.002). Tukey-Kramer post-
hoc analysis was then performed to test significance between the individual groups
(Figure 8b) as reported in the results.

2.3.9 Histopathological tissue examination of Rapa treated mice.
After 24 hours from the last SC in vivo treatment, mice from all the groups were
euthanized and major organs were collected for histopathological examination. Before
euthanasia, mice were anaesthetized with 2% v/v isoflurane gas with oxygen for whole
body blood perfusion. Heart, lungs, spleen, liver, kidney and skin were excised, and fixed
31

in zinc formalin (5701ZF, Thermo Fischer Scientific) overnight before preserving in 70%
ethanol. Appropriate size organ samples were then embedded in paraffin, sectioned in 5
µm thick tissue slices onto glass slides, and stained with hematoxylin and eosin (H & E).
The H & E stained tissues were then studied under a microscope for histopathological
changes analyzed by an unbiased blinded practicing pathologist (Figure 10a, Figure 11).

2.3.10 In vivo imaging of fluorescently labelled FKBP-ELPs.
FA, FAF and FSI in PBS were mixed with three molar excess of Cy5.5 NHS ester (47020,
Lumiprobe, Hallandale Beach, Florida) solubilized in DMSO and incubated overnight at 4
°C. Excess unreacted Cy5.5 was removed by loading the reaction mixture twice onto PD-
10 desalting columns (17-0851-01, GE Healthcare Life Sciences). Labeled fractions were
identified using SDS-PAGE and concentrated ten-fold using spin concentrators
(UFC503024, Amicon Ultra, 30 kDa MWCO). The labeled material was quantified with a
labeling efficiency of ~15 % on a UV-Vis spectrophotometer using the following equations:
CCy5.5 =
𝐴 679
× 𝑑𝑖𝑙𝑢𝑡𝑖𝑜𝑛 𝑓𝑎𝑐𝑡𝑜𝑟 209000 × 𝑙 Eq. 7
CFKBP-ELP =
[𝐴 280
− ( 0.09 × 𝐴 679
) ] × 𝑑𝑖𝑙𝑢𝑡𝑖𝑜𝑛 𝑓𝑎𝑐𝑡𝑜𝑟 𝑀𝐸𝐶 𝐹𝐾𝐵𝑃 −𝐸𝐿𝑃 × 𝑙 Eq. 8

Labeling efficiency (%) =
𝐶 𝐶𝑦 5.5
𝐶 𝐹𝐾𝐵𝑃 −𝐸𝐿𝑃 ×100 Eq. 9

Tumor implantation was performed as explained in the tumor regression study. Mice were
anaesthetized with 2% v/v isoflurane gas with oxygen followed by IV or SC injections of
~ 0.5 mg/kg Cy5.5 (80 µM) labelled FKBP-ELPs (530 µM) through tail vein or in the right
flank above the hind leg (n = 4 per group). Whole body dorsal and ventral scans were
imaged using the IVIS optical spectrum (Perkin Elmer, Waltham, MA) at 0, 4, 24 and 48
32

h post injection using 1 sec exposure time and small binning (Figure 13-15). Excitation
and emission filters for Cy5.5 were chosen to be 640 nm and 700 nm respectively. After
48 h, mice were euthanized and a small volume of blood was immediately withdrawn via
cardiac puncture. The carcasses were then dissected and individual organs along with
the blood withdrawn earlier were scanned for fluorescence (Figure 13, 15). Images were
analyzed using Living Image
®
software (Perkin Elmer). Regions of Interest (ROI) were
drawn on individual organs, and fluorescence from respective ROIs was quantified in Avg.
radiant efficiency with units [photons/sec/cm
2
/sr] / [µW/cm
2
] and plotted after subtracting
respective ROIs from control mice organs without Cy5.5 injections (Figure 13c, 15c). For
the SC study, results were analyzed by performing 1-way ANOVA on the log10
transformed Avg. radiant efficiency (n = 4, mean ± SD), which showed significant
differences between all the 3 FKBP-ELPs in kidneys, liver and tumor (α = 0.05 with 95%
CI, p = 0.0004, 0.0003 and 0.0004 respectively). Tukey-Kramer post-hoc analysis was
then performed to test significance between the carriers within each tissue as reported in
the results (Figure 13c). For the IV study, results were analyzed by performing paired t-
test on the log10 transformed Avg. radiant efficiency (n = 4, mean ± SD), which showed
statistically significant differences between FSI (IV) and FSI (SC) groups in liver, tumor
and spleen as shown in the results (Figure 15c).

2.4 Results and Discussion
Rapa is a highly potent drug with an unfavorable toxicity profile. While its cytostatic activity
prevents growth of some tumors, its application in human cancer treatment has been
limited by poor bioavailability, rapid clearance, and severe toxicity. Aiming to synthesize
33

a viable and safer Rapa formulation, we recently reported an ELP-based nanoparticle
drug carrier (FSI) that suppresses tumor growth in vitro and in vivo with reduced side
effects (Shi et al., 2013). To elucidate the implications of the ELP architecture on the
formulation stability and bio-distribution, we compared a library of related FKBP-ELPs for
binding thermodynamics, extended stability, in vivo efficacy and live optical imaging in a
human xenograft mouse model.

2.4.1 Characterization of FKBP-ELP carriers.
All FKBP-ELP fusions were expressed and purified from E. coli. Compared to our
previously reported FSI nanoparticles, the second generation carriers FA and FAF
maintain a comparatively smaller particle size with higher molecular weight (>80 kDa)
(Table 1). SDS-PAGE was used to determine the purity (Eq. 2) of FKBP-ELPs along with
their respective ELP backbones (Figure 2a). The precise molecular weights of all the
constructs was determined by analyzing samples on a MALDI-TOF mass spectrometer
(Table 1). Optical density measurements were used to characterize the temperature-
concentration phase diagram of ELP with and without FKBP (Figure 2b). Fusion of FKBP
to ELP minimally influences the ELP phase diagram; furthermore, Tt

follows an inverse
relationship with logarithm of the ELP concentration. Using the fit parameters (Eq. 3,
Table 1) for FKBP-ELPs, it is possible to estimate solubility profiles of all FKBP-ELPs at
physiological temperatures across concentrations relevant to therapy (1-500 μM). Based
on this dataset, it can be extrapolated that FSI assembles into nanoparticles at 37 °C,
while FA and FAF remain completely soluble under all concentrations. Very similar ELP
phase behavior was also observed after drug loading (Figure 2c).
34

After studying the thermal properties of FKBP-ELPs, the hydrodynamic radius (Rh) of all
the constructs were evaluated by performing temperature ramps using Dynamic Light
Scattering (DLS) (Figure 2d). As shown in the figure, particle radii were minimally
influenced by fusing FKBP to respective ELP backbones with SI and FSI assembling into
nanoparticles at or above 24-26 °C, which represents the critical micelle temperature
(CMT). In contrast, A192, FA and FAF remained soluble and retained sizes consistent
with free polymers. Furthermore, stability of FKBP-ELPs was evaluated by measuring the
particle size after Rapa loading for a period of 48 h at 37 °C (Figure 2e). The particles
remained stable, which demonstrates that drug binding to FKBP does not significantly
alter the protein folding state and also suggests that the formulation prevents precipitation
of the free drug.

Figure 2. Physicochemical characterization of FKBP-ELP carriers. (a) Copper-stained SDS-PAGE
confirmed the identity and purity of all the constructs with single band corresponding to greater than
90% purity (Table 1). Temperature-concentration phase diagrams of (b) ELPs with and without FKBP
and (c) Rapa loaded FKBP-ELPs measured by determining optical density at 350 nm. ELPs phase
separate (A192, FA, FAF) above the transition temperature or assemble nanoparticles (SI, FSI) above
critical micelle temperature (CMT) as shown by the indicated lines. (d) Hydrodynamic radii (R h) of ELPs
shows nanoparticle assembly only for SI and FSI whereas A192, FA and FAF remain soluble at 37 °C (n
= 3, mean ± SD). (e) All Rapa-loaded FKBP-ELPs maintain stable R h at 37 °C for 24 h (n = 3, mean ± SD).
35

2.4.2 FAF binds two Rapa per molecule with a similar affinity to FA and FSI.
To study the interaction between Rapa and FKBP-ELPs, Isothermal Titration Calorimetry
(ITC) was used to evaluate binding affinity and thermodynamics. ITC is a label-free
technique to evaluate a wide range of binding energetics including binding stoichiometry,
enthalpy (ΔH), entropy (ΔS), Gibbs free energy (ΔG) and affinity (Kd). Due to limitations
on Rapa’s aqueous solubility, reverse titrations were performed with Rapa in the
calorimeter cell, which was titrated against successive injections of FKBP-ELPs.
Saturable heat release was observed for all FKBP-ELPs, which suggests specific
interaction between Rapa and the FKBP domain (Figure 3). To eliminate the possibility
of non-specific interactions between Rapa and backbone ELPs, the experiment was
repeated with ELPs lacking the FKBP domain where only heat of dilution was observed
(Figure 3). ITC was performed for all FKBP-ELPs, and binding isotherms were obtained
Table 1: Physicochemical properties of ELP protein polymers with and without FKBP
Label

a
Amino acid
sequence

b
MW
[kDa]

c
Purity
[%]

d
R h at

e
Temperature-concentration
phase diagram

20 °C
[nm]
37 °C
[nm]
Slope, m
[°C Log(µM)]
Intercept, b
[°C]
SI

MG(VPGSG) 48(VPGIG) 48Y 39.774 93.6 5.3 ± 1.6 22.9 ± 0.5 4.7 ± 0.9 34.9 ± 1.3
FSI M-FKBP-G(VPGSG) 48(VPGIG) 48Y 51.576 94.5 6.1 ± 0.1 21.3 ± 0.6 3.5 ± 0.1 29.4 ± 0.2
A192 MG(VPGAG) 192Y 73.604 94.3 6.9 ± 0.2 6.6 ± 0.0 8.4 ± 0.6 73.9 ± 0.9
FA M-FKBP-G(VPGAG) 192Y 85.405 98.5 8.4 ± 0.1 7.8 ± 0.4 2.5 ± 6.2 61.7 ± 8.9
FAF M-FKBP-G(VPGAG) 192-FKBP 97.044 98.2 8.5 ± 0.6 7.9 ± 0.2 4.3 ± 0.7 63.6 ± 0.9
a
FKBP amino acid sequence:
GVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYAYG
ATGHPGIIPPHATLVFDVELLKLE(Standaert et al., 1990)
b
Expected MW based on amino acid sequence.
c
Purity was determined (Eq. 2) using SDS-PAGE gel and densitometry analysis of the copper chloride stained gel
using ImageJ.
d
Rh, hydrodynamic radius of 25 µM samples determined by Dynamic Light Scattering. Values represent mean ± SD
(n=3)
e
Phase diagrams for assembly (Figure 2b) were fit with Eq. 3. Values represent mean ± 95% CI.

36

as shown in Figure 4. The data was fitted to a ‘one set of sites’ binding model, which
enabled estimation of binding stoichiometry and thermodynamic parameters (Table 2).
As observed in Figure 4, the sharp inflection in ΔH on successive injections of FKBP-
ELPs occurred just before saturation when the ELP/Rapa ratio was ~ 1 for FSI and FA.
This confirms the stoichiometry of Rapa bound to FSI and FA is ~ 1, each matching the
number of FKBP domains. In contrast, saturation of FAF binding occurred at an
ELP/Rapa ratio of ~ 0.5. This data confirms that both FKBP domains on FAF are
functional; furthermore, FAF has twice the drug loading per molecule in comparison to
FSI and FA. Using a displacement assay, FKBP-Rapa interactions have been previously
reported to have a dissociation constant of 0.2 nM (Bierer et al., 1990). ITC of this dataset
Figure 3: Heat release during Rapa binding is observed only with FKBP-ELPs and not with backbone
ELPs. Raw binding isotherms generated using Isothermal Calorimetry by titrating Rapa against
increasing concentrations of (a) FSI, (b) FA and (c) FAF shows decreasing power required to maintain
zero temperature difference between calorimeter cell (containing Rapa) and reference cell
(containing water) on successive injections of respective FKBP-ELPs into the calorimeter cell. Each
power spike represents addition of respective FKBP-ELP into the calorimeter cell, which reaches
saturation at later time points. With control ELPs (d) only heat of dilution for SI and (e) un-saturable
heat of dilution for A192 was observed. Unlike for the FKBP-ELPs (FSI, FA, and FAF), the un-saturable
raw isotherms (SI, A192) suggests no distinct binding between Rapa and control ELPs. A
representative data set is shown from each group of n = 3.
37

revealed a slightly higher dissociation constant of ~ 6 nM for all the FKBP-ELPs (Table
2). The comparatively weaker Kd may be attributed to fusion of ELP to FKBP or the DMSO
used to dissolve Rapa in phosphate buffered saline (PBS), both of which could weaken
the interaction. Other parameters obtained on fitting the binding isotherms indicated a
thermodynamically favorable interaction. Binding enthalpy (ΔH) for FSI and FA were -39
kJ/mol and -58 kJ/mol respectively indicating exothermic reactions with heat released due
to non-covalent association between Rapa and respective FKBP-ELPs. The observed
enthalpies of binding are similar to a published dataset that predicts -83 kJ/mol for the
binding of purified bovine FKBP12 and Rapa at 37°C at pH 7.0 (Connelly and Thomson,
1992). A significant change in binding enthalpy of -104 kJ/mol was observed for FAF due
to the two-fold increase in drug binding per ELP. A positive -TΔS of ~ 10 kJ/mol for both
FSI and FA; and 54 kJ/mol was observed for FAF which revealed an entropic cost
associated with Rapa binding to FKBP-ELPs. This could be explained by transitioning of
Rapa from a free, unbound state in solution to a more ordered FKBP bound state.
However, previous studies have shown expulsion of bound water molecules from the

Figure 4: FAF has twice the drug loading capacity compared to FSI and FA. Isothermal titration
calorimetry was used to quantify the binding stoichiometry and thermodynamic parameters between
Rapa (8 µM) in 2.4% DMSO in PBS at 37 °C against increasing titrations of (a) FSI, (b) FA and (c) FAF.
An inflection in the ELP-to-Rapa ratio was ~ 1 for FSI and FA and ~ 0.5 for FAF, which is roughly
consistent with having 1 (FA, FSI) or 2 (FAF) FKBP domains per ELP. A representative data set is shown
from n = 3 per group.
38

hydrophobic cavity of bovine and human FKBP into bulk water on binding of rapalogues
as a favorable entropic contribution (Connelly and Thomson, 1992; Wilson et al., 1995).
An overall similar negative Gibbs free energy (ΔG), which sums enthalpy and entropy
contributions, suggests Rapa binding to FKBP-ELPs remains a thermodynamically
favorable interaction (Bissantz et al., 2010). Among all the FKBP-ELPs, FAF showed
twice the drug binding stoichiometry and comparatively significant change in binding
enthalpy and entropy, which may favor Rapa interactions over that with FSI and FA.

2.4.3 FA and FAF architectures extend stability and drug retention compared to
FSI nanoparticles.
After studying drug binding interactions, Rapa-loaded formulations were evaluated for
long-term drug retention and stability by performing dialysis under sink conditions in PBS
at 37 °C (Figure 5). To control for the loss in FA and FAF after long-duration dialysis
against a 20 kDa MWCO membrane, aliquots were assessed separately for both Rapa
and FKBP-ELP using calibrated RP-HPLC assays, and Rapa/ELP ratio was plotted
(Figure 5 a-c). Stability of each formulation was assessed using DLS, and the assay was
halted when the population consistent with the initial hydrodynamic radius dropped below
Table 2: Thermodynamic parameters of FKBP-ELP interaction with Rapa
Label Binding
stoichiometry,
FKBP-ELP / Rapa
Dissociation
constant,
Kd (nM)
Enthalpy of binding,
ΔH (kJ/mol)
-TΔS
(kJ/mol)
Gibbs free energy
of binding, ΔG
(kJ/mol)
FSI 1.33 ± 0.33 6.05 ± 0.91 -38.8 ± 2.1 10.0 ± 2.4 -48.8 ± 0.3
FA 1.12 ± 0.08 7.18 ± 1.42 -57.6 ± 2.2 9.2 ± 1.9 -48.4 ± 0.5
FAF

0.58 ± 0.04 4.87 ± 1.48 -103.8 ± 2.9 54.4 ± 3.2 -49.4 ± 0.3
All experiments were performed at 37
o
C. Binding isotherms were fitted to a ‘one set of sites’ binding model to
generate binding stoichiometry and thermodynamic parameters. Values are represented as mean ± SD (n = 3 per
group).
39

90% by mass (Figure 5 d-f). The FSI-Rapa formulation demonstrated an initial Rh of 26.6
± 1.5 nm, which remained consistent until at least 14 h after which Rh increased to ~ 239
± 137 nm. In contrast, FA-Rapa and FAF-Rapa formulations were stable throughout the
length of the assay with initial Rh of 6.4 ± 1.7 and 6.4 ± 1.6 nm respectively. Thus, FSI
was stable for about one day, FA was stable for about 2 weeks, and FAF was stable for
about one month. At 0 h post drug loading, FSI and FA, had ~ 0.9 molecules of Rapa
bound per ELP, whereas Berunda FAF had ~ 2.2 Rapa per ELP, which is consistent with
the binding stoichiometry observed by ITC (Figure 4). Surprisingly, for FAF this ratio
remained approximately unchanged up to one month. Together, these data verify that
FAF is functionally bi-headed, with two FKBP domains per ELP. Furthermore, both FA

Figure 5: The soluble architecture of FA and FAF enhance stability with extended drug retention
compared to FSI nanoparticle. Dialysis was performed under PBS sink conditions at 37 °C to test drug
retention and stability of FKBP-ELP formulations. (a) FSI-Rapa and (b) FA-Rapa formulations bound
Rapa in an ~ 1:1 ratio compared to (c) FAF-Rapa which bound drug in an ~ 2:1 ratio as quantified by
RP-HPLC using FKBP-ELP and Rapa peaks. Values are presented as mean ± SD (n = 3 per group). DLS
was performed at respective time points to study stability of Rapa loaded FKBP-ELP formulations. (d)
FSI-Rapa displayed a stable R h until 14 h after which its radius began to increase whereas (e) FA-Rapa
and (f) FAF-Rapa formulations were stable for 2-4 weeks demonstrating extended stability, strong drug
retention, and potential benefits to shelf-life. Values are presented as mean ± SD (n ≥ 3 per time point).
40

and FAF formulations have greater physical stability than observed for the FSI
formulation.

2.4.4 FAF-Rapa formulation demonstrates superior tumor growth suppression
following SC administration.
After performing the physicochemical characterization, drug binding and retention as well
as stability, we then proceeded to test Rapa efficacy in xenograft breast cancer mouse
model with and without the FKBP-ELP carriers. To determine the minimum effective dose
for SC administration, a pilot xenograft study (n = 3-4 mice per group) was first performed
by IV administration (Figure 6). A dose escalation regimen of FAF-Rapa (0.025 – 0.75
mg Rapa/kg body weight) with PBS and an intermediate dose of FSI-Rapa (0.25 mg/kg)
(Shi et al., 2013) was performed in MDA-MB-468 orthotopic breast cancer mouse model.
The FSI-Rapa group was included to compare architecture based difference in efficacy
between nanoparticle (FSI) and soluble (FAF) formulations at equivalent Rapa dose of
0.25 mg/kg.
Treatment groups responded differentially to the dose regimen. PBS treated mice showed
increasing tumor volumes, which varied between subjects (Figure 6a). Mice treated with
FSI-Rapa at 0.25 mg/kg (Figure 6b) and FAF-Rapa at 0.025 – 0.25 mg/kg (Figure 6c-e)
showed weak growth suppression while complete tumor suppression was only observed
with FAF-Rapa at 0.75 mg/kg (Figure 6f). Despite a trend, groups treated with FSI-Rapa
at 0.25 mg/kg and with FAF-Rapa at 0.025 – 0.25 mg/kg did not significantly differ from
the PBS group. Only the group treated with the high dose of FAF-Rapa at 0.75 mg/kg
showed statistical significance compared to PBS (Tukey’s post-hoc analysis, α = 0.05, p
41

= 0.002) (Figure 6g). With similar efficacy observed between FSI and FAF formulations
at 0.25 mg/kg, it suggests that there is no difference in IV efficacy between the
nanoparticle (FSI) vs soluble (FAF) architectures. With maximal tumor
suppression observed only with FAF at 0.75 mg/kg dose, Rapa formulations with and
without FKBP-ELP carriers (FSI, FA and FAF) were then compared at minimum effective
dose of 0.75 mg/kg with SC administration (Figure 7).

Figure 6: FAF-Rapa demonstrates dose-dependent tumor growth suppression when injected IV.
Athymic nude mice (n=3-4 per group) with orthotopic 10-50 mm
3
MDA-MB-468 tumors were treated
three times a week IV with (a) PBS, (b) FSI-Rapa at 0.25 mg/kg, (c) FAF-Rapa at 0.025 mg/kg, (d) FAF-
Rapa at 0.075 mg/kg, (e) FAF-Rapa at 0.25 mg/kg and (f) FAF-Rapa at 0.75 mg/kg. (g) Tumor burden
(Eq. 5) by day 62 (mean ± SD) was statistically significant for the comparison between PBS and FAF-
Rapa at 0.75 mg/kg (Tukey’s post-hoc analysis, α = 0.05, **p = 0.002). (h) No decrease in body weight
(mean ± SD) over time was observed in any group, suggesting that the formulations are tolerated.

42

The rationale behind exploring the SC route is to identify opportunities for absorption from
the site of injection into the systemic circulation. SC administration can be performed by
patients at home whereas IV administration requires clinical expertise. SC administration
is FDA-approved for monoclonal antibodies and other biotherapeutics including insulin
(McDonald et al., 2010). In addition, there is a strong precedent for SC delivery of ELP
fusions such as Glymera
TM
, which is a formulation having reached PhaseIIB clinical status
for Type II diabetes (Amiram et al., 2013; Pharmaceuticals, 2012). Bioavailability through
the SC route is governed by either direct diffusion into blood capillaries or through the
Figure 7. FAF-Rapa outperforms other carriers in suppressing tumors when injected SC. Athymic
nude mice (n=6-8 per group) with orthotopic 30-180 mm
3
MDA-MB-468 tumors were treated three
times a week SC with (a) PBS (b) Free Rapa (c) FAF-Rapa (d) FA-Rapa and (e) FSI-Rapa at 0.75 mg/kg
dose. (f) Tumor burden (Eq. 5) by day 50 (mean ± SD) was statistically significant for the comparisons
between PBS and Free Rapa, FAF-Rapa each (Tukey’s post-hoc analysis, α = 0.05, *p = 0.03,
○
p = 0.03
respectively). (g) Kaplan-Meier analysis shows Free Rapa and FAF-Rapa also had longer survival end
points than the PBS-treated control (Log-rank post-hoc analysis, α = 0.0125, p = 0.003 and 0.003
respectively). (h) There were no long-term trends in body weight (mean ± SD), except for the Free
Rapa group which recovered after a mild decrease in the first week of treatment.
43

interstitium into the lymphatic system, which depends on particle size and surface charge
(Richter et al., 2012). Based on the differences in hydrodynamic radii and drug loading,
the library of FKBP-ELPs (Table 1) was compared to determine the optimal carrier to
achieve tumor growth suppression following SC administration.
The comparative tumor regression study consisted of 5 groups: PBS, Free Rapa, FAF-
Rapa, FA-Rapa, and FSI-Rapa, all at the equivalent dose of 0.75 mg/kg (n = 6-8 mice/
group). The injections were dosed SC in the right flank above the hind leg. The group
treated with PBS exhibited a gradual increase in tumor volumes which remained variable
(Figure 7a). Groups treated with Free Rapa and FAF-Rapa showed strong tumor
suppression profiles (Figure 7 b, c) relative to groups treated with FA-Rapa and FSI-
Rapa (Figure 7 d, e). FA-Rapa and FSI-Rapa treatments showed no statistical
significance compared to PBS (Tukey’s post-hoc analysis, α = 0.05, p = 0.095 and 0.38
respectively). Only the groups treated with free Rapa and FAF-Rapa demonstrated
statistical significance compared to the PBS group (Tukey’s post-hoc analysis, α = 0.05,
p = 0.03 and 0.03 respectively). In addition to having lower tumor burdens, mice from the
free Rapa and FAF-Rapa had higher survival rates than FA-Rapa and FSI-Rapa groups
(Figure 7g). Kaplan-Meier analysis was employed to distinguish the survival rates with
four-fold increase in tumor volume considered as the endpoint. Post-hoc log-rank tests
comparing PBS with each of the four treatment groups revealed significant differences
with Free Rapa and FAF-Rapa (Log-rank post-hoc analysis, α = 0.0125, p = 0.003 and
0.003 respectively). There was no decrease in body weight across all treatment groups,
except for Free Rapa in the first week of treatment (Figure 7h). While it was not possible
to distinguish statistical differences in tumor burden or survival directly between FAF and
44

the FA and FSI formulations, the FAF-Rapa formulation maintained the strongest effect
on tumor growth with respect to PBS (Figure 7f). To further elucidate the relationship
between SC absorption of FKBP-ELPs and tumor efficacy, the influence of carrier
architecture on mTORC1-signaling, injection site toxicity, and bio-distribution was
evaluated in the same tumor xenograft model.

2.4.5 SC treatment with Rapa loaded FKBP-ELPs inhibits a downstream target of
the AKT-mTORC1 axis in MDA-MB-468 solid tumors.
Due to the unexpectedly high stability (Figure 5) and superior SC efficacy of the FAF
Berunda architecture (Figure 7), further pharmacological evidence was collected to
confirm whether the drug can reach the tumor and act on a known molecular target of
mTORC1 pathway. Stimulation of cell surface receptor tyrosine kinases by growth factors
is known to activate the PI3K-AKT-mTORC1 pathway in TNBCs which activates and
phosphorylates two major mTORC1 downstream targets: p70 S6 Kinase 1 (p70 S6K1)
and 4E-binding protein 1 (4E-BP1) (Massihnia et al., 2016). Phosphorylation of p70 S6K1
further activates and phosphorylates downstream ribosomal S6 protein (rpS6), which
plays a role in mRNA translation of proteins including elongation factors and ribosomal
proteins. Phosphorylation of the other mTORC1 target 4E-BP1 facilitates cap dependent
protein translation required for G1-to-S phase transition of cell cycle (Faivre et al., 2006).
Treating MDA-MB-468 cells with Rapa in vitro has been previously shown to mildly inhibit
p-p70 S6K1 (Thr 389) and p-4E-BP1 (Ser 65) while strongly suppressing p-rpS6 (Ser
235/236) (Liu et al., 2011; Mondesire et al., 2004; Noh et al., 2004). Based on this
pharmacology, at the conclusion of the SC study, tumor lysates were probed for p-p70
45

S6K1, p-4E-BP1 and p-rpS6 (Figure 8). At 24 hours after the last SC dose, there was no
significant decrease in the tumor level of p-p70 S6K1 and p-4E-BP1 (Figure 8a, 9). In
contrast, there was a significant decrease in p-rpS6 levels (Figure 8b) between
PBS and Free Rapa, FAF-Rapa, FA-Rapa and FSI-Rapa each (Tukey’s post-hoc
analysis, α = 0.05, p = 0.009, 0.035, 0.005 and 0.003 respectively). Similar to the results
observed in the IV (Figure 6g) and SC (Figure 7f) in vivo studies, there was no statistical
difference between the formulations, which suggests all the Rapa loaded FKBP-ELP
carriers equally suppress p-rpS6 levels.
The lack of a detected decrease in p-p70 S6K1 and p-4E-BP1 could be either due to
treatment with a transient tumor exposure in vivo following a low dose (0.75 mg/kg) as
compared to the constant exposure achieved for in vitro incubation. It is plausible that p-
p70 S6K1 and p-4E-BP1 levels recover during the 24 hours between the last dose and
tumor lysis. Despite this, the significant decrease in p-rpS6 level signifies that SC
Figure 8: SC treatment with Rapa inhibits downstream target of mTORC1. (a) Tumor lysates probed
for downstream targets of mTORC1 showed no significant inhibition in p-p70-S6K1 and p-4E-BP1
levels. However, there was a significant decrease in p-rpS6 levels in all treatment groups compared to
PBS. A representative western blot is shown from n = 4 per group. (b) 1-way ANOVA on the normalized
intensity levels (Eq. 6) of p-rpS6 (n = 4, mean ± SD) showed a statistically significant decrease between
PBS and Free Rapa, FAF-Rapa, FA-Rapa and FSI-Rapa each (Tukey post-hoc analysis, α = 0.05, **p =
0.009, *p = 0.035, °°p = 0.005,
●●
p = 0.003 respectively).

46

treatment of Rapa with or without FKBP-ELP can travel from a site of injection,
presumably through systemic circulation, to exert its effect on an orthotopic solid tumor.
Since all the treatments worked equally in dephosphorylating rpS6, we then proceeded
to study the relative toxicity and bio-distribution as a function of FKBP-ELP architecture.

2.4.6 Free Rapa treatment is toxic at the site of SC injection.
Even though SC administration of free Rapa without any carrier was efficacious in
suppressing tumor growth and phosphorylation of rpS6, treatments were not equally
tolerated at their injection site (Figure 10). Free Rapa was administered the first week in
100% DMSO, which was not tolerated and produced a small drop in BW. To continue the
treatment, starting in the second week, the Free Rapa control was instead solubilized
using Cremophor-EL as a co-solvent (Chao et al., 2005), which proved to be tolerated by
the mice resulting in a gradual gain of lost BW (Figure 7h). Free Rapa was formulated in
DMSO: EtOH: Cremophor-EL: PBS in 1:1:2:6 % v/v ratio. While the local bruising of Free

Figure 9: SC treatment with Rapa at 0.75 mg/kg does not inhibit p-p70 S6K1 and p-4E-BP1 levels. 1-
way ANOVA on the normalized intensity levels of (a) p-p70 S6K1 and (b) p-4E-BP1 (n = 4, mean ± SD)
showed no significant decrease between PBS and any treatment group.

47

Rapa was less prominent, local edema persisted at each site of injection for one week
after every SC injection. In contrast to Free Rapa, all FKBP-ELP formulations showed no
external visual signs of redness or blistering throughout the duration of the study (Figure
10b). At the end of the SC study, all mice were euthanized and organs were evaluated
for histopathology by Hematoxylin and Eosin (H & E) staining. Despite 50 days of
treatment, there was no pathophysiology seen in any of the major organs (Figure 11) in
all the treatment groups, with the exception of the skin (Figure 10a). The skin section
obtained after SC administration of Free Rapa group displayed epidermis with focal
hyperkeratosis, parakeratosis, and intraepidermal neutrophilic infiltrate with cellular
debris. The underlying hair follicles were necrotic and the adipose tissue exhibited
hemorrhage and neovascularization. In contrast, the epidermis in all the other treatment
groups was intact with keratinizing squamous epithelium. The dermis was observed with
connective tissue and sebaceous glands with numerous intact hair follicles. No evidence
Figure 10: FKBP-ELP carrier protects against tissue necrosis during SC administration. (a) After the
conclusion of 50 days of SC treatment three times weekly at 0.75 mg/kg Rapa dose, skin sections from
the most recent site of injection were excised, paraffin embedded, and evaluated for H & E
histopathology. Free Rapa treatment was toxic at site of injection compared to Rapa loaded FKBP-
ELPs. Panels i, ii, iii, iv, and v are from a representative mouse treated with PBS, free Rapa, FAF-Rapa,
FA-Rapa and FSI-Rapa respectively (n = 6-8). (b) The relative differences between the SC toxicity of
these formulations at the site of injection was also externally evident on day 30 of this study.
48

of inflammation or necrosis was identified with any of the Rapa loaded FKBP-ELP
formulations. Though effective in solubilizing free Rapa and inhibiting tumor growth, the
Cremophor-EL formulation produced severe toxicity at the site of injection. In contrast, all
other sections from mice treated with Rapa loaded FKBP-ELPs were devoid of any local
or systemic toxicity. This strengthens the argument that while free Rapa remains effective
as a cytostatic agent, it cannot be administered SC without inducing toxicity; furthermore,
suitable drug carriers must both improve its solubility and retain its relative cytostatic
bioavailability.

Figure 11: Histopathology of mouse organs evaluated post SC treatment fails to show evidence of
systemic toxicity across any treatment groups. After the end of study, mice were perfused under
anesthesia, euthanized and organs were evaluated for histopathology by H & E staining. No abnormal
pathophysiology was reported in any of the organs evaluated across all the treatment groups. Organs
from one representative mouse are shown from each group.
49

2.4.7 Soluble FA and FAF tumor accumulation is greater than FSI nanoparticles
after SC administration
To explore the effect of ELP architecture on the SC bio-distribution of FKBP-ELPs, their
uptake was tracked in xenograft mice by performing live optical imaging using a near
infrared dye, Cyanine5.5 (Cy5.5). FA, FAF and FSI were covalently labelled with Cy5.5
using N-hydroxysuccinimide chemistry at a ratio of ~0.15 Cy5.5/protein (Eq. 9) and an
equivalent dose of 0.5 mg Cy5.5 / kg body weight was administered SC in the flank above
the right hind leg (n = 4 mice/group). The Rh of Cy5.5 labelled FKBP-ELPs was confirmed
as stable prior to in vivo administration (Figure 12). In vivo fluorescence was monitored
using whole body optical imaging for 48 h from both dorsal and ventral perspectives
(Figure 13, 14). For all three formulations, the injection site remained highly fluorescent
during the entire duration of the study from the dorsal view; which could be due to
entrapment of carriers in the lymph nodes. However, FA and FAF moved away from the
injection site more rapidly than did FSI nanoparticles (Figure 14). From the ventral
perspective, fluorescence accumulation at both the tumor and site of injection were
Figure 12: Cy5.5 labeled FKBP-ELPs retained a stable hydrodynamic radius at 37 °C. FKBP-ELPs post
Cy5.5 labeling were characterized by dynamic light scattering before injecting in vivo. The R h of (a)
Cy5.5-FSI, (b) Cy5.5-FA and (c) Cy5.5-FAF remained stable for 24 h; furthermore, the particle size was
consistent with that observed prior to Cy5.5 labeling (Figure 2d). Values are represented as mean ±
SD (n = 3).
50

qualitatively visible (Figure 13a). For quantitative comparisons between organs too deep
to view using this optical imaging modality, mice were euthanized at 48 h, organs were
isolated, and scanned immediately for fluorescence. After correcting for the tissue auto
fluorescence observed in control mice without Cy5.5 administration, FA and FAF showed
high fluorescence in the kidney, liver, and tumor compared to FSI (Figure 13 b, c). Tukey
post-hoc comparisons were performed to test significance between the individual
treatment groups (Figure 13c) within each tissue. The kidney accumulation of signal was
significantly greater for FA and FAF than for FSI (α = 0.05, p = 0.0004, 0.005 respectively).
Similarly, the liver accumulation was significantly greater for FA and FAF than for FSI (α
Figure 13. FA and FAF show high accumulation in tumor and clearance organs compared to FSI. (a)
MDA-MB-468 tumor implanted nude mice administered SC with Cy5.5 labeled FKBP-ELPs were imaged
using IVIS Spectrum. FA and FAF show high tumor fluorescence at 24 h and 48 h compared to FSI.
Tumor accumulation and site of injection are shown as indicated by arrows. A representative mouse
scan in ventral position at 0, 4, 24 and 48 h is shown from each group of n = 4 mice. (b) Post 48 h whole
body scan, mice were immediately euthanized and organs were scanned for fluorescence. A
representative mouse is shown from each group of n = 4. (c) The fluorescence intensity in Avg. radiant
efficiency (n = 4, mean ± SD) was quantified by drawing ROIs on all the organs. Tukey’s multiple post
hoc analysis reveals statistical significance between FA and FSI; FAF and FSI in kidneys, liver and tumor
respectively (α = 0.05, ***p = 0.0004, **p = 0.005, °°p = 0.001, °°°p = 0.0004,
●●●
p = 0.0004,
●●
p =
0.004).

51

= 0.05, p= 0.001, 0.0004 respectively). Matching the qualitative observations (Figure
13a), the tumor accumulation for FA and FAF were also significantly greater than for FSI
(α = 0.05, p = 0.0004, 0.004 respectively). Taken together, these observations suggest
that soluble FA and FAF yield greater accumulation in the tumor compared to the FSI
nanoparticles, which is likely a combination of their more rapid absorption from the SC
site of administration, differences in tumor permeability, and also differences in interaction
with clearance organs. FA and FAF also exhibited significantly higher tumor localization

Figure 14: Live body scans of SC injected Cy5.5 labeled FKBP-ELPs taken dorsally. FA, FAF and FSI
show increased areas of fluorescence over time at site of SC injection. A single injection at the SC site
at 0 h is shown as indicated by arrows. This high level of signal in the skin hindered tracking the bio-
distribution of material in clearance organs, kidneys and liver for live mice; however, FA and FAF show
greater whole body distribution compared to FSI. One representative mouse is shown from each group
of n = 4.

52

in live mice at 24 h and 48 h compared to FSI nanoparticles, which showed minimal tumor
localization (Figure 13 a).
To further understand the poor FSI bio-distribution observed with the SC administration,
Cy5.5 modified FSI was injected intravenously and compared to its SC counterpart
(Figure 15). FSI injected intravenously had significantly higher liver, tumor and spleen
accumulation than the SC counterpart (Tukey’s post hoc analysis, α = 0.05, p = 0.01,
0.008 and 0.01 respectively) which suggests longer systemic circulation and enhanced
bio-distribution likely due to higher bio-availability observed with intravenous

Figure 15: Cy5.5-FSI injected IV shows greater whole body distribution and tumor accumulation
compared to Cy5.5-FSI injected SC. (a) MDA-MB-468 tumor implanted nude mice administered IV and
SC with Cy5.5 labeled FSI were imaged using IVIS spectrum. FSI (IV) show high body-distribution and
tumor accumulation compared to FSI (SC). Tumor accumulation and SC site of injection are shown as
indicated by arrows. A representative mouse scan in ventral position at 0, 4, 24 and 48 h is shown from
both the groups with n = 4 mice. (b) Post 48 h whole body scan, mice were immediately euthanized
and organs were scanned for fluorescence. A representative mouse is shown from each group of n =
4. (c) The fluorescence intensity in Avg. radiant efficiency (n = 4, mean ± SD) was quantified by drawing
ROIs on all the organs. Paired t-test analysis revealed statistical significance between FSI (IV) and FSI
(SC) in liver, tumor and spleen respectively (α = 0.05, **p = 0.001, °°p = 0.008, *p = 0.01).
53

administrations. There was no significant kidney accumulation with the IV injection
suggesting nanoparticle clearance predominantly by the liver and spleen.
Absorption of biologics from SC injection into systemic circulation occurs either by direct
uptake into blood capillaries or through the interstitium into lymphatic vessels (Richter et
al., 2012). Small peptides and proteins with particle sizes < 10 nm and MW ≤ 16 kDa are
more easily taken up by diffusion into blood capillaries whereas high molecular weight
protein therapeutics with particle sizes in the range of 10-100 nm are taken up by
lymphatic vessels (Supersaxo et al., 1990; Swartz, 2001). FA/FAF and FSI are high
molecular weight proteins with particle radii ~ 7 nm and 25 nm respectively (Table 1,
Figure 2). Even though all the three FKBP-ELPs exhibit favorable characteristics for
lymphatic uptake, FA and FAF owing to their smaller particle size exhibit more rapid
absorption and thus greater tumor accumulation compared to FSI nanoparticles (Figure
13a). Curiously, these differences in tumor accumulation were not differentiated between
treatment groups in suppression of tumor burden and p-rpS6 levels (Figure 7f, Figure
8b). The lack of strong tumor accumulation by FSI with SC administration may suggest
its delivery of Rapa by some other mechanism, such as through biodegradation inside
macrophages along the lymph absorption pathway (McLennan et al., 2005; Porter and
Charman, 2000). While there is not enough evidence to point to a different mechanism
between FA/FAF and FSI efficacy, the observations of higher tumor accumulation for
FA/FAF are consistent with our previous report that soluble A192 ELP alone exhibits
better tumor penetration and favorable pharmacokinetics compared to an ELP
nanoparticle (Janib et al., 2013). When Cy5.5 labeled FSI injected IV was compared to
its SC counterpart, there was enhanced accumulation in liver and tumor compared to FSI
54

injected SC which validates the poor bio-distribution of FSI due to its biodegradation along
the SC lymph absorption pathway. Furthermore, despite the enhanced bio-distribution of
FSI observed with ~ 100% bioavailable intravenous route (Figure 15), the tumor and liver
fluorescence was similar to that observed with FA and FAF injected SC (Figure 13 b, c).
This observation further highlights the superior bio-distribution of FA/FAF through SC
route which was only matched by FSI when injected intravenously.
Taken together, these findings suggest that ELPs with soluble morphology (FA and FAF)
behave similarly when administered SC and demonstrates superior bio-distribution to
ELP with nanoparticle morphology (FSI). Increase in the number of ELP repeats beyond
192 pentamers may further improve the bio-distribution of soluble FKBP-ELP formulations
due to favorable increase in MW. In contrast, despite the poor SC bio-distribution of FSI,
it retains its ability to suppress phosphorylation of tumor rpS6. All three carriers facilitated
toxicity free administration from an SC site. However, based on the fact that FAF efficacy
was highest among the carriers, in addition to its long-duration stability and drug retention,
the sum of the data suggests that the Berunda architecture is optimal for SC
administration of Rapa. Future studies are required to clarify the differences in
bioavailability, clearance, blood half-lives, tumor permeability, FKBP biodegradation and
to understand the lymphatic absorption mechanism from the SC site of injection.
Rapa and its analogs are potent small molecule inhibitors of the AKT-mTORC1 pathway,
which renders them excellent cytostatic drugs (Benjamin et al., 2011; Faivre et al., 2006).
Currently, there are three FDA approved rapalogues - Sirolimus, Temsirolimus and
Everolimus. Sirolimus is formulated only for oral administration via liquid and solid
formulations; however, its poor solubility yields low bioavailability with severe side effects
55

(Marti and Frey, 2005; Pham et al., 2004; Stenton et al., 2005). Temsirolimus, an ester
prodrug of sirolimus, is formulated as an ethanolic, non-aqueous IV infusion to overcome
its poor solubility, which promotes dermatological and hypersensitivity reactions (Danesi
et al., 2013; Gomez-Fernandez et al., 2012). Formulated as a solid tablet, Everolimus
also has a low bioavailability and commonly causes dose-limiting side effects in the clinic
(Danesi et al., 2013; Gabardi and Baroletti, 2010). Not unlike chemotherapeutics such as
doxorubicin and paclitaxel, the rapalogues are potent, effective drugs that can be further
enhanced through better delivery strategies. To explore proteins as potential carriers, we
previously reported that a recombinant fusion using FSI to carry Rapa suppresses
xenograft tumor growth when administered IV, while reducing evidence of systemic
toxicity. While IV administration overcomes low oral bioavailability, the rapalogues would
clearly benefit from a parenteral route of self-administration such as SC. These findings
further advances our approach by exploring a library of protein-polymer architectures to
favor systemic drug absorption, tumor localization, and efficacy with SC administration.

2.5 Conclusion
Three different architectures for FKBP-ELP fusions were compared for drug loading,
binding thermodynamics, stability, efficacy and bio-distribution in an orthotopic model of
breast cancer. The soluble two-headed Berunda polypeptide (FAF) had significant
advantages over a single-headed (FA) or a nanoparticle formulation (FSI). Only the
Berunda polypeptide improved drug-loading efficiency, retention, and formulation stability
as shown by ITC and dialysis. When compared with FSI by IV administration at the same
drug dose of 0.25 mg/kg, there was a similar level of efficacy observed for FSI-Rapa and
56

FAF-Rapa. When all three architectures were compared via SC administration at
equivalent dose of 0.75 mg/kg, only Free Rapa and FAF-Rapa showed statistical
significance compared to PBS. Despite these statistical differences, all formulations were
able to deliver some amount of Rapa to the tumor, as verified by probing downstream
targets of mTORC1. When toxicity was evaluated, free Rapa treatment although
efficacious produced significant necrosis at the site of injection compared to Rapa loaded
FKBP-ELP formulations, which is consistent with other literature demonstrating that free
Rapa administration is often associated with dose-limiting toxicity. Molecular imaging
studies by SC administration confirmed that tumor accumulation of FA and FAF is
significantly higher than for the nanoparticle FSI. When bio-distribution of FSI was
compared by IV and SC injections, FSI injected IV had similar tumor accumulation to that
observed for FA and FAF injected SC. These comparisons prefer soluble ELP
architecture (FA, FAF) over nanoparticle (FSI) for enhanced SC bio-distribution. Overall,
all the carriers were able to deliver Rapa to orthotopic tumors either by direct
accumulation (FA, FAF) or through systemic bio-degradation (FSI) but the Berunda FAF
formulation provides the best combination of increased drug loading, favorable drug
binding interactions, enhanced in-vitro formulation shelf-stability in addition to tumor
accumulation and tumor growth suppression. This strategy of fusing the FKBP domain to
protein-polymers, such as an ELP, effectively opens up a range of interesting delivery
options for rapalogues and other potent drugs.

57

2.6 Acknowledgements
This work was made possible by University of Southern California (USC), the National
Institute of Health R01GM114839 and R01EY026635 to JAM, the USC Whittier
Foundation, the USC Ming Hsieh Institute, P30 DK048522 to Liver Histology Core of USC
Research Center for Liver Diseases, the USC Molecular Imaging Center, USC Nano
Biophysics Core Facility, Translational Research Laboratory at USC School of Pharmacy
and Proteomics and Metabolomics Facility, Colorado State University.

58

Chapter 3
Switchable Elastin-Like Polypeptides that respond to chemical inducers of
dimerization

3.1 Abstract
Elastin-like polypeptides (ELPs) are protein polymers that reversibly phase separate in
response to increased temperature, pressure, concentration, ionic strength, and
molecular weight. If it were possible to engineer their phase separation to respond to
specific molecular substrates, ELP fusion proteins might be engineered as biosensors,
smart biomaterials, diagnostic imaging agents, and targeted therapies. What has been
lacking is a strategy to design ELPs to respond to specific substrates. To address this
deficiency, we report that ELP fusion proteins phase separate in response to chemical
inducers of dimerization (CID). The rationale is that ELP phase separation depends on
molecular weight, concentration, and local hydrophobicity; therefore, processes that
affect these properties, including non-covalent dimerization, can be tuned to produce
isothermal phase separation. To test this hypothesis, constructs were evaluated
consisting of an immunophilin: human FK-506 binding protein 12 (FKBP) attached to an
ELP. Under stoichiometric binding of a CID, the fusion protein homodimerizes and
triggers phase separation. This dimerization is reversible upon saturation with excess CID
or competitive binding of a small lipophilic macrolide to FKBP. By modulating the ELP
molecular weight, phase separation was tuned for isothermal response to CID at
physiological ionic strength and temperature (37°C). To interpret the relationship between
transition temperature and equilibrium binding constants, an empirical mathematical
59

model was employed. To the best of our knowledge, this report is the first demonstration
of reversible ELP switching in response to controlled dimerization. Due to its simplicity,
this strategy may be useful to design ELP fusion proteins that respond to specific dimeric
biological entities.

3.2 Introduction
Protein switching is a critical triggering event in many biological signaling processes.
However, using such events to trigger or modulate behavior of polymers remains
challenging due to the complexity involved in the size, structure and nature of the polymer
and ligand-protein pair. Herein, we report a fusion construct consisting of genetically
engineered protein polymer linked to a fusion protein that homodimerizes upon binding
of a bifunctional ligand known as a chemical inducer of dimerization (CID). CID’s induce
non covalent association between two hetero- or homologous proteins (Austin et al.,
1994; Pastuszka and Mackay, 2010). The protein polymer belongs to a class of elastin-
like polypeptides (ELPs) that respond to environmental properties including temperature,
ionic strength, polymer concentration and pH(Mackay et al., 2010; Meyer and Chilkoti,
2004). ELPs phase separate above an inverse phase transition temperature, Tt(Urry,
1988, 1992), which has properties similar to that displayed by polymers with lower critical
solution temperatures. We demonstrate these fusion polypeptides reversibly phase
separate when triggered by binding of a bifunctional ligand - B/B Homodimerizer (CID).
This phase separation is specifically reversible upon competition with a lipophilic
immunosuppressive macrolide - Rapamycin (Figure 16).

60

Related studies have explored phase separation of protein-polymer fusions to control
binding of ligand to the appended protein(Ding et al., 2001; Shimoboji et al., 2002a;
Shimoboji et al., 2003; Shimoboji et al., 2002b; Stayton et al., 1995)

as well as the reverse
effect, that is, modulation of phase separation by allosteric ligand binding (Kim and
Chilkoti, 2008); however, none of these approaches have identified dimerization as a
mechanism to control phase separation. As such, it remains challenging to adopt previous
findings to engineer fusion proteins that respond to new targets. In contrast, the formation
of dimers is a simple approach to control ELP Tt, which has many potential applications
due to the wide prevalence of multimeric target proteins, including antibodies,
hemoglobin, tyrosine kinase receptors and cytokines, for instance, IL-5 and IL-10 (Kusano
et al., 2012; Zdanov et al., 1995). Motivating this study, it remains to be seen if ELP fusion
proteins that target dimeric species can be developed into smart polymers that switch
from soluble (off) to insoluble (on) in response to their specific target.
Figure 16: Reversible switching of FKBP-ELP fusion proteins by controlled dimerization. (a) Addition
of a CID induces assembly of the fusion proteins, which can be reversed by competition with a high
affinity substrate, Rapamycin. The dimeric fusion protein has a lower T t; therefore, under isothermal
conditions they phase separate in response to CID substrates. (b) Chemical structure of CID. (c)
Chemical structure of Rapamycin.
61

To explore the potential applications of dimerization to design substrate-specific ELP-
mediated phase separation, we engineered a fusion construct consisting of an
immunophilin: FKBP attached to an ELP. ELPs are a class of protein polymers biologically
inspired from human tropoelastin(Urry et al., 1976) which are composed of the repetitive
pentameric amino acids sequence (Val-Pro-Gly-Xaa-Gly)l where Xaa and l control the
ELP phase behavior. We selected ELPs as the environmentally responsive polymer for
multiple reasons, including that they are amenable to genetic engineering

using recursive
directional ligation(McDaniel et al., 2010). This enables biosynthesis of fusion constructs
with precise control over chain length, protein position and the arrangement of fusion
domains that might be challenging to prepare from synthetic polymers with LCST
behavior, such as poly(N-isopropylacrylamide)(Chen et al., 1990) and poly(N-
vinylcaprolactam)(Srivastava and Kumar, 2010). Also, the ELP Tt can be modified by
varying its guest residue(Urry et al., 1992) and chain length(Meyer and Chilkoti, 2004)
which makes their sensitivity to the environment highly tunable(Pastuszka et al., 2012).
Lastly, ELP tagged proteins can be purified from cellular expression systems using their
thermal responsiveness(Meyer and Chilkoti, 1999).
Given many options of homodimeric proteins to choose from, we selected FKBP because
of its size and amphiphilic structural topology(Main et al., 1999). FKBP is a cytosolic
receptor

for immunosuppressive drugs, like FK-506 and Rapamycin, and plays a
significant role in inhibiting T cell lymphokine gene activation(Bierer et al., 1990; Sharma
et al., 1994). FKBP homodimerization has been well characterized and exploited in areas
of transcription and signal transduction pathways(Amara et al., 1997; Spencer et al.,
1993). However, in this study, we harness FKBP homodimerization to modulate polymer
62

solubility in response to a CID switch. We hypothesized that at a fixed temperature, FKBP
homodimerization by CID would trigger ELP phase separation due to an increase in local
ELP chain length and decrease in solvent-exposed hydrophobic area of FKBP-ELP
dimer. FKBP is a soluble protein of ~ 12 kDa(Aghdasi et al., 2001) in size and holds a
hydrophobic ligand binding pocket(Main et al., 1999) both of which may facilitate ELP-
mediated phase separation. Previous studies on FKBP homodimerization in response to
CID’s such as AP1510 and FK1012A have been reported(Amara et al., 1997; Schultz and
Clardy, 1998). Thus, FKBP can be used with a small library of CID’s with various affinities,
structures, and molecular weights. FKBP also has a strong affinity for Rapamycin (Kd =
0.2 nM)(Bierer et al., 1990), which can specifically compete FKBP back to its monomeric
state. CID applications have been reported in a range of cellular events inducing
glycosylation, Wnt signaling, and apoptosis(Czlapinski et al., 2008; Shahi et al., 2012;
Souza et al., 2010) but never, as per the best of our knowledge, have been used to trigger
the phase separation of an ELP protein polymer.

3.3 Materials and Methods
3.3.1 FKBP-ELP fusion gene design and synthesis
FKBP-ELP gene assembly was done in a two-step cloning process. pIDTsmart vector
with the FKBP oligonucleotide sequence (the amino acid sequence of human FKBP
previously been published)(Standaert et al., 1990) was ordered from Integrated DNA
technologies (IDT) with three restriction cut sites: NdeI, BserI and BamHI. The FKBP gene
was flanked by restriction sites for NdeI and BserI with NdeI and BamHI cut sites at the
5’ and 3’ ends of the oligonucleotide respectively. The FKBP gene was cleaved from
63

pIDTsmart vector using NdeI and BamHI cut sites and gel purified (GE Healthcare). The
FKBP gene was then inserted into the pET25b (+) vector (Novagen) digested with same
set of NdeI and BamHI enzymes. For the second step, FKBP gene was inserted into
pET25b (+) vector containing the ELP gene using double digestion with BserI and BssHII
cut sites.(Sun et al., 2011a) The in-frame amino acid sequence of the fusion construct
with FKBP attached to N terminus of ELP was confirmed by DNA sequencing.

3.3.2 FKBP-ELP protein expression and purification:
E. coli BLR cells were transfected with pET25b (+) vector having the FKBP-ELP gene.
Cells were inoculated onto ampicillin plates and incubated for period of 15-17 h at 37⁰C
for optimum growth of bacterial colonies. A liter of bacterial culture was obtained by
overnight inoculation with bacterial cells from 50 ml terrific broth starter media
supplemented with 100 µg/mL ampicillin. The bacterial culture was centrifuged at 4000
rpm at room temperature, and the pellet obtained was re-suspended in cold PBS. The
suspension was sonicated for cell lysis with a 10 sec on, 20 sec off pulse interval for a
period of 3 min and the lysed product was centrifuged at 12,000 rpm at 4⁰C to discard
any insoluble cellular debris. Polyethylene imine (0.5 %) was added to the supernatant
for co-precipitation of DNA, incubated on ice for 15-20 min with occasional stirring and
centrifuged again at 12,000 rpm at 4⁰C to remove any remnant insoluble cellular debris.
The supernatant, which contains the fusion protein, was purified by Inverse Transition
Cycling (ITC)(Hassouneh et al., 2010). The fusion protein obtained was checked for its
purity using SDS-PAGE (Figure 17a).

64

3.3.3 FKBP-ELP characterization:
The fusion construct obtained after ITC was calculated for its concentration using Beer
Lambert’s law at absorbance of 280 nm on a Nanodrop UV-Vis spectrophotometer with
an estimated extinction coefficient of 11,585 M
-1
cm
-1
using phosphate buffer saline (PBS)
as the diluting solvent. Concentration ranges of 10-20 μg/μl were used for determining
the molecular weight by running samples on 4-20% gradient Tris-Glycine-SDS PAGE gel
under reducing conditions. Samples were stained with SDS loading buffer, denatured at
95⁰C for 5 mins and loaded onto SDS gel. Gels were stained using copper chloride
solution (10% w/v) and imaged using a VersaDoc Gel Imager (Figure 17a). The precise
molecular weight of all constructs was confirmed by using MALDI-TOF (Table 3).

3.3.4 FKBP-ELP kinetics and transition temperature determination:
The turbidity profiles of the samples were obtained using UV-Vis spectrophotometer.
FKBP-ELP solutions with different B/B Homodimerizer (CID - Clontech, CA)
concentrations were heated in Beckman Coulter Tm microcells (Brea, CA). The
temperature was increased at rate of 1⁰C/min with readings taken every 0.3⁰C
increments. Optical density at 350 nm was analyzed using the first derivative method and
the maximum first derivative was defined as the phase transition temperature (Figure 19
a, b, c). FKBP-ELP kinetic studies were performed on UV-Vis spectrophotometer by
measuring OD at 350 nm as a function of time at a constant temperature by successive
addition of stoichiometric amounts of CID and Rapamycin at predetermined fixed intervals
(Figure 20 a, b).

65

3.3.5 MALDI-TOF:
The precise molecular weight of the fusion proteins was determined by MALDI-TOF
(Table 3). Samples with 500μM concentration were prepared in a fresh saturated matrix
solution of sinapic acid (50 mg in 7:3 ratio of acetonitrile to distilled water). An external
control of albumin and apomyoglobin mixed with 1:1 ratio of matrix was prepared for
calibration. All samples were loaded onto MALDI plate wells for drying at room
temperature followed by determining its molecular weight by using weight - time of flight
(TOF) principle on a mass spectrometer (Kratos Analytical).

3.3.6 Bio-layer Interferometry:
The affinity of the CID towards FKBP-ELP was determined on a Blitz instrument
(ForteBio, CA). To a 100 µM FKBP-ELP solution in PBS, 100 µM NHS-PEG4-Biotin
(Thermo Scientific) dissolved in distilled water was added. The mixture was incubated for
45 min at room temperature. Unreacted biotin was separated using Zeba Spin Desalting
columns (7K MWCO, Thermo Scientific). The concentration of biotinylated FKBP-ELP
was determined at absorbance of 280 nm using extinction coefficient of 11,585 M
-1
cm
-1
.
Streptavidin biosensors were hydrated in PBS for at least 10 min before start of each run.
A single run was divided into five distinct steps as follows: i) Baseline – where the
streptavidin biosensor tip was immersed in PBS for 30 sec to obtain a zero baseline. ii)
Loading – where 1 µM biotinylated FKBP-ELP was immobilized onto streptavidin-coated
biosensor tip. This step was carried out for 180 sec, until the binding reached a plateau
indicating maximum binding of biotinylated FKBP-ELP to streptavidin-coated biosensor
tips. iii) Baseline – where the biosensor tip was again immersed in PBS for 30 sec to
66

remove any unreacted biotinylated FKBP-ELP. iv) Association – where biotinylated
FKBP-ELP biosensor tip was immersed in CID solution for a period of 240 sec. The data
from this step was used to estimate differences in interference caused by binding of CID
to biotinylated FKBP-ELP. v) Dissociation – where the FKBP-ELP-CID complex was
immersed in PBS for 160 sec to dissociate the CID. Subsequent runs were performed
with 0.05, 0.2, 1 and 2 µM CID solutions in PBS. Plain PBS was run as blank and
subtracted from all sample readings. A new biosensor tip was used for every run. Data
were analyzed using ForteBio Data Analysis package (Figure 24).

3.4 Results and Discussion
3.4.1 Purification and phase behavior of FKBP-ELP fusion proteins:
Two ELP constructs with Xaa = Val and l = 48 and 72 (V48, V72) and two FKBP fusion
proteins (FKBP-V48, FKBP-V72) were purified from E. coli using Inverse Transition
Cycling (ITC)(Hassouneh et al., 2010) with yields of 80-100 mgs/L (Table 3). SDS-PAGE
was used to determine the purity and molecular weights of all fusion constructs (Figure
17a). The precise molecular weight of the fusion proteins was determined by MALDI-TOF

Figure 17: Characterization of ELP fusion proteins. (a) Copper-stained SDS-PAGE confirmed the
identity and purity of fusion proteins. Samples appeared as single bands with V48 and V72 in lanes 2
and 3; and FKBP-V48 and FKBP-V72 in lanes 4 and 5 respectively. (b) Temperature-concentration
phase diagrams measured optical density at 350 nm by warming the sample solution at the rate of
1⁰C/min. ELPs phase separate above the indicated lines.
67

(Table 3). Optical density was used to characterize the temperature-concentration phase
diagrams for each fusion protein (Figure 17b). As observed in the figure, fusion to FKBP
minimally influences the ELP transition temperatures, and the Tt follows an inverse
relationship with logarithm of concentration (Meyer and Chilkoti, 2004). Using the fit
equation parameters for each of the fusion proteins (Figure 17b, Table 3), it is possible
to ‘set’ the Tt between 30 and 50 °C simply by selecting the appropriate fusion protein
(FKBP-V48 or FKBP-V72) and adjusting the concentration (1-100 µM).

3.4.2 The ELP transition temperature responds to stoichiometric additions of CID:
Given our hypothesis that a fusion between FKBP and an ELP protein polymer will exhibit
switchable solubility upon ligand binding, we first tested the fusion protein sensitivity
towards the CID. We chose the stoichiometric concentration CID: FKBP [1:2] as the
starting point because theoretically each bifunctional CID should homodimerize two
fusion proteins giving the maximal change in local concentration and hydrophobicity. A 5
μM FKBP-V48 solution in PBS was ramped from 15-60 ⁰C with and without (control)
stoichiometric amount of CID. Binding of the CID to the fusion protein lowered the phase
Table 3: Physical properties of ELP protein polymers with and without FKBP
Label
a
Amino acid
sequence
Expected
MW
(kDa)
b
Observed
MW
(kDa)
Tt at
25 µM
(⁰C)
c
Slope, m
[⁰C
Log (µM)]
c
Intercept, b
(⁰C)
V48 MG(VPGVG)48Y 19.7 19.7 38.8 7.01 48.8
V72 MG(VPGVG)72Y 29.5 29.6 33.2 4.45 39.5
FKBP-V48

FKBP-G(VPGVG)48Y 31.5 31.4 42.0 10.26 56.7
FKBP-V72 FKBP-G(VPGVG)72Y 41.3 41.3 33.4 5.76 41.5
a
FKBP amino acid sequence:
MGVQVETISPGDGRTFPKRGQTCVVHYTGMLEDGKKFDSSRDRNKPFKFMLGKQEVIRGWEEGVAQMSVGQRAKLTISPDYA
YGATGHPGIIPPHATLVFDVELLKLE
b
Dialyzed samples in water (500 µM) were mixed with acetonitrile saturated with sinapic acid, air dried, and
characterized using MALDI-TOF.
c
Phase diagrams were fit with the following linear relationship: Tt = b – m[Log10(concentration)]. Mean ± 95% CI.
R2 = 0.99.
68

transition temperature by ~ 5-6 ⁰C as compared to the control group (Figure 18 a, b).
Similar results were obtained upon stoichiometric addition of CID to 4 μM FKBP-V72
which lowers the Tt by ~ 3-4 ⁰C as compared to the control group (Figure 18 c, d). A
plausible explanation for this observation is that FKBP dimerization acts as a bridge,
roughly doubling the relative ELP chain length. In addition to increasing the ELP
concentration associated with the complex, dimerization might also be accompanied by
reduced number of interactions with the neighboring water molecules and a local increase
in the hydrophobic environment of the FKBP/CID complex. Unliganded FKBP is
associated with ordered water molecules in the hydrophobic binding cavity (Wilson et al.,
1995). However, in presence of a related CID ligand, which dimerizes a mutant FKBP
protein (FM), enhanced hydrophobic contacts as well as hydrogen bonding and

Figure 18: CID homodimerization to FKBP-ELP lowers its phase transition temperature. (a) Optical
density profile of 5 µM FKBP-V48 in presence of stoichiometric amount of CID (filled triangles) and
control (filled circles). (b) Decrease in transition temperature of 5 µM FKBP-V48 by stoichiometric CID
binding (n = 3), Paired t-test, p = 0.007, R
2
= 0.98 (c) Optical density profile of 4 µM FKBP-V72 in
presence of stoichiometric amount of CID (filled triangles) and control (filled circles). (d) Decrease in
transition temperature of 4 µM FKBP-V72 by stoichiometric CID binding (n = 3), Paired t-test, p = 0.023,
R
2
= 0.95.
69

electrostatic interactions between the dimer have been observed (Rollins et al., 2000). In
this study, CID likely induces a combination of FKBP-ELP dimerization and enhanced
local hydrophobicity, which together result in substrate-dependent phase separation
under isothermal conditions. As ELP phase separation depends on molecular weight and
local polarity, both an increase in local ELP concentration and hydrophobicity may
contribute to coacervation at reduced temperatures (Meyer and Chilkoti, 2004; Trabbic-
Carlson et al., 2004).
To further explore the responsiveness of ELP fusion proteins, we tested the behavior of
FKBP-ELP at different CID concentrations. We observed that the fusion protein follows a
biphasic competitive ligand-binding model. In particular, the fusion protein displays three
trends: i) stoichiometric concentrations of CID results in the largest decrease in Tt; ii)

Figure 19: FKBP-ELP phase transition temperature depends on CID stoichiometry. (a) T t values for 5
µM FKBP-V48 (n = 4) and (b) 2.5 µM FKBP-V72 (n = 4) decreases with increase in CID concentration
until CID: FKBP reaches stoichiometry (permitting the maximal concentration of homodimers).
Subsequent increase in the CID concentration competes apart homodimers and return the phase
transition temperature back upwards. (c) 5 µM V48 with different CID concentrations showing no
difference in T t.

70

above stoichiometry the system returns to the Tt values of the control group (without CID);
and iii) below stoichiometry Tt increases incrementally towards the control group as
observed for 5 μM FKBP-V48 (Figure 19a). This illustration supports our initial hypothesis
in three ways: First, at stoichiometric CID concentrations, one bifunctional CID
homodimerizes two FKBP-ELP fusion proteins giving the maximal concentration of
homodimers and the largest decrease in phase transition temperature. Second, at
increasing concentrations, the CID’s compete with each other to occupy FKBP binding
sites and in doing so, each FKBP binding pocket becomes occupied by a CID. At
saturating concentrations, no two free FKBP binding pockets are available to form the
homodimer and thus the complex phase separates at temperatures similar to the control
group. Third, with CID concentrations below stoichiometry, fewer homodimers are formed
because of lack of sufficient CID molecules and the observed Tt increases. A similar trend
is observed for 2.5 μM FKBP-V72 with CID concentrations above and below stoichiometry
(Figure 19b). A control of 5 µM V48 (without FKBP) in PBS with different CID
concentrations was evaluated similarly. There was no change in Tt in samples with CID
when compared to that of control (Figure 19c). Taken together, this suggests that the
decrease in Tt

observed with FKBP-ELP fusion protein (Figure 18) occurs due to FKBP
homodimerization in response to binding of its CID substrate. Thus, from these findings,
we observe that FKBP-ELP is not only sensitive to the CID, but actually responds in a
biphasic manner, whereby by adjusting the concentration of the ELP fusion protein it may
be possible to detect either a decrease or an increase in the target CID concentration.

71

3.4.3 Reversible switching of FKBP-ELP at isothermal conditions:
Having determined the specificity and stoichiometry of the FKBP-ELP phase separation
in response to CID concentration, we next explored the isothermal reversibility of the
switch using Rapamycin as a monomeric FKBP ligand. This was demonstrated by
measuring optical density of the fusion proteins at 350 nm as function of time on a UV-
Vis spectrophotometer with subsequent addition of stoichiometric amounts of CID and
Rapamycin at predetermined fixed intervals. A 5 μM FKBP-V48 solution in PBS was
stabilized at temperature of 46 ⁰C and temperature was held constant thereafter.
Stoichiometric addition of 2.5 μM CID led to an increase in particulate turbidity as
demonstrated by an increase in optical density to ~ 0.45, which returned to baseline levels
on stoichiometric addition of 5 μM Rapamycin (Figure 20a). The reversibility of the switch
may be attributed to the stronger affinity of Rapamycin for monomeric FKBP compared
to the CID. On addition of stoichiometric amounts of Rapamycin, it displaces the CID and
in doing so, it disrupts the homodimer. This returns the system to the phase transition
temperature observed for FKBP-ELP monomers, similar to that observed before addition
of CID. The reverse ELP phase separation presumably occurs due to a decrease in the
Figure 20: FKBP-ELP phase separation is fast and reversible under isothermal conditions. Phase
separation was determined by measuring optical density as function of time using UV Vis kinetics. (a)
Optical density profile of 5 µM FKBP-V48 (filled triangles) and control (filled circles) at 46 ⁰C. (b) Optical
density profile of 4 µM FKBP-V72 (filled triangles) and control (filled circles) at 37 ⁰C. The results were
seen after sequential addition of stoichiometric amounts of CID and Rapamycin as shown by arrows.
72

bridging of ELPs and return of the native FKBP state with increased polarity at the
FKBP/CID interface as well as a decrease in the local concentration of ELP. Binding of
Rapamycin to bovine FKBP has been shown to produce local changes in protein
conformation and mobility (Wilson et al., 1995). Furthermore, the atomic structure of
recombinant hFKBP with Rapamycin is associated with tightly bound water molecules
(Van Duyne et al., 1993). This suggests a possible role for the increased polarity of FKBP-
ELP-Rapamycin complex relative to CID-bound FKBP-ELP dimer. Under isothermal
conditions, this competition from Rapamycin thus reverses ELP to their soluble form.
Because solubility of Rapamycin in water is negligible (~ 3 µM) (Simamora et al., 2001),
a 36% v/v ethanol in water solution of Rapamycin was prepared for its solubilization and
used to demonstrate the reversibility of the protein switch. A control was performed using
36% v/v of ethanol (without Rapamycin), adding an amount equivalent to that used in the
sample group. The control was run to demonstrate that the reversibility of the switch was
not due to a solubilizing effect of trace ethanol but rather due to specific disruption of the
homodimer, successively reversing ELP phase separation. Isothermal switching was
performed at 46 ⁰C because FKBP-V48 (5 µM) phase separates above and below 46 ⁰C
in absence and presence of CID respectively (Figure 18b).
To demonstrate that isothermal switching is not limited to FKBP-V48 and show that
reversible phase separation can occur at physiological body temperature; we repeated
these experiments with the fusion construct FKBP-V72 (4 µM) at 37⁰C (Figure 18d). For
this construct, optical density rose up to ~0.45 upon addition of 2 µM CID and returned to
baseline upon successive addition of 4 µM Rapamycin (Figure 20b). This data shows
that it is possible to develop switchable ELP fusion polymers that are reversible under
73

isothermal conditions at any target temperature, simply by modulating ELP chain length
and concentration.

3.4.4 Quantitative modeling of FKBP-ELP switching behavior:
Similar to a mathematical model that relates ELP phase behavior to its molecular
architecture (Ghoorchian and Holland, 2011); we developed a quantitative model that
predicts the phase transition behavior based on the FKBP-ELP fusion homodimerization.
We began by quantifying the amount of FKBP-ELP in the dimeric or monomeric state at
any given concentration of fusion protein and CID. The fusion protein’s interaction with
CID is assumed to occur via a two-step mechanism. First, one FKBP-ELP protein binds
one CID. Then, the FKBP-ELP-CID complex binds a second FKBP-ELP protein to form
a homodimer (Figure 21). Eq. 10 and Eq. 11 represent the two reactions where free
FKBP-ELP is denoted as ‘P’, free CID is denoted as ‘L’, FKBP-ELP-CID is denoted as
‘PL’, and the homodimer is denoted as ‘P2L’.
P+L <--> PL (Eq. 10)
PL+P <--> P2L (Eq. 11)

Figure 21: FKBP-ELP dimerization occurs via a two-step process. FKBP-ELP protein binds to one CID
to give FKBP-ELP-CID complex which then binds to a second FKBP-ELP protein to give the homodimer.
74

Both steps are reversible, with distinct dissociation constants Kd1 and Kd2. Assuming the
system reaches equilibrium, Eq. 12 and Eq. 13 define Kd1 and Kd2. Square brackets
denote concentration.
Kd1 = [P ][L]/[PL ] (Eq. 12)
Kd2 = [PL ][P ]/[P
2
L] (Eq. 13)
Given the total concentration of FKBP-ELP as CELP and CID as CCID, applying a mass
balance to each species yields Eq. 14 and Eq. 15.
C
ELP
= [P ] + [PL ] + 2[P
2
L] (Eq. 14)
C
CID
= [L] + [PL ] + [P
2
L] (Eq. 15)
Eqs. 12, 13, 14, and 15 can be solved numerically for [P], [PL], [P2L], and [L], thus allowing
us to quantify the amount of FKBP-ELP that is ‘switched on’ [P2L] or ‘switched off’ [P],
[PL] at any total concentration of fusion protein and CID. To simplify the use of the above
expressions, we define the fraction of ELP fusion protein that exists in the homodimeric
state, f, as follows:
f =
2[P
2
L]
C
ELP
(Eq. 16)
Subject to the magnitudes of Kd1 and Kd2, f can be controlled by changing the total
concentration of FKBP-ELP fusion protein, CELP and the total concentration of the
chemical inducer of dimerization, CCID.
In addition to possible contributions from the polarity of the local environment, ELP
transition temperature depends on molecular weight and concentration; both of which
change during formation of the homodimeric species. Meyer and coworkers developed
an empirical model to describe the phase transition temperature as a function of chain
length, sequence identity, and concentration(Meyer and Chilkoti, 2004). We further
75

developed Meyer’s model to incorporate the concentration of FKBP-ELP that is ‘on’ and
‘off’ in order to quantify the relationship between [P], [L], [PL], and [P2L], and the phase
transition temperatures. Ultimately, this model allows the prediction of ELP phase
behavior, which will be essential to deliberately design ELP fusions that phase separate
in response to a specific concentration of a CID at a given temperature. Meyer’s model
relies on three constants—a critical transition temperature (Tc), a critical concentration
(Cc), and a constant (k) with units of ⁰C pentamers as follows:
T
t
= T
c
+ (
k
l
)ln(
C
c
C
ELP
) (Eq. 17)
The data in Figure 17b for ELPs with and without FKBP were fit to Eq. 17 (Table 4);
furthermore, these are in agreement with numbers reported for ELPs with Xaa = Val
(Meyer and Chilkoti, 2004). To incorporate the relationship between FKBP-ELP and CID
concentration into this model, Eq. 17 was combined with a series of assumptions as
follows: i) the phase behavior of the monomer and dimeric species will both follow the
solution for Eq. 17 (Table 4); ii) when f = 1, dimerization is accompanied by a 2 fold
decrease in the concentration; iii) subject to Eqs. 12, 13, 14 and 15, f depends on the
relative concentrations of the FKBP-ELP and the CID; and iv) the change in transition
temperature between the monomeric and dimeric species can be approximated by a
linear relationship as follows:
Table 4: Fit parameters for temperature vs. interaction of length and concentration for ELP with and without FKBP
fusion protein

*FKBP-ELP
(Xaa=Val)
*ELP
(Xaa=Val)
**ELP
(Xaa=Val)
Tc (⁰C) 15.5 21.7 20.8
k (⁰C pentamers) 203.5 144 129
Cc (μM) 14,120 8,008 25,000
* Data (Fig. 2b) fit to Eq. 17
** Reported values fit to Eq. 17
76

T
t
= ( 1 − f) T
t,monomer
+ f T
t,dimer
(Eq. 18)
This above approximation assumes that the whole system phase separates at a single
phase transition temperature and that this is a linear interpolation between the transition
temperature for 100% monomer and 100% dimer. This assumption was made for three
reasons: i) for mixtures of FKBP-ELP and CID below stoichiometric ratios, only a single
transition temperature was observed (Figure 19 a, b); ii) the phase transition temperature
for FKBP-ELPs followed a continuous-- not stepwise-- shift between the phase transition
temperature of the dimer and the monomer; and iii) a posteriori, this assumption fit the
data well. Since the whole system phase separates simultaneously, linear interpolation
(Eq. 18) was selected to relate the phase transition temperature of the entire system to
the monomer and dimer transition temperatures, which are given as follows:
T
t,monomer
= T
c
+ (
k
l
)ln(
C
c
C
ELP
) (Eq. 19)
and
T
t,dimer
= T
c
+ (
k
2l
)ln(
C
c
C
ELP
2
) (Eq. 20)
where l is length in pentamers of monomer and 2l is the length ELP associated with the
homodimer. In the case where f = 1, then the ELP concentration would be CELP divided in
half. Substitution of Eqs. 19 and 20 into Eq. 18, followed by simplification yields the
following relationship:
T
t
= T
c
+
k
l
[(1 −
f
2
)ln(
C
c
C
ELP
) + (
f
2
)ln ( 2) ] (Eq. 21)
Where in the case that f = 0, Eq. 21 reduces to Eq. 19, and if f = 1 then Eq. 21 reduces
to Eq. 20. Values for the model parameters Tc, k and Cc were obtained using nonlinear
77

regression to Eq. 17 to the set of FKBP-ELP transition temperatures, concentrations, and
lengths (Figure 17b, Table 4).

3.4.5 Modeling results:
The model described above was fit to the experimental data set of 5 µM FKBP-V48
(shown in Figure 19a). Least squares fitting by numerical iteration was used to estimate
the values for Kd1 and Kd2 that gave an optimal fit (Figure 22a). As demonstrated in the
figure, the optimal fit was obtained with Kd1 equal to 230 nM and Kd2 equal to 2.0 µM.
Given those parameters, the model predicts the biphasic inverse phase transition
temperature of FKBP-ELP fusion protein with a correlation coefficient of R
2
= 0.76. To

Figure 22: Quantitative model of FKBP-ELP switching behavior. (a) FKBP-V48 (5 μM) model fit with
parameters K d1 = 230 nM, K d2 = 2.0 μM and R
2
= 0.76 and (b) FKBP-V72 (2.5 μM) model fit with
parameters K d1 = 215 nM, K d2 = 2.7 μM and R
2
= 0.7. (c) To visualize the relationship between the shape
of the curve and K d2, the predicted transition temperature is indicated for FKBP-V72 (2.5 μM, K d1 = 215
nM) and varying the ratio of K d2/K d1.
78

confirm the validity of the model, it was also fit to the experimental data set of 2.5 µM
FKBP-V72 (shown in Figure 19b). Using least squares fitting by numerical iteration, the
values for Kd1 and Kd2 were found to be 215 nM and 2.7 µM respectively which yield a fit
with a correlation coefficient of R
2
= 0.70 (Figure 22b).
To further elucidate the differences between Kd1 and Kd2, we used our model to generate
a plot of expected transition temperatures for FKBP-V72 as a function of CID
concentration while varying the ratio between Kd1 and Kd2 (Figure 22c). This plot indicates
how for cases where Kd2/Kd1 = 1, a more significant downward shift in the transition
temperature would be expected than was observed (Figure 22b). Intuitively, it makes
sense that the two binding constants are different. The first binding event is the
unhindered interaction of a small molecule (CID) with a large hydrophobic face of a single
FKBP. In contrast, the second binding constant is the result of two FKBP domains coming
into close proximity. Unlike naturally dimeric proteins, the FKBP proteins are not
complementary. Instead, to dimerize via the CID, they must overcome additional steric
hindrance. Thus, this data suggests that for the FKBP/CID system, Kd1 is less than Kd2.
The predicted concentration of each form of FKBP-ELP, that is, [P], [PL], and [P2L] is
plotted against CID concentration for both the fusion proteins: 5 µM FKBP-V48 and 2.5
µM FKBP-V72 (Figure 23 a, b). These figures estimate how much of the FKBP-ELP is in
monomeric and dimeric form at any given CID concentration, and support our hypothesis
of competitive ligand binding model (as observed in Figure 19 a, b). As shown in the
figure, we observe that at zero concentration of CID, all FKBP-ELP is in free monomeric
form. As the CID is added, the concentration of free FKBP-ELP [P] drops quickly, as
individual monomers bind to CID molecules. The concentration of FKBP-ELP-CID [PL]
79

starts increasing until a particular CID concentration (stoichiometric amount) is reached,
where the concentration of homodimeric FKBP-ELP [P2L] is highest. Beyond
stoichiometry, at saturating concentrations of CID, each FKBP-ELP molecule’s binding
site is occupied by its own CID molecule. As the concentration of FKBP-ELP-CID [PL]
increases, the concentration of homodimer [P2L] decreases, and we observe the reverse
effect. These figures confirm that the highest concentration of homodimer [P2L] does in
fact occur when the concentration of CID is at stoichiometry. This model validates our
understanding of the FKBP-ELP switching behavior. In particular, it indicates that the two-
step reaction mechanism accurately describes the observed data and that the biphasic
phase separation can be mediated by the stoichiometry of FKBP binding to a CID.

3.4.6 Model limitations:

This model is designed to predict the transition temperature for a system of ELP
monomers and homodimeric complexes. The optical density measurements used to
generate Figures 17-19, revealed only a single major transition temperature for mixtures
of ELP and CID. For this reason, a linear interpolation model (Eq. 18) was selected to
model the transition temperature (Eq. 17). While the data suggest that all ELP fusion
Figure 23: Predicted concentrations of FKBP-ELP species vs. CID concentration. Maximal
concentration of homodimer formation [P 2L] occurs at stoichiometric concentrations of CID for (a) 5
μM FKBP-V48 and (b) 2.5 μM FKBP-V72.
80

proteins phase separate at a single transition temperature, limitations in the interpretation
of optical density prevent us from determining if monomeric species phase separate
simultaneously with homodimeric ELP complexes. Thus, this model is limited by the
assumption that the whole system phase separates at a single temperature. Similarly, the
empirical model (Eq. 17) used to calculate transition temperatures only incorporated
factors resulting from local molecular weight/concentration. Thus this model neglects
possible contributions by local hydrophobicity at the FKBP/CID interface. The model also
neglects possible contributions resulting from the phase separation of multi-block
architectures, such as ELP-FKBP/CID/FKBP-ELP. Next, we only demonstrated the
accuracy of this model in predicting fusion protein behavior with ELPs containing valine
as the guest residue. Lastly, this model relies on an assumption that the FKBP-ELP
mixture reaches equilibrium in solution. Despite these limitations, the ability of this model
to fit the observed data suggests that these assumptions are generally useful.

3.4.7 CID binding kinetics over immobilized FKBP-ELP:
To further validate the above model, an independent measurement was used to estimate
the equilibrium disassociation constant, Kd1, of the CID towards FKBP-ELP using Bio-
layer Interferometry (BLI). BLI is a label-free analytical technique that measures binding
kinetics in real time using microliter amounts of sample. BLI technology determines the
change in interference pattern of white light reflected by binding of molecules onto the
biosensor tip. This binding produces a shift in the interference pattern, which is recorded
in nanometers (nm) by the instrument. NHS-PEG4-Biotin was conjugated to exposed
lysine groups of FKBP-ELP fusion protein using NHS-ester chemistry; furthermore, this
81

material was immobilized on a streptavidin coated BLI biosensor tip. The experiment was
designed to determine the binding kinetics of the first binding event where CID binds to
FKBP-ELP giving FKBP-ELP-CID complex. Biotinylated FKBP-V72 was immobilized onto
streptavidin biosensors followed by subsequently immersing the biosensor tips into CID
solutions and PBS to measure the binding kinetics. Four different CID concentrations
were used for the binding assay – 0.05, 0.2, 1 and 2 µM. The magnitude of the binding
signal depended on the CID concentration (Figure 24). A global fit was done to determine
Kd1, kon and koff as 243 nM, 2.00x10
4
M
-1
s
-1
and 4.85x10
-3
s
-1
respectively. Taking into
consideration the design of the experiment, the affinity constant Kd1 determined by BLI
assay proved to be in relative agreement with that determined in the quantitative model
(Figure 22b). Due to the limitations of the instrument, BLI was unable to directly estimate
the second and weaker dissociation constant, Kd2; however, the agreement between
independently obtained values for Kd1 from BLI and the quantitative model strengthens
our hypothesis that FKBP-ELP interaction with CID is a two-step mechanism with two
binding events.

Figure 24: Binding of CID to FKBP-V72 shows strong association and fast dissociation kinetics.
Association and Dissociation kinetics of CID solutions over immobilized FKBP-V72 yield a global fit with
K d1 = 243 nM, k on = 2.00x10
4
M
-1
s
-1
and k off = 4.85x10
-3
s
-1
.
82

3.5 Conclusion
Adding to the drug delivery applications of ELPs as drug carriers, this chapter describes
a rational strategy to design biosensing ELPs that changes solubility in response to small
molecule ligands. To explore this approach, small molecules including both CID and
Rapamycin were shown to bind to FKBP-ELP fusion proteins and induce sharp, reversible
changes in the polypeptide solubility. A quantitative model was used to validate the
biphasic relationship between the CID-dependent phase diagrams for two fusion proteins.
This strategy to design switchable protein polymers has three distinct advantages over
any yet proposed. First, it provides a logical approach to detect classes of target
molecules that mediate dimerization via substrate-specific interaction with an ELP protein
fusion. While we have evaluated this approach to detect small molecule CID’s, this
strategy might similarly detect multimeric protein targets. Second, because the response
to CID concentration is biphasic, by adjusting the ratio between the ELP and CID this
strategy can induce either association or dissociation in response to a respective increase
or decrease in CID concentration. Third, the isothermal response to CID can be
modulated to occur at any temperature between 30 and 50°C by adjusting the ELP
molecular weight or concentration. ELPs of other amino acid sequences may permit a
wider range for isothermal switching; therefore, switching may be adaptable to
refrigeration, ambient, or physiological temperatures. Having demonstrated the feasibility
of this strategy, it may now be possible to engineer environmentally responsive protein
polymers that phase separate in response to multimeric target substrates. Due to the
adaptability and specificity of this strategy, these fusion protein polymers may be
evaluated for diverse applications in the detection and treatment of diseases.
83

3.6 Acknowledgements
This work was made possible by the University of Southern California, the National
Institute of Health R21EB012281, P30 CA014089 to the Norris Comprehensive Cancer
Center, the Wright Foundation, the Stop Cancer Foundation, the American Cancer
Society, the USC Ming Hsieh Institute to J.A.M., the USC Nanobiophysics Core Facility,
and the Translational Research Laboratory at the School of Pharmacy.

84

Chapter 4
Elastin-Like Polypeptide Switches – A design strategy to detect multimeric
proteins.

4.1 Abstract
Elastin-Like Polypeptides (ELPs) reversibly phase separate in response to changes in
temperature, pressure, concentration, pH, and ionic species. While powerful triggers,
biological microenvironments present a multitude of more specific biological cues, such
as antibodies, cytokines, and cell-surface receptors. To develop better biosensors and
bioresponsive drug carriers, rational strategies are required to sense and respond to
target proteins. We recently reported that non-covalent association of two ELP fusion
proteins to a ‘chemical inducer of dimerization’ small molecule (1.5 kDa) induces phase
separation at physiological temperatures. Having detected a small molecule, here we
present the first evidence that ELP multimerization can also detect a much larger (60 kDa)
protein target. To demonstrate this strategy, ELPs were biotinylated at their amino
terminus and mixed with tetrameric streptavidin. At a stoichiometric ratio of [4:1], two to
three biotin-ELPs associate with streptavidin into multimeric complexes with an apparent
Kd of 5 nM. The increased ELP density around a streptavidin core strongly promotes
isothermal phase separation, which was tuned to occur at physiological temperature. This
phase separation reverses upon saturation with excess streptavidin, which only favors
[1:1] complexes. Together, these findings suggest that ELP association with multimeric
biomolecules is a viable strategy to deliberately engineer ELPs that respond to multimeric
protein substrates.
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4.2 Introduction
Protein-polymers are recombinant polypeptides that can be genetically engineered, which
allows precise control over their composition and biosynthesis. One class of protein-
polymers are the elastin-like polypeptides (ELPs), which are biologically inspired from
human tropoelastin(Urry et al., 1976). Typical ELPs are composed of repetitive
pentameric sequence (Val-Pro-Gly-Xaa-Gly)l where Xaa is a guest residue and l defines
the molecular weight. ELPs are highly water soluble until they are heated beyond their
inverse phase transition temperature, Tt. Above Tt, ELPs phase separate from bulk water,
a process that can be tuned by changing ELP concentration and molecular
weight(Mackay et al., 2010; Meyer and Chilkoti, 2004). Since ELPs can be fused to
different functional domains such as cell trafficking proteins(Pastuszka et al., 2014), drug-
binding receptors(Shah et al., 2013; Shi et al., 2013) and antibody fragments(Aluri et al.,
2014), this enables them to bind and recognize different targets. By combining the ELP-
mediated phase separation and the ability of fused domains to bind specific targets, ELP
fusions and bioconjugates make an excellent platform for developing smart bioresponsive
polymers. The rationale of this work is that ELP phase separation depends on molecular
weight, concentration, and local hydrophobicity; therefore, target biomolecules that shift
these properties may induce isothermal phase separation at physiological temperature.
If successful, this design strategy may enable development of ELP fusions that both
detect and deliver agents to diseased microenvironments with high selectivity.
We recently reported that non-covalent dimerization of two FKBP-ELP fusion proteins
(32, 41 kDa) induces ELP phase separation upon binding to a small molecule target (1.5
kDa) called a ‘chemical inducer of dimerization’ (CID)(Dhandhukia et al., 2013). This
86

study takes this design strategy to the next logical step, to detect a high molecular weight
multimeric protein, streptavidin (Figure 25). Although previous studies have described
ELPs that respond to an allosteric ligand(Kim and Chilkoti, 2008) or use phase separation
of synthetic polymers to modulate protein-ligand interactions(Ding et al., 2001; Shimoboji
et al., 2002a; Shimoboji et al., 2003; Stayton et al., 1995), we are the first group to report
that non-covalent ELP crosslinking is a simple design strategy to detect multimeric
biomolecules. In this study, we extend our hypothesis and report that: (i) ELP phase
separation can also detect large (60 kDa) tetrameric proteins; and (ii) this can be tuned
to occur at physiological temperatures even with a high molecular weight ELP (77 kDa)
(Table 5). Due to the ubiquity of multimeric proteins in nature, including IL-5 cytokine
(dimer)(Kusano et al., 2012), hemoglobin (tetramer)(Vitagliano et al., 2016),
immunoglobulins of class IgA (dimer)(Woof and Russell, 2011) and IgM (pentamer)(Boes,
2000), and cell-surface receptor tyrosine kinases (dimer) like VEGFR and

Figure 25: Designing bioresponsive ELPs that phase separate in response to a model multimeric
protein: streptavidin. Biotin-ELPs phase separate above a relatively high temperature and remain
soluble; however, when they crosslink with streptavidin, the resulting complex undergoes rapid
phase separation. This concept provides a rational strategy to design switchable ELPs that detect
multimeric proteins at a constant physiological temperature.

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EGFR(Lemmon and Schlessinger, 2010; Mac Gabhann and Popel, 2007; Swift et al.,
2011), crosslinking ELPs might be designed to detect many species important in
diagnostic and therapeutic applications.
Streptavidin is a ~60 kDa homotetrameric protein isolated from S.avidinii(Hofmann et al.,
1980). Each subunit of streptavidin has a potential biotin binding pocket(Weber et al.,
1989). Given many possible proteins with multimeric quaternary structures, we chose
streptavidin to study ELP multimerization because: (i) biotin-streptavidin interactions are
well-characterized with picomolar affinity(Qureshi et al., 2001), which may provide a
strong association between biotin-ELPs and streptavidin; (ii) biotin is a small molecule
that can be bioconjugated at high yield and specificity to the amino terminus of purified
ELPs; (iii) surprisingly, no other investigators have reported a relationship between
streptavidin-biotin interactions and the ELP phase behavior. Although streptavidin-ELP
interactions have been recently explored to enhance an immunoassay(Ikeda et al., 2016),
to the best of our knowledge, this is the first report that ELP assembly on streptavidin
significantly changes ELP phase behavior. Future iterations of this design strategy may
be useful to develop bioresponsive diagnostics and therapeutics that bind to other
multimeric species.

4.3 Materials and Methods
4.3.1 ELP expression, purification and characterization
A modified pET25b(+) vector containing the ELP(Pastuszka et al., 2012) gene was
transfected into BLR (DE3) E.coli competent cells (EMD Millipore, Billerica, MA) and
inoculated onto Agar plates with 100 µg/mL ampicillin. A batch of 3-4 liters of bacterial
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culture was grown at 37 C by overnight inoculation with bacterial cells obtained from a
50 mL terrific broth starter culture supplemented with 100 µg/mL carbenicillin. Cultures
were harvested by centrifugation at 4000 rpm for 12 min at 37 C and cells were
resuspended in cold PBS (Dulbecco’s sterile PBS buffer, PBL01, Caisson labs,
Smithfield, UT). Resuspended cells were lysed using a microfluidizer (Microfluidics,
Newton, MA) to release cytosolic ELPs. Polyethylene imine (0.5 %) was added to the
lysed cells for co-precipitation of DNA. Cells were then centrifuged at 4000 rpm for 12 min
at 4 C to remove insoluble cellular debris. ELP in the supernatant was purified using
Inverse Transition Cycling(Hassouneh et al., 2010). Purification cycles were repeated 3-
4 times until > 90% purity was achieved by SDS-PAGE. ELP was filtered using 200 nm
cellulose acetate filters (28145-477, VWR, Radnor, PA) and concentration was estimated
using Beer-Lambert’s law at A280 using 1,285 M
-1
cm
-1
as the molar extinction
coefficient(Pace et al., 1995). Purity and identity was determined by loading 5 µg ELP in
SDS loading buffer, heating at 95 C for 5 mins, and running on a 4-20% gradient Tris-
Glycine SDS PAGE gel (58505, Lonza, Walkersville, MD). A standard Kaleidoscope
protein ladder (161-0395, Bio-Rad, Hercules, CA) was run for comparison. Gels were
stained using 10% w/v copper chloride and imaged using a VersaDoc (Bio-Rad, Hercules,
CA) Gel Imager (Figure 26a). The purity was quantified using ImageJ (NIH, USA) using
the following equation:
% purity =
𝐴 𝑝𝑒𝑎𝑘 𝐴 𝑡𝑜𝑡 ×100 (22)
where Apeak is the area of the protein band peak and Atot is the total area under all the
peaks in the lane.

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4.3.2 Biotin labeling and quantification of ELPs
Purified ELP, 2VA192, having a single primary amine at the amino terminus was
conjugated with biotin using N-hydroxysuccinimide chemistry. Briefly, 200 µM ELP in PBS
was mixed with 20 fold molar excess of Sulfo-NHS-biotin (21326, Thermo Fischer
Scientific, Waltham, MA) dissolved in PBS. The reaction mixture was incubated on ice for
1 hour and then overnight at 4 C. The reaction mixture was then dialyzed in PBS under
1:1000 sink condition to remove excess free biotin. The PBS buffer was replaced at 2 and
4 hour intervals and purified samples were collected after 16 hours. The biotin
concentration was quantified using the HABA (4'-hydroxyazobenzene-2-carboxylic acid)
quantification kit (28005, Thermo Fischer Scientific), and this value was used to estimate
a biotin labeling of 88.9%.

4.3.3 Biotin-ELP kinetics and transition temperature determination
The ELP transition temperature, Tt, was determined using a UV-Vis spectrophotometer
over a temperature gradient. ELPs at different concentrations in PBS were heated from
20 – 50 C in Beckman Coulter Tm microcells (Brea, CA). The temperature was increased
at rate of 1 °C/min with readings taken every 0.3 °C. Optical density at 350 nm was
collected, and the Tt was defined as the lowest temperature where ELPs could be
observed undergoing phase separation, taken as the OD measurement 5% above
baseline (Figure 26b). Biotin-ELPs were mixed with [4:1] ratio of streptavidin (S4762,
Sigma Aldrich Inc, St. Louis, MO) and Tt was determined by performing temperature
ramps (Figure 28 a, d). Similarly, Tt of biotin-ELPs mixed with streptavidin below and
above stoichiometry was determined (Figure 30 a-c). The kinetics of biotin-ELP
90

coacervation at constant temperature was performed by measuring optical density over
time after addition of streptavidin in [4:1] ratio (Figure 28 c, f).

4.3.4 Thermodynamics for streptavidin and biotin-ELP assembly
The equilibrium dissociation constant and thermodynamic parameters between biotin-
ELP and streptavidin were studied using Isothermal Titration Calorimetry (Figure 27) on
a MicroCal PEAQ ITC (Malvern Instruments Ltd, Worcestershire, United Kingdom). The
reference cell was filled with water, and calorimetry was performed at 25 °C. Standard
titrations were performed with streptavidin (300 µl at 1 µM in PBS) in the calorimeter cell
and a titration syringe filled with biotin-ELP (30 µM in PBS) was injected (3 µl) into the
calorimeter cell 12 times, allowing sufficient time between successive injections to
facilitate equilibration. The resulting isotherm was fitted to a ‘one-set-of-sites’ binding
model in offset mode using MicroCal PEAQ ITC analysis software (Malvern Instruments)
to generate affinity (Kd), number of binding sites, enthalpy (ΔH), entropy (-TΔS), and the
Gibbs free energy of binding (ΔG). All values are reported as mean ± SD (n = 3).

4.3.5 Particle size measurement using Dynamic Light Scattering
Purified biotin-ELPs were evaluated in the absence and presence of streptavidin for their
hydrodynamic radius (Rh) using Dynamic Light Scattering at 25 C on a Wyatt Dynapro
plate reader (Santa Barbara, CA) (Figure 30e). High concentration solutions of biotin-
ELP and streptavidin in PBS were filtered separately using 200 nm sterile Acrodisc
®
13
mm filters (PN 4454, Pall Corporation, Port Washington, NY). After filtration, samples
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were mixed in ratios of biotin-ELP: streptavidin of [16:1], [4:1], and [1:1] keeping biotin-
ELP constant at 20 µM. All values are reported as mean ± SD (n = 3).

4.4 Results
4.4.1 Purification of biotin-ELP and characterization of its phase behavior
To test the hypothesis that ELP multimerization can drive isothermal assembly near a
physiologically-relevant temperature, a new 77 kDa high molecular weight ELP, 2VA192,
was constructed with amino acid sequence MG(VPGVGVPGVGVPGAG)64Y. 2VA192
was purified from E.coli with yields of 30-50 mgs/L. The identity and purity (94%) was
determined using SDS-PAGE gel (Figure 26a). This particular ELP was chosen because
its molecular weight is greater than the ~ 60 kDa streptavidin tetramer; furthermore, its
repetitive sequence containing valine and alanine in a 2:1 ratio enables it to phase
separate near physiological temperatures within target concentrations between 1 and 10
μM (Table 5). The concentration – temperature phase diagram for the entire (2VA) ELP
library with increasing chain length was determined by measuring optical density as a
function of temperature (Figure 26b). Similarly, the Tt of biotin-ELP with and without

Figure 26: Identification of a high molecular weight ELP that detects streptavidin-biotin
interactions. (a) SDS-PAGE confirmed the identity and purity of an ELP, 2VA192 (Table 5). (b) Optical
density was used to characterize the concentration-temperature phase diagrams for a library of ELPs
with increasing chain lengths. ELPs phase separate above the indicated best-fit lines. (c) Similarly,
biotin-2VA192 (biotin-ELP) with and without a stoichiometric ratio of streptavidin [4:1] was
characterized. The best-fit line and its 95% confidence interval are depicted.

92

stoichiometric ratio of streptavidin [4:1] was determined (Figure 26c). As observed,
biotinylation of 2VA192 had little influence on Tt; however, when biotin-ELP was combined
with streptavidin, both the magnitude and slope of line decreased. To quantify this shift in
phase behavior, each individual ELP in this library was fit by the following equation:
𝑇 𝑡 = 𝑏 − 𝑚 Log
10
( 𝐶 𝐸𝐿𝑃 ) (23)
The intercept, b, is the Tt at a reference concentration of 1 μM. The slope, m, can be
interpreted as the decrease in Tt with a ten-fold increase in concentration, CELP. Using
Eq. 26, the working Tt of each ELP can be estimated at any concentration (Table 5). For
example, 1 μM biotin-ELP is soluble at physiological temperature (Tt, intercept ~ 38 °C);
however, if concentrated to 10 μM, it would phase separate at body temperature (Tt ~ 34
°C) (Figure 26c). Usefully, this fit reveals that the slope, m, of the temperature-
concentration phase diagram for biotin-ELP drops from 3.8 to 2.0 °C upon binding with
streptavidin (Table 5). To further interpret this change to the phase diagram, the phase
Table 5: Physical properties of (2VA) ELPs evaluated in this report
Label Amino acid sequence MW
(kDa)
a
Tt, Slope, m
[⁰C Log (µM)]
a
Tt,

Intercept,
b (⁰C)
2VA30
2VA36
2VA48
2VA72
2VA96
2VA192
biotin-ELP

biotin-ELP +
streptavidin [4:1]
MG(VPGVGVPGVGVPGAG)10Y
MG(VPGVGVPGVGVPGAG)12Y
MG(VPGVGVPGVGVPGAG)16Y
MG(VPGVGVPGVGVPGAG)24Y
MG(VPGVGVPGVGVPGAG)32Y
MG(VPGVGVPGVGVPGAG)64Y
biotin-
MG(VPGVGVPGVGVPGAG)64Y
-
12.4
14.8
19.6
29.2
38.8
77.2
77.4

-
29.5 ± 13
24.6 ± 7.9
11.9 ± 1.4
7.3 ± 0.4
5.7 ± 0.2
3.3 ± 0.3
3.8 ± 0.8

2.0 ± 0.4
124.9 ± 23
107 ± 11.3
73.9 ± 2
55.3 ± 0.5
47.4 ± 0.3
38.3 ± 0.4
38.1 ± 0.7

33.9 ± 0.3
a
Concentration-temperature phase diagrams (Fig. 26 b, c) were fit with Eq. 23. Values represent mean ±
95% CI.

93

behavior for the entire library (Figure 26b) was next fit to a previously described
model(Meyer and Chilkoti, 2004) using:
𝑇 𝑡 = 𝑇 𝑐 + (
𝑘 𝑙 ) ln (
𝐶 𝑐 𝐶 𝐸𝐿𝑃 ) (24)
where best-fit parameters Tc = 22.7 ± 2.4 °C, k = 337 ± 46 °C pentamers, and Cc = 5,214
± 3,878 μM describe the transition temperature for any length, l in pentamers, or
concentration of ELPs with the amino acid composition in Table 5. Insertion of these
parameter values into Eq. 24 and rearranging yields:
𝑇 𝑡 = 22.7 +
337×ln( 5,214)
𝑙 −
337×2.303 Log
10
( 𝐶 𝐸𝐿𝑃 )
𝑙 (25)
Based on inspection of Eqs. 23 and 25, the apparent number of ELP pentamers needed
to complex with streptavidin to result in slope, m, can be estimated as follows:
𝑙 =
776
𝑚 (26)
Using the 95% confidence interval [1.6 to 2.4 °C] (Table 5), for the slope of the biotin-
ELP: streptavidin complex, Eq. 26 may be used to estimate that a multimeric complex
containing between l = 323 and 485 ELP pentameric repeats might be expected to have
slope similar to that observed. Since each biotin-ELP is composed from 192 repeats, an
average complex containing between 1.7 and 2.5 biotin-ELPs per streptavidin would be
consistent with the phase behavior observed (Figure 26c).

4.4.2 Biotin-ELP associate into dimeric and trimeric complexes with streptavidin
Having observed that complexation between biotin-ELPs and streptavidin yields a
quantifiable shift in the phase diagram (Figure 26c), isothermal titration calorimetry (ITC)
was used to quantify the equilibrium disassociation constant (Kd), binding stoichiometry,
and thermodynamics (ΔH, -TΔS, ΔG). Prior to the assay, biotin-ELPs and streptavidin
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were dialyzed against phosphate buffered saline (PBS) to maintain equivalent buffer
composition and to prevent background heat of release due to differences in buffer
composition. Standard titrations were performed at 25 °C with biotin-ELPs injected into a
calorimeter cell containing streptavidin. Saturable heat release (Figure 27a) was
observed and fit to a ‘one-set-of-sites’ binding model to generate a binding curve (Figure
27b). Using the model fit, the binding stoichiometry was estimated as 2.77 ± 0.06 biotin-
ELPs per streptavidin. This experimentally determined stoichiometry is consistent with
the observed phase behavior and quantitative prediction of ELP crosslinking (Figure
26c), and suggests that the complex is a mixture of dimeric and trimeric ELPs. Other
thermodynamic parameters determined on biotin-ELP/streptavidin interaction were (i) an
apparent affinity (Kd) of 5.4 ± 3.2 nM (ii) binding enthalpy (ΔH) of -69.8 ± 5.1 kJ/mol (iii)
ligand entropy (-TΔS) of 22.3 ± 5.4 kJ/mol and (iv) Gibbs free energy (ΔG) of -47.5 ± 1.4
kJ/mol. Based on overall negative ΔG, which is the sum of enthalpy and entropy,

Figure 27: Biotin-ELPs interact with up to three sites on streptavidin. Isothermal titration calorimetry
was performed to quantify binding stoichiometry and thermodynamic parameters between 1 µM
streptavidin in PBS at 25 °C in a calorimeter cell titrated with injections of 30 µM biotin-ELPs. (a) Raw
binding isotherm shows saturable heat release indicating distinct binding between biotin and
streptavidin. (b) The binding fitting curve revealed an inflection near the biotin-ELP/streptavidin ratio
of ~3, which indicates that these complexes formed at an excess of biotin-ELP are at most trimeric
complexes. A representative data set is shown from n=3.

95

interactions between about three biotin-ELPs and streptavidin appear to be
thermodynamically favorable.

4.4.3 Fine tuning biotin-ELP detection of streptavidin to occur at physiological
temperatures
After demonstrating that a molar ratio of biotin-ELP to streptavidin [4:1] results in
assembly of dimeric and trimeric ELP complexes with reduced phase transition
temperatures, these complexes were further tuned such that their assembly occurs at
physiologically relevant temperatures. First, a 5 μM biotin-ELP solution in PBS was
heated with and without streptavidin and the Tt was identified. Binding of streptavidin to

Figure 28: Adjustment of the biotin-ELP concentration tunes streptavidin-induced phase separation
to physiological temperatures. (a) Optical density was observed for a 5 µM biotin-ELP with and
without a stoichiometric ratio of streptavidin as a function of temperature. (b) Addition of streptavidin
to the 5 µM biotin-ELP significantly reduces T t (n = 3, mean ± SD), Paired t-test, p = 0.0006. (c) The
kinetics of phase separation for 5 µM biotin-ELP held constant at 33.5 °C were observed upon addition
of streptavidin at the stoichiometric ratio [4:1]. (d) Optical density of 1 µM biotin-ELP was observed
with and without a stoichiometric ratio of streptavidin as a function of temperature. (e) Addition of
streptavidin to 1 µM biotin-ELP significantly reduces T t from above to below 37 °C (n = 3, mean ± SD),
Paired t-test, p = 0.004. (f) By tuning the biotin-ELP concentration down to 1 μM and holding the
temperature constant at 37 °C, rapid phase separation was again observed.

96

biotin-ELP lowered the phase transition temperature by ~ 3 °C compared to the control
(Figure 28 a, b). Having determined the Tt with and without streptavidin, the kinetics of
coacervation were next characterized by measuring optical density at constant
temperature of 33.5 C (Figure 28c). Biotin-ELP was optically clear and soluble at the
baseline temperature; however, within 40 secs of adding streptavidin at [4:1] molar ratio,
the optical density rose sharply. A control mixture of unlabeled ELP (without biotin)
produced a negligible increase in OD upon addition of streptavidin (Figure 29). To tune
the phase separation to occur around 37 °C, this experiment was repeated using 1 μM
biotin-ELP, which produced an ~4 °C decrease in Tt upon adding streptavidin (Figure 28
d, e). Upon addition of the stoichiometric ratio of streptavidin, the system again rapidly
phase separated due to ELP multimerization (Figure 28f). Both experiments demonstrate
how simple it is to tune and detect target concentrations of streptavidin near
physiologically relevant temperatures.

Figure 29: ELP does not respond to streptavidin in the absence of biotin labeling. The optical density
of 5 µM unlabeled ELP was monitored at 33.5 °C as a function of time after addition of streptavidin at
the stoichiometric ratio of [4:1]. A high optical density, consistent with phase separation was not
observed.

97

4.4.4 Biotin-ELP transition temperature responds to multimerization at different
streptavidin ratios
While it was clear that streptavidin reduces Tt for biotin-ELP, it remained unclear what
degree of multimerization (dimer, trimer) dominated this shift or how the ratio between
biotin and streptavidin affects phase separation. To further explore these questions,
biotin-ELP at a fixed concentration was incubated with streptavidin below and above [4:1]
molar stoichiometry (Figure 30 a-c). Similar to observations of an FKBP-ELP undergoing
dimerization(Dhandhukia et al., 2013), biotin-ELP follows biphasic competitive ligand

Figure 30: The biotin-ELP transition temperature is minimized when the formation of multimers with
streptavidin is maximized. (a) Optical density profiles of 5 µM biotin-ELP in presence of different
streptavidin concentrations below stoichiometry and (b) above stoichiometry. (c) T t for 5 µM biotin-
ELP decreases with increasing streptavidin concentration until reaching stoichiometry of [4:1], which
permits the maximum concentration of ELP multimers. Subsequent increase in streptavidin
concentration competes apart multimers, returning T t back upwards (n = 3, mean ± SD). (d) As a
control, 5 µM unlabeled ELP (2VA192) was incubated with different streptavidin concentrations below
and above stoichiometry. No change in T t was observed which confirms that streptavidin has no effect
on unmodified ELP (e) Dynamic light scattering was used to compare the particle size distributions at
25 C for free streptavidin, free biotin-ELP and biotin-ELP: streptavidin mixed in ratios of 16:1, 4:1, and
1:1 (Table II). A near stoichiometric [4:1] mixture of biotin-ELP produces the largest hydrodynamic
radius, consistent with the assembly of multimeric complex. A representative data set from n = 3 is
shown.

98

binding model. A distinct trend in the phase transition temperature of biotin-ELP was
observed with increasing concentrations of streptavidin (Figure 30c). The trend was
noticeable in three ways: (i) at zero concentration of streptavidin, biotin-ELP phase
separates at a Tt value of ~ 35 C; however, with small increase in streptavidin
concentration the Tt decreases sharply. (ii) Near the stoichiometric ratio of streptavidin
[4:1], a minimum value for Tt was observed. (iii) For streptavidin concentrations above the
[4:1] stoichiometric point, the biotin-ELP Tt increases more gradually back to that of the
control group. To rule out the possibility that streptavidin has a non-specific interaction
with 2VA192, unlabeled ELP was evaluated similarly below and above stoichiometry
(Figure 30d) which produced no change in the ELP Tt.
After demonstrating that the biotin-ELP Tt responds in a biphasic manner to streptavidin
concentration, the relative size of these complexes was then probed using dynamic light
scattering (DLS) over similar ratios below and above stoichiometry (Figure 30e). To avoid
the scattering of light by coacervate particles and to interpret the size of the crosslinked
complex in its soluble state, particle size was measured at 25 C, a temperature well
below the Tt for biotin-ELP complexes (Figure 26c). To detect sufficient scattering from
both free streptavidin and biotin-ELP, a 4-fold higher concentration of biotin-ELP (20 μM)
was required. Similar to the biphasic response in Tt, biotin-ELP streptavidin complexes
also displayed a biphasic change in particle size distribution (Table 6). Under these
conditions, free streptavidin displayed a hydrodynamic radius, Rh of 4.7 ± 0.7 nm and free
biotin-ELP displayed a Rh, of 7.3 ± 0.4 nm. When biotin-ELPs were mixed with different
ratios of streptavidin, the Rh of the crosslinking complexes were 10.2 ± 0.1 nm [16:1], 13.3
± 0.3 nm [4:1] and 9.2 ± 0.1 nm [1:1]. This light scattering data clearly demonstrates that
99

the maximum extent of ELP multimerization occurs at the same stoichiometric ratio [4:1]
that most significantly depresses Tt (Figure 30c).

4.5 Discussion
Polymer phase separation has been previously explored for various biosensing
applications. Synthetic polymers like poly(N-isopropylacrylamide)(Stayton et al., 1995),
poly(N,N-diethylacrylamide)(Ding et al., 2001) and N-4-
phenylazophenylacrylamide(Shimoboji et al., 2002a) have been reported to respond to
stimuli, such as temperature and light, to control binding of small molecules to target
proteins. In comparison to synthetic polymers, protein-polymers may have added
advantages as smart polymers due to recombinant production that enables their precise
linkage with functional proteins. For example, the ELP protein-polymers are produced
using cellular translation machinery, which promotes control over their design,
arrangement, and reproducibility and can eliminate the need for chemical
bioconjugation(Despanie et al., 2016). ELPs fused with calmodulin have been reported
to undergo phase separation in response to binding of Ca
2+
, which was reversed by
Table 6: Hydrodynamic radii for biotin-ELP complexes with streptavidin
biotin-ELP
(µM)
Streptavidin
(µM)
Ratio
(biotin-ELP: streptavidin)
a
Rh at 25 °C
(nm)

0 5 - 4.7 ± 0.7
20 0 - 7.3 ± 0.4
20 1.25 16:1 10.2 ± 0.1
20 5 4:1 13.3 ± 0.3
20 20 1:1 9.2 ± 0.1
a
Rh,

hydrodynamic radius determined by Dynamic Light Scattering (n = 3, mean ± SD)

100

chelation of Ca
2+
by EDTA(Kim and Chilkoti, 2008). An alternative design strategy
developed smart ELPs with negatively charged calcium-binding motifs to respond upon
neutralization by divalent Ca
2+
cations(Hassouneh et al., 2013). Despite these innovative
biosensing applications, no approaches have defined a strategy based on ELP
multimerization as a workable strategy to respond to target proteins. To address this
untapped niche, our group first demonstrated that ELP dimerization is a viable technique
to detect small ligand molecules. In this study, we extend this defined multimerization
strategy from the detection of a small molecule to a large multimeric protein.
It has been known that various environmental parameters can induce ELP-mediated
phase separation(Urry, 1988, 1992); however, few reports have discussed how
interactions with other macromolecules affect assembly. The primary finding of this study
is that biotin-ELPs change their phase behavior upon binding their target protein;
furthermore, this is mediated through assembly of multimeric structures. Our working
model is that ELPs in the presence of a stoichiometric amount of a target protein
assemble multivalent complexes (Figure 26, 28, 30), which increases the local density of
ELPs and reduces the observed Tt. When the Tt of biotin-ELP was studied across
increasing streptavidin concentrations, a distinct biphasic ligand-binding trend was
observed (Figure 30c). This relationship was further explored by extrapolating the data
in Figure 26b using Eq. 24 with an assumption that biotin-ELPs complexed around a
streptavidin core would behave similarly to ELPs with greater length. This assumption
allows estimation of the number of ELP pentamer repeats, l, necessary to achieve the
same phase diagram observed for biotin-ELP in the presence of [4:1] streptavidin (Figure
26c, Table 5). This extrapolation estimates that between 1.7 to 2.5 biotin-ELPs are bound
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to the average streptavidin. This assumption was then independently validated using ITC,
whereby a remarkably similar biotin-ELP/streptavidin binding stoichiometry of ~2.77 ±
0.06 was obtained. Taken together, these findings suggest that ELP multimerization is
sufficient to detect mixtures of dimeric and trimeric ELP complexes. This strategy will be
the most useful if it can generate fusion proteins that respond to target biomolecules at
physiological concentrations and constant temperatures. Therefore, we used this
approach to show how simple it is to design ELPs to detect streptavidin at a constant
temperature relevant to physiology (Figure 28). When streptavidin was added to 5 µM
biotin-ELP at 33.5°C, the sharp rise in optical density confirmed that ELP can successfully
detect streptavidin by rapid phase separation, which could be tuned to physiological
temperature by lowering the biotin-ELP concentration to 1 µM (Figure 28 c, f).
To confirm direct binding between biotin-ELPs and multiple sites on streptavidin, binding
thermodynamics and stoichiometry were evaluated using ITC (Figure 27). ITC is a
powerful label-free technique to evaluate bio-molecular interactions using thermodynamic
measurements. Calorimetry was performed below the ELP Tt to determine the
relationship between substrate binding in the soluble state. Saturable heat release was
observed, which suggests specific interaction between biotin and streptavidin domain
(Figure 27a). The sharp inflection in ΔH on successive injections of biotin-ELP occurred
just before hitting saturation where the stoichiometry of biotin-ELP/streptavidin was ~2.77
± 0.06 (Figure 27b). This confirms that our bacteria-derived source of streptavidin has a
capacity to assemble trimeric complexes and rules unlikely the extensive formation of
tetramers. A similar binding stoichiometry of 2.5 sites was reported previously where ITC
was used to study interaction between free biotin and streptavidin(Kuo et al., 2015);
102

furthermore, that report used the same commercial source for streptavidin as used here.
This suggests that fusion of 77 kDa ELP to biotin does not radically hinder its ability to
bind to between 1 and 3 pockets on each streptavidin. Using the ‘one set of sites’ binding
model, the ITC binding curve was best fit by a Kd of 5.4 ± 3.2 nM (Figure 27b). Using
other techniques, biotin affinities for streptavidin have been characterized in the pM range
(Magalhaes et al., 2011; Qureshi et al., 2001). For example, biotin-streptavidin
interactions with Kd ~ 5 x 10
-14
M, have been estimated from stop-flow fluorescence
kinetics(Hyre et al., 2006). This discrepancy occurs because conventional ITC has a
limited ability to measure affinities below a Kd of 1 x 10
-9
M. This limitation occurs due to
the steep increase in molar heat of injection with small increase in the biotin/streptavidin
ratio. Hence, the best interpretation of this affinity is that each of the 3 binding pockets on
streptavidin has an apparent affinity for biotin-ELP at or below 5.4 nM. A gain in binding
enthalpy (ΔH) of -69.8 ± 5.1 kJ/mol indicates that binding is an exothermic reaction with
heat released due to non-covalent association between biotin-ELP and streptavidin
favoring an enthalpy-driven binding mechanism. A positive (-TΔS) value of 22.3 ± 5.4
kJ/mol revealed an entropic cost due to loss in conformational ligand entropy associated
with a decrease in the disordered state of biotin-ELP when bound to streptavidin. The
sum of enthalpy and entropy, given by a negative Gibbs free binding energy (ΔG) of -47.5
± 1.4 kJ/mol suggests that biotin-ELP crosslinking around a streptavidin core remains a
thermodynamically favorable interaction at relevant concentrations. Biotin-streptavidin
thermodynamics have been studied previously by other groups using atomic force
microscopy(Chilkoti et al., 1995) and ITC(Kuo et al., 2015; Magalhaes et al., 2011), giving
similar ΔH, -TΔS and ΔG values to that observed in our hands. Small differences in these
103

values could be attributed to difference in bacterial vs mammalian expressed streptavidin,
fusion of 77 kDa ELP to biotin, and differences in buffers(Kuo et al., 2015).
The relationship between ELP crosslinking and the change in Tt with increasing
streptavidin ratios suggests phase separation occurs in three different regimes (Figure
30). First, in absence of streptavidin, biotin-ELPs remain unassociated and undergo
phase separation at a particular Tt. Second, with small increments in streptavidin
concentration, a sharp downward shift in Tt occurs due to the formation of ELP multimers.
At low streptavidin concentrations, the biotin-ELP remains at great excess. As the
concentration of streptavidin is increased, the complexation of two or three ELPs
decreases the Tt of the solution. This proceeds up to a point; however, when the target
approaches its molar stoichiometric ratio [4:1], the maximum concentration of biotin-ELP
multimeric complexes is produced, yielding a maximal drop in Tt. Third, at streptavidin
concentrations above stoichiometry, the biotin-ELPs become saturated with excess
streptavidin such that only 1:1 complexes are formed. Since the 1:1 complexes have a
higher Tt than the multimers, the Tt of the system returns upward to a plateau (Figure
30c). This data confirms that biotin-ELPs are not only sensitive to streptavidin
concentration, but that they respond differently to streptavidin below and above
stoichiometry. This observation is consistent with particle size distributions obtained using
light scattering (Figure 30e, Table 6). At a biotin-ELP to streptavidin ratio below
stoichiometry [16:1], the Rh of the crosslinked complex was larger than either free biotin-
ELP or streptavidin. This suggests that biotin-ELP is sensitive to crosslinks by small
amounts of streptavidin, which produces a drop in Tt. When approaching the
stoichiometric molar ratio of [4:1], a maximum particle size was observed, which is
104

consistent with the greatest extent of multimers yielding the lowest Tt. When biotin-ELPs
and streptavidin were mixed in a ratio above stoichiometry [1:1], the Rh decreased again,
which correlates with an increase in the Tt (Figure 30c). Together this data consistently
describes how multimeric complexation increases ELP density around a streptavidin core,
which decreases Tt, and leads to isothermal phase separation of these complexes.
ELPs are highly tunable protein-polymers that can be genetically designed to respond to
target concentrations across physiological temperatures. This proof of concept study
demonstrates how biotin-ELP was tuned to respond to streptavidin from 33.5 °C to 37 °C
by decreasing the ELP concentration from 5 to 1 µM. To accomplish this, we introduced
a new ELP called 2VA192, which was intentionally designed to phase separate in the
physiological range of 30-40 °C at concentrations from 1-10 µM (Figure 26b). To
modulate this detection range, ELPs with different lengths or guest residue compositions
can be synthesized to respond to targets at different concentrations or temperatures. For
instance, an ELP, V192 with only valine as guest residue (Xaa = Val, l = 192 pentamers)
might respond to streptavidin at 37 °C at concentrations lower than 1 µM since its
transition temperature is lower than 2VA192. Alternatively, an ELP, A192 with only
alanine as guest residue (Xaa = Ala, l = 192 pentamers) might respond to streptavidin at
37 °C at concentrations greater than 1 µM since its transition temperature is higher than
2VA192. Furthermore, ELPs with different lengths having the same guest residue
composition might also be designed to respond to targets at temperatures above or below
37 °C. Provided that both the relevant temperature and concentration of the target protein
is known, it should be possible to detect other protein targets under isothermal conditions
using this strategy.
105

4.6 Conclusion
Through non-covalent, reversible phase separation, ELPs both detect and respond to
target microenvironments; however, their targets have been mostly limited to ionic
species, pH, or heat. Since ELPs are also strongly responsive to molecular weight, there
remains an untapped potential to engineer them to respond to more specific biomolecular
cues, such as proteins. Building on our previous findings that ELPs can respond to a
small dimeric CID ligand, this chapter presents a rational strategy to engineer ELPs that
detect a high molecular weight multimeric protein. Using streptavidin as a model protein,
this chapter describes how biotin-ELPs behave as ‘smart polymers’ capable of phase
separation upon detection of their target, even at fixed temperature. Based on this proof-
of-concept study, it may become feasible to design ELPs into diagnostics and
therapeutics that respond to multimeric macromolecules such as antibodies, cytokines,
and tyrosine kinase receptors.

4.7 Acknowledgements
This work was made possible by the University of Southern California and the National
Institutes of Health R01GM114839 to J.A.M., the Translational Research Laboratory and
the Gavin Herbert Endowed Chair Pharmaceutical Sciences at the USC School of
Pharmacy, the USC Ming Hsieh Institute, the USC Whittier Foundation, USC Nano
Biophysics Core Facility and P30 CA014089 to the Norris Comprehensive Cancer Center.

106

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Creator Dhandhukia, Jugal P. (author)

Core Title Multivalent smart elastin-like polypeptide therapeutics with drug delivery and biosensing applications.

School School of Pharmacy

Degree Doctor of Philosophy

Degree Program Pharmaceutical Sciences

Publication Date 07/24/2017

Defense Date 06/15/2017

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag bioresponsive polymers,cancer drug delivery,crosslinking,elastin-like polypeptides,OAI-PMH Harvest,rapalogues

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Language English

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Advisor MacKay, Andrew (committee chair), Epstein, Alan (committee member), Okamoto, Curtis (committee member)

Creator Email dhandhuk@usc.edu,jugaldhandhukia@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c40-411955

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