Protein biologics are an important class of drugs, but the necessity for frequent parenteral administration is a major limitation. Drug-delivery materials offer a potential solution, but protein-material adsorption can cause denaturation, which reduces their effectiveness. Here, we describe a new protein delivery platform that limits direct contact between globular protein domains and material matrix, yet from a single subcutaneous administration can be tuned for long-term drug release. The strategy utilizes complementary electrostatic interactions made between a suite of designed interaction domains (IDs), installed onto the terminus of a protein of interest, and a negatively charged self-assembled fibrillar hydrogel. These intermolecular interactions can be easily modulated by choice of ID to control material interaction and desorption energies, which allows regulation of protein release kinetics to fit desired release profiles. Molecular dynamics studies provided a molecular-level understanding of the mechanisms that govern release and identified optimal binding zones on the gel fibrils that facilitate strong ID-material interactions, which are crucial for sustained release of protein. This delivery platform can be easily loaded with cargo, is shear-thin syringe implantable, provides improved protein stability, is capable of a diverse range of in vitro release rates, and most importantly, can accomplish long-term control over in vivo protein delivery.
Protein biologics are an important class of drugs, but the necessity for frequent parenteral administration is a major limitation. Drug-delivery materials offer a potential solution, but protein-material adsorption can cause denaturation, which reduces their effectiveness. Here, we describe a new protein delivery platform that limits direct contact between globular protein domains and material matrix, yet from a single subcutaneous administration can be tuned for long-term drug release. The strategy utilizes complementary electrostatic interactions made between a suite of designed interaction domains (IDs), installed onto the terminus of a protein of interest, and a negatively charged self-assembled fibrillar hydrogel. These intermolecular interactions can be easily modulated by choice of ID to control material interaction and desorption energies, which allows regulation of protein release kinetics to fit desired release profiles. Molecular dynamics studies provided a molecular-level understanding of the mechanisms that govern release and identified optimal binding zones on the gel fibrils that facilitate strong ID-material interactions, which are crucial for sustained release of protein. This delivery platform can be easily loaded with cargo, is shear-thin syringe implantable, provides improved protein stability, is capable of a diverse range of in vitro release rates, and most importantly, can accomplish long-term control over in vivo protein delivery.
Protein therapeutics
have become a significant source of new drugs
due to their high affinity and selectivity.[1] However, protein drugs cannot be taken orally and often require
frequent parenteral administration for optimal efficacy, both of which
can complicate treatment regimens. Thus, a delivery method that utilizes
a single administered dosage of drug with long-term release would
be a powerful clinical tool for improving treatment efficacy and patient
compliance. Many different materials-based protein delivery platforms
have been developed,[1−3] but various challenges remain that limit further
application.[4] For example, the formulation
process of encapsulating protein can lack precise control over the
amount of drug loaded, and undesirable interactions between proteins
and organic cosolvents, cross-linking agents, or the materials themselves
can lead to denaturation and/or immunogenicity.Hydrogels made
from either synthetic or natural polymers are promising
materials for improving protein delivery.[2,5] Their
aqueous interiors are often compatible with long-term protein encapsulation,
but significant material optimization is typically necessary to tune
the rate of drug release. One strategy to control delivery is to engineer
binding interactions between the protein and ligands displayed within
the gel matrix, where stronger interactions lead to slower rates of
release. Ligands such as nucleic acids, peptides, or other proteins
have been employed for these affinity-controlled systems.[6−14] However, since protein–ligand binding is often specific,
unique materials must be engineered to deliver each protein of interest.
The design of a general affinity-based platform that could be used
to deliver a larger array of proteins would have utility. In principle,
the primary interactions that govern protein–ligand binding,
such as H-bonding, hydrophobics, and electrostatics, could be used
to engineer such a system. From a design standpoint, electrostatic
interactions are attractive offering tunable affinity and plasticity
in their geometric requirements.[15−26] However, the folded conformations of many proteins are marginally
stable, and encapsulation of a charged protein into a material network
of opposite charge can cause nonspecific protein–matrix interactions
that results in protein aggregation or denaturation. Additionally,
engineering precise charge complementarity between the protein and
matrix can be challenging due to the varied distribution of charged
residues on protein surfaces and the heterogeneous spatial display
of charge within polymers.[27,28]Reported herein
is the design of an electrostatics-driven delivery
system that offers tunable release of proteins. This platform is comprised
of two components, a highly negatively charged fibrillar hydrogel
network and a family of designed positively charged interaction domains
(IDs) that can be fused to the termini of, in principle, any negatively
charged protein. The ID is responsible for sequestering the protein
to the gel fibrillar scaffold and controlling its eventual release.
Importantly, this strategy ensures that the globular domain of a gel-encapsulated
protein is noninteracting with the material matrix via charge repulsion,
and matrix binding is largely facilitated by the ID (Figure ). Furthermore, since the suite
of different IDs affords a high degree of control over release rates,
it eliminates the need for re-engineering the hydrogel for delivering
different proteins.
Figure 1
Controlling protein release
from a negatively charged peptide hydrogel
using a cationic interaction domain (ID).
Controlling protein release
from a negatively charged peptide hydrogel
using a cationic interaction domain (ID).
Results
and Discussion
Design of the Interaction Domains and Complement
Hydrogel Scaffold
The design of our delivery system was inspired
by the additive
nature of biomolecular electrostatic interactions that impact macromolecular
folding,[29,30] association,[31−33] and ultimate function.
Extensive biophysical studies in proteins demonstrated that salt bridges
can help stabilize the folded native state. The strength of these
interactions is dependent on both the type of residues involved and
their location within the protein.[30,34−36] With this in mind, we designed a family of interaction domains with
the potential to make a varying number of weak, medium, and strong
interactions with the fibers of the gel network to control release.
The general design of the ID utilizes a linear sequence (RH)R-(GGSGS)2- that contains a varying number
of (RH) repeats. The alternating sequence is designed to place all
of the guanidinium side chains of arginine on the same face of an
extended β-strand conformation to maximize potential interactions
with the gel’s β-sheet rich fibers (Figure ). Arginine was chosen to be
the driver of ID association to the fibers based on its high pKa and known ability to engage in multiple binding
orientations with carboxylates.[37] Histidine
was incorporated at the alternate position to aid solubilization,
as opposed to a noncharged hydrophobic residue which would result
in an amphiphilic sequence prone to aggregation. We also envisioned
that for the longer IDs, the histidines could act as an intrinsic
purification handle eliminating the need for a separate poly-histidine
domain. Lastly, IDs are appended to a protein of interest with a simple
glycine/serine linker. ID amino acid composition, sequence, and length
influence the type and strength of electrostatic interactions made
between the ID and fiber, which in turn, dictates protein release
kinetics.The hydrogel component of the delivery system is prepared
from AcVES3, a self-assembling peptide. AcVES3 contains strands of
alternating hydrophobic and hydrophilic residues that flank a central
tetrapeptide capable of promoting a type II’ β-turn (Figure , Table ). Sequences of this type are
known to assemble into highly homogeneous β-hairpin-rich fibers.[38−46] Hydrophilic residues are displayed on the solvent-exposed surface
of the fibers, while the hydrophobic residues are buried within the
core of a bilayer.[47] To test our hypothesis
that IDs can control protein release from the gel, we first designed
a library of enhanced green fluorescent protein (EGFP) analogues containing
different IDs at their N-termini (Table , Figure S1).
EGFP, which has the β-barrel structure found in all fluorescent
proteins, is an excellent model because its spectral properties allow
for easy quantification and assessment of activity.[48] Importantly, EGFP is negatively charged (pI ≈ 5.6)
and allows us to test one of our design principles, which asserts
that matching the electrostatic potential of a protein’s globular
domain with the gel scaffold should limit their direct interaction.
Table 1
Electrostatic Components for Proteins
and AcVES3
protein
basic A.A.
in ID
calc pI
EGFP
5.6
For EGFP/mRuby3,
N-Terminal IDn = G(RH)nR(GGSGS)2-
ID1-EGFP
2 Arg, 1 His
5.9
ID2-EGFP
3 Arg, 2 His
6.1
ID3-EGFP
4 Arg, 3 His
6.3
ID4-EGFP
5 Arg, 4 His
6.5
ID5-EGFP
6 Arg, 5 His
6.7
ID6-EGFP
7 Arg, 6 His
7.0
H6-EGFP
6 His
6.0
H12-EGFP
12 His
6.2
NH6-EGFP
3 Arg, 2 Lys, 6 His
6.3
mRuby3
5.8
ID5-mRuby3
6 Arg, 5 His
8.4
For
IFNα, C-Terminal IDn = -(SGSGG)2(RH)nR
IFNα
5.4
IFNα-ID3
4 Arg, 3 His
7.0
IFNα-ID5
6 Arg, 5 His
8.4
In Vitro Release of ID-EGFP from AcVES3 Hydrogel
The
library of EGFP analogues was generated by bacterial expression
(Figure S1) and AcVES3, used for hydrogelation,
was synthesized by solid phase peptide synthesis (Figures S2 and S3). The conformation of the peptide within
the empty gel is rich in β-sheet structure, as observed by CD,
and TEM indicates a highly homogeneous fibrous network (Figure S4). Precise amounts of protein can be
easily loaded directly into the AcVES3 gel network during hydrogel
formation with 100% efficiency (Video S1). This is in contrast to preformed gels that must be loaded by permeation.
Direct encapsulation of the ID proteins (∼1 mg/mL) does not
affect the rheological properties of the AcVES3 hydrogel, as time-sweep
measurements for ID-EGFP-loaded gels display shear-thin recovery properties
that are identical to gel alone (Figures A and S5). The
unaltered behavior of the material is further exemplified by the consistency
of the storage moduli before and after shear-thinning across the different
protein-loaded gels (Figure B), similar kinetics of gel formation at early time points
(Figure S5), and the observance of similar
fibers by TEM (Figure S4). We also assessed
the rheological behavior at higher protein concentrations (3 and 5
mg/mL) and observed similar shear-thin recovery properties (Figure S5). Since the IDs do not affect peptide
self-assembly or hydrogelation under these conditions, we postulate
that the electrostatic interactions between the ID and material must
be formed later in the assembly process, after a highly charged fiber
surface is generated. The ability of the protein-loaded gels to form
rigid materials and reheal after shearing is important because it
demonstrates that they can be administered by syringe injection for
in vivo delivery.
Figure 2
Shear-thin recovery properties of AcVES3 hydrogels with
and without
protein. (A) Comparison of time-sweep experiments for empty hydrogel
and ID5-EGFP-containing gel. Other ID-EGFP analogues behave in a similar
manner, as shown in Figure S5. (B) Storage
modulus of gels containing protein before and after (bars outlined
with black) shearing compared to empty hydrogel.
Shear-thin recovery properties of AcVES3 hydrogels with
and without
protein. (A) Comparison of time-sweep experiments for empty hydrogel
and ID5-EGFP-containing gel. Other ID-EGFP analogues behave in a similar
manner, as shown in Figure S5. (B) Storage
modulus of gels containing protein before and after (bars outlined
with black) shearing compared to empty hydrogel.We then showed that the IDs could achieve a diverse range of in
vitro release profiles (Figure A). As expected, unmodified EGFP, which is negatively charged,
undergoes burst release within 2 days from the like-charged gel network.
ID1-EGFP is released at a rate similar to EGFP, with ID2-EGFP showing
only a modest increase in retention. In contrast, the ID3–6
analogues offer excellent prolonged control over release. After 36
days, ∼50% of ID3-EGFP was released, whereas only about 5%
of ID6-EGFP had been released. Intermediate amounts (∼20%)
of ID4- and ID5-EGFP are released over the same time period. Further,
experiments performed in the presence of a high concentration of salt
greatly expedited release indicating that electrostatics is the primary
interaction governing matrix binding and release (Figure S6). The slow release at longer times (>2 weeks)
for
ID3–6 might be due to ID proteins located deep within the gel
undergoing multiple desorption and resorption events en route to exiting
the matrix.
Figure 3
Release of EGFP versus analogues containing (A) IDs and (B) control
domains.
Release of EGFP versus analogues containing (A) IDs and (B) control
domains.In addition to studying the ID-appended
proteins, we also investigated
the release of EGFP-containing control domains to confirm that amino
acid composition and local sequence arrangement of ID residues are
important design determinants for release (Table and Figure S1). Controls H6 and H12 contain 6 and 12 histidine
residues, respectively, appended to the N-terminus of EGFP. The NH6
control domain originates from a common fusion used in protein expression,
which contains a variety of basic residues distributed throughout
its sequence. While the IDs afforded a range of release rates, the
polyhistidine controls offered little ability to retain protein within
the material (Figure B). This demonstrates the importance of arginine within the ID design
and suggests that charge alone is not sufficient for controlling release.
In fact, if charge content was the only defining factor controlling
release rates, then the isoelectric point (pI) of any N-terminally
modified protein should be an absolute predictor for release rates.
Although there is good correlation within the ID1–6 family,
the release profiles of ID3-EGFP and the NH6-EGFP control are quite
different, despite having similar pIs (∼6.3). The control data
also show that ID length is not a sole determinant of release behavior.
The H12-fusion offers no control over EGFP release compared
to ID5, despite having the same number of residues outside their linker
domains. These results indicate that in addition to charge content
and length, the composition and sequential arrangement of residues
within the ID are important design factors.Proteins released
from the gel retain their activity. Fluorescence
spectra of the ID-EFGPs before gel encapsulation and after gel release
were identical (Figure S7). Further, qualitative
evidence of active protein remaining in the materials is demonstrated
by the visual examination of the gels over time (Figure S8). Conversely, EGFP encapsulated into cationic peptide
hydrogels led to weak, brittle gels, suggesting that the oppositely
charged EGFP interferes with peptide self-assembly (Figure S9). Furthermore, the EGFP that is released is denatured
and displays attenuated fluorescence. This highlights the delicate
nature of protein encapsulation and that denaturation can be mitigated
through the installation of an ID.
Fine-Tuning Release and
Time-Staggered Delivery
As
shown in Figure A,
there is a significant gap between the release profiles of ID2- and
ID3-EGFP. This region of delivery space can be accessed using combinations
of different IDs within the family. The expected release of protein
can be determined by fitting each of the release curves in Figure A to a first-order
kinetics model, then performing linear combinations of the fitted
data. To address this previously neglected delivery profile, the release
curves for ID2- and ID3-EGFP were fit and linearly combined at a ratio
of 4:6 (ID2-EGFP/ID3-EGFP, Figure A). The predicted protein release behavior closely
matched the experimental release data. Although this is only a simple
test case, more complex combinations should be readily possible.
Figure 4
(A) Release
profiles for mixtures of EGFP containing different
interaction domains can be predicted, as shown with a 4:6 ratio of
ID2-EGFP/ID3-EGFP. First, release data for each pure ID protein was
fit to first-order kinetics (dashed pink and red lines), obtained
by numerically integrating the equation [Pu] = k1 [Pb] –k–1 [Pu], where t is time, Pu is unbound protein,
Pb is bound protein, and k1 and k–1 are adsorption/desorption
rate constants. Fits are linearly combined to predict the release
of the mixed system (black dashed line), which agrees well with the
experimental data (black circle). (B) Co-encapsulation and staggered
release of distinct proteins.
(A) Release
profiles for mixtures of EGFP containing different
interaction domains can be predicted, as shown with a 4:6 ratio of
ID2-EGFP/ID3-EGFP. First, release data for each pure ID protein was
fit to first-order kinetics (dashed pink and red lines), obtained
by numerically integrating the equation [Pu] = k1 [Pb] –k–1 [Pu], where t is time, Pu is unbound protein,
Pb is bound protein, and k1 and k–1 are adsorption/desorption
rate constants. Fits are linearly combined to predict the release
of the mixed system (black dashed line), which agrees well with the
experimental data (black circle). (B) Co-encapsulation and staggered
release of distinct proteins.In addition to fine-tuning the release of one specific protein
of interest, our system can also be used to stagger the release of
multiple proteins. Combination therapies can significantly improve
treatment outcomes, with sequential delivery of different drugs often
leading to improved efficacy over monotherapy or simultaneous codelivery.[49−52] To model this treatment paradigm, we generated ID5-mRuby3, the ID5
variant of the monomeric red fluorescent protein mRuby3 (Table , Figure S1)[53] and coencapsulated
it into an AcVES3 hydrogel with EGFP. These fluorescent proteins have
a difference in absorbance wavelength maxima of 70 nm, allowing for
their precise concentration determination within the same sample. Figure B shows that independent
control over the release of multiple proteins from a single gel is
possible. EGFP was released within several days, followed by slow
sustained delivery of the ID5-containing protein. This staggered release
is shown qualitatively in Figure S10 through
the visual monitoring of fluorescence over time.
Installing
IDs onto the C-Terminus of Interferon-α for
Controlled Cytokine Delivery
After demonstrating control
over the release of model fluorescent proteins, we sought to expand
the utility of the ID delivery platform toward the release of a clinically
relevant protein, interferon-α (IFNα). Type I interferons,
including IFNα, are important cytokines that are involved in
the innate immune response and have been used for the treatment of
viral infections and as cancer immunotherapies.[54−56] IFNα
is negatively charged (pI ≈ 5.4) similar to EGFP and mRuby3,
which should lead to fast release of the unmodified protein from the
negatively charged AcVES3 gel. Unlike the fluorescent proteins, however,
IFNα is α-helical and contains multiple intramolecular
disulfide bonds. We designed the IFNα analogues with the IDs
at the C-terminus (Table ), to further test the generality of ID placement. Since protein
termini can be involved in binding interactions, having flexibility
with respect to ID location is crucial. Also, putting the ID at the
C-terminus opens the possibility that this strategy can be applied
to proteins that utilize N-terminal signal peptides for secretory
or protein folding purposes during the expression and maturation process.ID proteins were cloned into the pPAL7 vector containing IFNα.[57] After expression, proteins were purified/cleaved
using Profinity eXact resin (Figure S11). As mentioned earlier, the longer IDs might be useful purification
handles. As a proof of concept, IFNα-ID5 was first purified
to homogeneity by metal affinity utilizing the ID domain prior to
incubation with the eXact resin (Figure S11). This showcases the potential dual functionality of this domain
to both control release and act as an intrinsic purification handle.
Once purified, CD experiments were performed that showed that the
ID does not interfere with the protein’s helical structure
(Figure S12). We then performed concentration-dependent
studies of IFNα and the ID analogues in the presence of HL116
cells.[57] When stimulated with IFNα,
HL116 expresses luciferase that can report on protein activity levels.[58] Importantly, the IFNα-ID proteins had
similar picomolar activity as the native IFNα, indicating
that the ID does not hinder binding to the IFNα receptor and
activation of cell-signaling pathways (Figure A). In vitro release experiments show that
the IDs can effectively control delivery of IFNα (Figure B). As seen with the EGFP studies,
the unmodified IFNα was mostly released within a few days, while
IFNα-ID5 had a much slower release (<20% after 2 weeks).
IFNα-ID3 offered intermediate release to unmodified and ID5-functionalized
protein as expected. IFNα-ID protein released from the gel retained
its ability to stimulate HL116 cells (Figure C). These results further validate the capability
of IDs to modulate protein release and demonstrate that they can be
used for proteins of different structure (α-helical or β-sheet)
when incorporated at either protein termini. Although we anticipate
that the IDs will be compatible with many negatively charged proteins,
there will certainly be outliers.
Figure 5
(A) Dose response for HL116 cell stimulation
for IFNα and
two ID analogues. (B) Release profiles of IFNα and its analogues.
(C) HL116 stimulation activity of released IFNα-ID5 compared
to soluble IFNα (500 pM) and empty gel (no lum = no luminescence).
(A) Dose response for HL116 cell stimulation
for IFNα and
two ID analogues. (B) Release profiles of IFNα and its analogues.
(C) HL116 stimulation activity of released IFNα-ID5 compared
to soluble IFNα (500 pM) and empty gel (no lum = no luminescence).
Molecular-Level Insight into ID Binding,
Mobility, and Release
The release data suggest that ID composition,
sequence, and length
influence release kinetics. To gain molecular-level insight into how
the IDs physically engage the hydrogel’s fibrils, which affects
binding and subsequent release, molecular dynamics (MD) simulations
were performed. AcVES3 assembles into fibrils with two opposing hydrophilic
faces, each containing distinct strips of glutamate-derived negative
charge that traverse the fibril long axis (Figure S13). Microsecond simulations performed for each ID show that
these charged strips on the fiber are the main orchestrators of the
ID–fibril interaction. As designed, simulations suggest that
the IDs bind to the fibrils in an extended conformation to maximize
the electrostatic interactions between the arginine and glutamate
residues. Conversely, when ID6 was forced to bind a fibril in a nonextended
compact conformation, the calculated interaction energy was more than
35 kcal/mol less favorable than the extended conformation (Figure S14).[59,60] Interaction
energies were determined for the entire family of IDs and showed that
the longer IDs have greater binding potentials (Figure A). Interestingly, the interaction energies
are much greater than what might be expected for typical electrostatic
interactions in proteins (normally on the order of single digit kcal/mol)[29,30] and are more comparable to the energies observed for the complexation
of oppositely charged peptide homopolymers.[61,62] Additional experiments were performed to assess ID mobility once
bound to the fibril. Here, an opposing force to ID binding was applied
to mimic the induced repulsion between an appended negatively charged
protein and the like-charged fiber. These simulations show that shorter
IDs were much more mobile (Figure B). Video S2 shows the dynamics
of ID1 versus ID6 over 100 ns, with the shorter ID being more conformationally
flexible and traveling a longer distance along the fiber. Here, the
mobility was also quantitated by measuring the displacement of the
IDs’ center of mass relative to its initial docking site as
a function of time (Figure C). Figure D shows snapshots of the two IDs from Video S2 before and after the simulation; ID6 remains more centrally bound
to the fibril’s high-density charged regions, as compared to
ID1. To assess the energetic requirements for ID desorption from the
gel matrix, the release curves for the ID-EGFP analogues (Figure A) were analyzed
to derive activation energies using the Arrhenius rate law (Figure E). The longer IDs
required more energy for protein release, and the observed trend shows
an inverse correlation to the calculated interaction energies for
ID binding (Figure A).
Figure 6
(A) Computationally determined interaction energies for IDs. (B)
Rate of movement for IDs during simulations. (C) Change in the center
of mass and (D) visual snapshots before and after 100 ns simulation
for ID1 and ID6, demonstrating differences in mobility. (E) Calculated
desorption energies for ID-EGFP determined by fitting the Arrhenius
rate law (k = Ae(−) to the release
curves in Figure A,
where k is the rate constant, A is
the Arrhenius pre-exponential factor, Ea is the activation (desorption) energy, R is the
gas constant, and T is the temperature.
(A) Computationally determined interaction energies for IDs. (B)
Rate of movement for IDs during simulations. (C) Change in the center
of mass and (D) visual snapshots before and after 100 ns simulation
for ID1 and ID6, demonstrating differences in mobility. (E) Calculated
desorption energies for ID-EGFP determined by fitting the Arrhenius
rate law (k = Ae(−) to the release
curves in Figure A,
where k is the rate constant, A is
the Arrhenius pre-exponential factor, Ea is the activation (desorption) energy, R is the
gas constant, and T is the temperature.Further analysis of the MD trajectories indicates that a
substantial
variety of interactions are made between the ID arginines and the
glutamate side chains of the fiber, ranging from weak transient interactions
to strong multidentate interactions that firmly anchor the ID onto
the fiber. These binding interactions were assigned into one of three
groups, namely, weak (type I), intermediate (type II), and strong
(type III). This was accomplished across all ID family members by
dividing each of their respective 100 ns trajectories into 5 ns sections
and then computing the interaction energy for all of the arginine
residues within that time frame. All arginine–glutamate intermolecular
contacts <5.0 Å were binned into their respective types (I,
II, or III) based on their computed energy. Within each type, the
mobility of each arginine residue was determined, as well as the average
number of glutamate side chains the arginine guanidinium group could
make contact with during the simulation. Arginine residues that made
weak interactions (type I) had an average interaction energy of −2.8
kcal/mol, traveled the greatest distance over the course of the simulation
period (>4 Å), and were bound to at most one glutamate (on
average
0.50). The intermediate interactions (type II) had more favorable
binding energies (−6.2 kcal/mol), which were less mobile (traveled
∼3.3 Å) and could make contacts with at least one glutamate
(average 0.98). The strongest contacts (type III) had an average interaction
energy of −12 kcal/mol, which is roughly on par with the energetics
of poly-arginine/poly-glutamate scaffolds reported previously.[61] Type III arginine residues migrated very little
during the simulation (<3 Å) and made contacts with multiple
glutamates at a given time (average 1.56). Various molecular binding
geometries were observed within each type; Figure A shows examples based on the statistics
compiled from the simulations.
Figure 7
Molecular insight into the ID and fiber
interaction. (A) Potential
binding modes of arginine, classified as type I, II, or III. (B) Histogram
showing the probability of forming a second arginine type III interaction
as a function of sequential position when an existing type III interaction
is made at position i. (C) Graphical representation
of an ID binding to a fiber containing four repeat units of a self-assembled
AcVES3 peptide. The right-most panel contains the entire sequence
of AcVES3. The ID shown at top contains the minimal sequence necessary
to make type III interactions with arginine located at positions i, and i + 6.
Molecular insight into the ID and fiber
interaction. (A) Potential
binding modes of arginine, classified as type I, II, or III. (B) Histogram
showing the probability of forming a second arginine type III interaction
as a function of sequential position when an existing type III interaction
is made at position i. (C) Graphical representation
of an ID binding to a fiber containing four repeat units of a self-assembled
AcVES3 peptide. The right-most panel contains the entire sequence
of AcVES3. The ID shown at top contains the minimal sequence necessary
to make type III interactions with arginine located at positions i, and i + 6.We next investigated whether a particular ID could make multiple
type III interactions, and if so, we sought to determine whether there
was a positional dependence of arginine residues that allowed for
multiple interactions. Figure B shows the probability of finding an arginine engaged in
a type III interaction (i + n) residues away from
an arginine at sequence position (i) that is also
engaged in a type III interaction. The data indicate that arginine
residues occupying (i, i + 6) sequential
arrangements are more likely to engage in simultaneous type III interactions.
Having discovered this positional dependence within the ID, we turned
our attention to the model of the fibril to search for repetitive
complementary glutamate-based motifs that could support the formation
of multiple type III interactions. Each face of a given hydrogel fibril
contains two strips of negative charge resulting from the solvent-exposed
glutamate side chains (Figure S13). This
molecular arrangement is depicted in the cartoon shown in Figure C. Optimal binding
zones were identified every 5 Å along one of the charged strips,
where each zone contains three proximal glutamates. The greater density
of glutamate residues here increases the probability of the ID forming
type III interactions. Within the ID, the average measured distance
between the Cα carbons of two bound (i, i + 6) arginine residues engaged in a type III interaction
and the distance between two binding zones along the fiber are both
∼20 Å. Alternative arrangements of arginine residues within
the ID are less capable of binding to optimal zones simultaneously.
For example, arginines at (i, i + 2) positions are 6.8 Å apart, a distance that does not fully
complement the 5 Å repeat between zones. The importance of the
(i, i + 6) arrangement is exemplified
by the observed change in ID release behavior transitioning from ID2
to ID3 (Figures A
and 6A,E). ID2 shows almost no ability to control
release as compared to ID3, with the latter being the first interaction
domain in the series capable of displaying arginine side chains in
an (i, i + 6) arrangement. In addition
to making more interactions of all types, the domains beyond ID3 have
an increased probability of forming pairs of type III interactions.
Thus, the collective assessment of ID behavior through experimental
release and computational analysis suggests ID–gel interaction
energies, ID motility, and activation energies for ID desorption all
regulate the release of protein.
Control over in Vivo Protein
Release Using IDs
Finally,
we used our system to locally deliver protein in vivo with temporal
control, using mRuby3 as a model. At the outset, we acknowledged that
a peptide hydrogel containing l-amino acids will be digested
by secreted proteases and phagocytosed by macrophages in subcutaneous
tissue, both of which would reduce the overall delivery lifetime of
the material. In an effort to hinder these processes, we conducted
in vivo experiments using hydrogels consisting of either AcVES3 (also
termed l-AcVES3) or its enantiomer d-AcVES3 (Figure S3). We hypothesized that the D-gel, which
contains mainly d-amino acids, would be more proteolytically
stable than l-AcVES3 and would prolong the protein delivery
period. The L- and D-gels form similar fibrous nanostructures with
identical mechanical properties (Figures S4 and S5), and we observe the same in vitro release profiles with
the mRuby3 analogues (Figure S15). This
suggests that release is dictated by the general arrangement of charge
displayed on the gel fibers, not by side chain stereochemistry. Therefore,
any observed differences in release rates in vivo should be attributed
to differences in peptide gel stability.In the first set of
in vivo experiments, mice were injected with l-AcVES3 gel
containing either mRuby3 or ID5-mRuby3 in their left and right dorsal
flanks, respectively (Figures A and S16A). mRuby3 was rapidly
released within 1 day, and ID5-mRuby3 was largely retained within
the material, indicating the ID was effective in slowing protein release.
Analogous experiments comparing release of the mRuby3 analogues using d-AcVES3 hydrogels produced the same results (Figure S16B). Next, mice were injected on their left and right
dorsal flanks with ID5-mRuby3 encapsulated in either l-AcVES3
or d-AcVES3 gels, respectively, and release was measured
over 28 days (Figures B and S16C). Release from the l-AcVES3 gel occurred over 10–14 days, demonstrating that the
ID can enable extended release of protein, while release from the d-AcVES3 gel was sustained through 21 days. Four of the five
mice had detectable levels of ID5-mRuby3 in the d-AcVES3
gel after 28 days (Figure S16C). These
results demonstrate the ID operates within an in vivo setting, and
that the stereochemical character of the gel can enhance the delivery
lifetime. To investigate whether biodegradation of the hydrogel material
was indeed responsible for longer delivery, histology was conducted
on the tissue surrounding both left and right flank injection sites.
The left flank tissue shows subcutaneous macrophage infiltration (for
which the nuclei are stained purple) and the absence of the L-gel
(Figure C). In contrast,
the right flank tissue shows remaining D-gel surrounded by macrophages,
presumably still working to clear the material through phagocytosis
(Figure D). As shown
in Figure B, after
28 days the right flank tissue was still fluorescent, which signifies
the presence of ID5-mRuby3 within the remaining gel. The current limiting
factor for in vivo delivery using our ID-system is thus the clearance
of AcVES3 gel, not the release kinetics of the ID, and we are currently
exploring approaches to further extend the material’s lifetime.
Nonetheless, the ID delivery approach has the potential to release
protein over the course of 3 weeks from a single administration, a
marked improvement over the often-daily parenteral administration
typically needed for protein drugs.
Figure 8
(A) In vivo comparison of mRuby3 and ID5-mRuby3
released from l-AcVES3 hydrogels. (B) Comparison of l-AcVES3 and d-AcVES3 hydrogels for ID5-mRuby3 release. (C)
Histological
analysis of injection site subcutis for l-AcVES3 and (D) d-AcVES3 for the mouse in panel (B) at 28 days post injection.
Engorged macrophages are present throughout the injection site for l-AcVES3 gel with complete clearance of the material, whereas
significant amounts of d-AcVES3 gel remained (marked by *)
with macrophages at the periphery. Scale bars = 100 μm.
(A) In vivo comparison of mRuby3 and ID5-mRuby3
released from l-AcVES3 hydrogels. (B) Comparison of l-AcVES3 and d-AcVES3 hydrogels for ID5-mRuby3 release. (C)
Histological
analysis of injection site subcutis for l-AcVES3 and (D) d-AcVES3 for the mouse in panel (B) at 28 days post injection.
Engorged macrophages are present throughout the injection site for l-AcVES3 gel with complete clearance of the material, whereas
significant amounts of d-AcVES3 gel remained (marked by *)
with macrophages at the periphery. Scale bars = 100 μm.
Conclusions
We have developed a
modular strategy to control protein release
from a biocompatible peptide hydrogel that mitigates gel-based protein
denaturation and the need for gel re-engineering for delivering different
proteins of interest. A suite of IDs for controlling release was designed
for convenient incorporation at either termini of proteins during
expression. Individual or combinations of different IDs can be used
to finely tune the release profiles for a given protein. Furthermore,
our system also allows for the time-staggered delivery of different
proteins, which should be beneficial in drug combination regimens.
The presence of the IDs did not alter the material properties of the
hydrogel nor did they affect the structural or functional properties
of the proteins examined in this study. MD simulations afforded molecular-level
insight into the behavior of the ID–gel interaction, which
helped elucidate the mechanism that dictates sustained protein release.
Simulations also suggest opportunities for future ID design to further
fine-tune delivery. Most importantly, the ID delivery approach was
validated in vivo, with sustained release of protein for over 3 weeks
using a hydrogel composed of mainly d-amino acids. This platform
represents a promising strategy to deliver negatively charged proteins
and complements existing affinity-controlled delivery methods.
Authors: Vivek A Kumar; Nichole L Taylor; Siyu Shi; Navindee C Wickremasinghe; Rena N D'Souza; Jeffrey D Hartgerink Journal: Biomaterials Date: 2015-02-21 Impact factor: 12.479
Authors: Aaron D Robison; Simou Sun; Matthew F Poyton; Gregory A Johnson; Jean-Philippe Pellois; Pavel Jungwirth; Mario Vazdar; Paul S Cremer Journal: J Phys Chem B Date: 2016-08-29 Impact factor: 2.991
Authors: Bryce T Bajar; Emily S Wang; Amy J Lam; Bongjae B Kim; Conor L Jacobs; Elizabeth S Howe; Michael W Davidson; Michael Z Lin; Jun Chu Journal: Sci Rep Date: 2016-02-16 Impact factor: 4.379
Authors: Poulami Majumder; Yichuan Zhang; Marcos Iglesias; Lixin Fan; James A Kelley; Caroline Andrews; Nimit Patel; Jason R Stagno; Byoung Chol Oh; Georg J Furtmüller; Christopher C Lai; Yun-Xing Wang; Gerald Brandacher; Giorgio Raimondi; Joel P Schneider Journal: Small Date: 2020-08-18 Impact factor: 15.153