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. 2024 Feb 20;35(3):300–311. doi: 10.1021/acs.bioconjchem.3c00454

Synthetic and Computational Design Insights toward Mimicking Protein Binding of Phosphate

Whitney C Fowler †, Chuting Deng †, O Therese Teodoro †, Juan J de Pablo †,‡,*, Matthew V Tirrell †,‡,*
PMCID: PMC10962344  PMID: 38377539

Abstract

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The unique and precise capabilities of proteins are renowned for their specificity and range of application. Effective mimicking of protein-binding offers enticing potential to direct their abilities toward useful applications, but it is nevertheless quite difficult to realize this characteristic of protein behavior in a synthetic material. Here, we design, synthesize, and evaluate experimentally and computationally a series of multicomponent phosphate-binding peptide amphiphile micelles to derive design insights into how protein binding behavior translates to synthetic materials. By inserting the Walker A P-loop binding motif into this peptide synthetic material, we successfully implemented the protein-binding design parameters of hydrogen-bonding and electrostatic interaction to bind phosphate completely and selectively in this highly tunable synthetic platform. Moreover, in this densely arrayed peptide environment, we use molecular dynamics simulations to identify an intriguing mechanistic shift of binding that is inaccessible in traditional proteins, introducing two corresponding new design elements—flexibility and minimization of the loss of entropy due to ion binding, in protein-analogous synthetic materials. We then translate these new design factors to de novo peptide sequences that bind phosphate independent of protein-extracted sequence or conformation. Overall, this work reveals that traditional complex conformational restrictions of binding by proteins can be replaced and repurposed in a multicomponent peptide amphiphile synthetic material, opening up opportunities for future enhanced protein-inspired design.

Introduction

Proteins perform remarkable functions using highly sophisticated molecular interactions and conformations, inspiring attempts to realize their functionality in tunable synthetic materials1−3 for applications such as targeted drug delivery,4 biomimetic scaffolding,5−7 or reclamation and purification efforts.8,9 However, adequately translating protein binding to its synthetic counterparts is highly nontrivial. To date, various synthetic designs have been engineered to recapture protein binding potential, including employing peptides1,3,4,9−11 or peptoids,8,12 utilizing unconjugated binding motifs13−15 or tethering them to a larger construct,7,9,10 and either extracting a preidentified protein-binding motif15,16 or identifying a new motif through combinatorial12 or computational13,17 screening. Nevertheless, further study of synthetic binding mechanisms is merited so that future evolutions of materials can more fully realize proteins’ sophisticated specificity and performance.

To study how to design a protein-inspired synthetic material that preserves critical binding abilities, both a well-characterized protein-binding motif and a strategic material platform must be chosen. The Walker A P-loop motif18,19 is an apt choice for the former for several reasons. First, it is a simplified motif: its sequence is GXXXXGK(S,T), where X is any amino acid, and its binding interactions largely depend on an isolated sequence and a localized conformation rather than a complex tertiary structure, simplifying synthetic mimicry. Second, its native binding mechanism within phosphate-binding proteins (PBPs) has been highly characterized over decades of research.13−15,18,20,21 The P-loop binds to phosphate through three factors—adopting a nested cavity conformation,22−24 stabilizing phosphate through hydrogen bonds in the amide backbone, and utilizing a positively charged amino acid (AA) residue. This well-established understanding of binding in its native state will allow one to directly compare which binding mechanisms are adequately translated and which become altered. Third, there have been preliminary synthetic studies verifying that its phosphate binding capabilities can be retained outside of the protein.14−16 Lastly, if the P-loop is properly translated to a synthetic platform, it could have intriguing applications in resource recovery,25,26 phosphate sensing,27 or medical treatment of diseases corresponding to excess phosphate concentration in the blood.28

This P-loop binding motif can be readily translated into a strategic material framework. One promising synthetic construct, peptide amphiphile (PA) micelles or “protein-analogous” micelles (PAMs),29 is especially well-suited for a rational protein-mimicry mechanistic study. PAs consist of a peptide conjugated to a hydrophobic tail that spontaneously self-assembles in water, displaying the peptide binding motif in precise concentration to target ligands. Importantly, PAs are highly tunable in key protein-mimicking design components: precise AA control is achieved through sequence-specific synthesis,30,31 their supramolecular assembly architecture29 and composition32,33 is tuned through programmable intermolecular interactions of multiple components, and their secondary structure within the peptide “headgroup” can be tailored through well-studied design principles of peptide interaction.34−36 PA micelles have recently been designed that use AA sequences extracted from proteins to bind to phosphate selectively over nitrate and nitrite for multiple cycles,37 showcasing the translatable nature of protein binding to this platform. This ability has also been demonstrated in PAs that target monoclonal antibodies using specific protein-derived AA sequences.38 In addition to its promise as a useful material for targeted molecular binding, we can also learn from this micelle system how a binding mechanism of proteins is altered when rationally translated into a synthetic material.

To realize protein functionality in synthetic materials, we must first understand how binding functionality translates and then use that information to optimize the synthetic design. In this work, we evaluated a series of rationally designed multicomponent PA micelles to (1) identify binding mechanistic shifts that occur from a single phosphate-binding peptide to a dense array of phosphate-binding peptides assembled in a micelle, (2) distill our findings into generalized design principles, and (3) translate the design principles toward de novo design of phosphate-binding peptides. By employing complementary experimental and molecular dynamics simulation methods, we uncover new binding contributors unique to synthetic material platforms that overcome the limitations of complex tertiary and quaternary conformations required for traditional in situ protein binding. Overall, this work redefines essential features required to translate protein functionality into a deployable material, motivating optimized protein-mimicking design in future synthetic materials in PA micelles and beyond.39

Results and Discussion

Peptide Amphiphile Design Scheme

To mimic protein binding adequately in synthetic PA micelles, one must first review the mechanism that proteins employ in their native state to determine which features must be replicated in the synthetic construct. Over decades of study, proteins of vastly different sizes and functions have been found to specifically and reversibly bind using three complementary contributors: hydrogen bonds (H-bonds), electrostatic charge stabilization, and the formation of a localized secondary structure. In the Walker A P-loop in phosphate-binding proteins (PBPs), NH and OH H-bonds along the backbone of an AA sequence play essential roles in binding various forms of phosphate.40,41 Since the positioning of H-bonds is reliant on a delicate trivariate balance of covalent, electrostatic, and van der Waals interactions, slight changes in the AA sequence or the secondary structure of a protein or peptide can significantly alter its binding behavior and even its physiochemical properties.42 Cooperating in tandem with H-bonds, the presence of positively charged AAs—particularly arginine, with the guanidinium group and lysine—have been observed in many proteins as especially crucial for anion capture in contexts where limited H-bond stabilization is available from other residuals.43−45 Lastly, the P-loop employs the secondary structure of a compound LRLR nest to bind phosphate. L and R correspond to predetermined dihedral backbone angles, and a single LR “nest” consists of three NH groups in a peptide backbone oriented to create a cavity that binds negatively charged ligands.24,45,46 Many small polypeptide AA sequences have been shown to form similar H-bond nest formations when extracted from larger proteins,24 revealing their predisposition toward adopting this conformation even when isolated from their native environment. Harnessing these insights, in our previous work47 we successfully mimicked protein-binding of phosphate using PA micelles by employing a LRLR-nested P-Loop motif, Ser-Gly-Ala-Gly-Lys-Thr, extracted from ATP-binding proteins. However, the relative impact of each of these three contributors has not been explored, limiting possible design insights.

Here, a series of multicomponent peptide amphiphile micelles were designed (Figure 1) to isolate the relative contributions of conformation, hydrogen bonding, and electrostatic attraction on peptide binding of phosphate in a PA micelle, utilizing a dual experimental and computational approach. This rational design was informed by a key insight derived from our previous work, namely, that the phosphate ions were stabilized through hydrogen bonding and electrostatic attraction from multiple peptide chains in the micelle corona, reminiscent of tertiary binding.37 However, in this high-density environment of the peptide micelle corona, the peptide binding motifs were hypothesized to be conformationally constrained and the protein-derived LRLR nested cavity conformation could be inhibited.

Figure 1.

Figure 1

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(A) Molecular structures of the Filler PA (50 Å) and the Binding PA (75 Å) that feature three building block regions, which spontaneously coassemble into a micelle in water due to the hydrophobic effect. (B) Cryo-TEM images of the four PA systems with varying ratios of Filler PA to Binding PA, colisted with the Filler PA percent composition, which reveal extended wormlike micelles for all systems.

We aimed to enable the formation of the nested cavity conformation in the micelle system by sequentially decreasing the density of the peptide binding motifs in the micelle corona, making the motifs less conformationally constrained. We hypothesized that increasing the conformational freedom of the phosphate-binding motifs would further optimize phosphate binding, allowing the protein-analogous micelle to more closely mimic the nested conformation characteristic of P-loop binding.

Multicomponent PA systems are well poised to evaluate this. The peptide density can be precisely tuned by spontaneous coassembly of a Binding PA and a Filler PA into multicomponent supramolecular structures at predetermined compositions. Here, we designed a series of four PA micelle systems using both components, with the composition of Binding PA sequentially reduced by half from 100% to 50% to 25%. A pure Filler PA system was also evaluated as a control for non-sequence-specific binding. A similar design scheme was used by Cui and co-workers. They designed a two-component PA micelle to bind to monoclonal antibodies, and they found that decreased composition of the binding moiety corresponded to increased antibody capture.48

Each PA was designed with tunable “building block” regions with individualized function.31,49 The Binding PA, denoted C16G5hex (Figure 1A), is derived from the prototype phosphate-binding PA micelle with a nearly identical design.50 Region 1 is a hydrophobic tail required to facilitate self-assembly. Region 2 is a five-glycine spacer region that promotes wormlike micelle formation,51 which is the desired micelle architecture to create an entangled network of PA micelles to capture and release phosphate. The number of glycine residues was increased from three to five in this study to further extend the binding motif into the environment and access greater conformational freedom as well as increase the solubility of the Filler PA counterpart. Region 3 is the protein-derived P-loop hexapeptide binding moiety, SGAGKT, that has previously been shown to bind phosphate.50,52,53 The Filler PA, denoted C16G5K, has identical Regions 1 and 2 to ensure that it homogeneously coassembles with C16G5hex. The binding moiety in Region 3 is substituted with a lysine residue, which was required for solubility.

We synthesized the PAs using FMOC solid phase synthesis and purified them to greater than 95% purity (Figure S2). All PAs were confirmed to self-assemble into wormlike micelles using cryogenic transmission electron microscopy (cryo-TEM) imaging (Figure 1B–E) with similar dimensions, which will allow for a direct comparison between systems.

Experimental Phosphate-Binding Results by Multicomponent Peptide Amphiphile Micelles

The phosphate-binding abilities of the multicomponent PA micelles were evaluated at key conditions derived from our previous study. In that work, phosphate was nearly completely bound at pH 6 and a molar ratio of 3:1 PA:PO, with simulations revealing that two to three PA chains were always required to bind. In our re-engineered multicomponent design, we wanted to determine if we could achieve higher binding at lower ratios of Binding PA to PO4 if the nested cavity conformation was employed, which would also provide further insight into binding mechanisms. Thus, we evaluated phosphate binding at pH 6 at ratios of 1:1, 2:1, and 4:1 PA:PO4. Here the PA is total PA, rather than Binding PA, to keep the PA concentration constant across all systems tested. These ratios nicely complement the Binding PA multicomponent compositions and would easily facilitate a direct per-molecule binding analysis. For example, a 4:1 PA:PO4 ratio for the 3:1 Filler:Binding system would have a 1:1 ratio of binding motif to phosphate. In our previous work, we also described how phosphate-binding in the micelle at high pH was restricted due to a “squeezing” effect of the micelle corona when the amine lysine side chain was deprotonated at high pH, which is contrary to phosphate binding trends of the free hexapeptide.52,54 Thus, we evaluated binding at pH 10 and 11 again here to determine if a decreased density of the micelle corona would mitigate this squeezing effect and replenish the ability to bind at high pH.

The phosphate binding performance of the four PA systems is shown in Figure 2. The results are surprising, revealing similar binding trends across all four systems for each pH or ratio condition. At pH 6, we observe essentially complete binding of all phosphate present in solution at a 4:1 ratio of PA:PO4 for all systems, with incomplete binding at lower ratios. These PA:PO4 ratio trends are consistent with those of our previous work. We also see similar trends across pH conditions as in our previous study, namely, that binding was still prohibited at pH 10 and 11 but maximized at pH 6. The only noticeable difference between systems is that there is marginally higher binding for the Pure Filler PA and the 1:1 Filler:Binding PA systems at pH 6 and 1:1 ratio of PA:PO4, which bound nearly 50% of the phosphate compared to 25%. Interestingly, selectivity over nitrate and nitrite is also retained for all four PA systems, as shown in Figure 2I–L.

Figure 2.

Figure 2

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Phosphate-binding results of the multicomponent micelle systems (A–D). Phosphate-binding performance of each PA system at a 4:1 ratio of PAtotal:PO4 and pH conditions of 6, 10, and 11 (E–H). Phosphate-binding performance at pH 6 of increasing ratios of PAtotal:PO4, where [PAtotal] = [Binding PA] + [Filler PA]. Selectivity phosphate-binding results over nitrate and nitrite of four PA micelle systems at pH 6 (I–L). The phosphate concentration is 10 ppm, and the molar ratios of PA:PO4:NO3:NO2 evaluated were 1:1:1:1, 2:1:1:1, and 4:1:1:1. The binding trends are nearly identical across all systems, contrary to expectations.

These unexpected results lead to several conclusions. First, as the density of the phosphate-binding motif decreases from 100% to 50% to 25%, there is no noticeable effect on binding, suggesting that increased conformational freedom of the unit in this design does not correlate with more efficient 1:1 binding of phosphate. What is more surprising is that the trend remains intact, even for the pure Filler PA system, which was designed to be a control system. The P-loop sequence-specific binding motif was unexpectedly not required to selectively bind phosphate, suggesting that the P-loop-associated nested cavity conformation may not be needed to bind phosphate but that other binding factors exert a larger influence. We also determined that binding at high pH is not reestablished as the density is reduced. To understand these results, we turned to molecular dynamics simulations to deconvolute the influence of H-bonds, charge, and conformation in each of the four PA designs and to probe the molecular-level interactions of binding in a synthetic, densely arrayed supramolecular material.

MD Simulation Binding Results

Using molecular dynamics (MD) simulations, we aimed to (i) verify that simulations matched experimental results, (ii) probe why binding occurred in the PA micelle independent of P-loop sequence specificity, considering binding by both a unimer PA and a PA micelle, and (iii) derive new design insights for mimicking protein binding from these unexpected yet illuminating findings.

To compare with experimental results and verify our simulation setup, we performed unbiased MD simulation for the multicomponent PA micelles at pH 6 and 11, with the Filler PA composition X varying from 0% to 100% at a 25% interval. As X increases, the reduced extent of crowding in the corona is hypothesized to improve the presentation of the P-loop binding motifs. As introduced in our previous work, the pH 6 condition consists of protonated lysine amine and H2PO4– and the pH 11 condition consists of neutral lysine amine and HPO42. The experimental protonation states for pH 10 are more ambiguous, as the lysine amine is thought to partially deprotonate before H2PO42– does, due to a shift in the lysine pKa in the densely packed charged environment. Therefore, we use the protonation state consisting of a protonated lysine amine and HPO42– to represent an idealized binding condition that allows us to obtain useful design insight.

In each simulation, the unit cell contains 90 PAs that are assembled into a single worm-like micelle. The simulation box is periodic in all three directions. The equilibrated box dimension varies slightly among systems, with an approximate dimension of 18 nm × 18 nm × 4 nm. The micelle extends along its cylindrical axis (z-axis) infinitely through the periodic bound condition. The PA micelle binding results are shown in Figure 3 at the three protonation conditions. We measured the extent of binding as the probability for a phosphate ion to form n hydrogen bonds with the micelle, where n = 0 implies that the phosphate is unbound. Overall, the results agree with those of the experiments. We find that binding is stronger at pH 6 than at pH 11, as in experiments. The binding performance remains unchanged as the Filler PA gradually replaces the Binding PA, with the Filler-PA-only system exhibiting effective phosphate binding that is comparable to that of the Binding-PA-only counterpart. The same trend is observed at each protonation condition. The binding results are accompanied by representative snapshots of the phosphate–micelle complexes taken at the end of the production run to visualize binding (Figure 3b). Overall, the snapshots indicate that the Filler and Binding PA are uniformly mixed in the multicomponent micelle. At each pH condition, the phosphate binding visually appears to remain constant across all compositions tested. We note that, at pH 6, while the snapshots agree with our experiments and show that most, if not all, phosphates are bound, the extent of binding is somewhat underestimated by the hydrogen-bonding measure, where roughly 40% of the phosphate ions are labeled unbound. This is because H2PO4– are found to form clusters (Figure S5), and as the clusters bind to the micelle, only some of its members form hydrogen bonds with the micelle. The phenomenon of spontaneous clustering for phosphate has been previously reported.55 At the optimized conditions, each phosphate (HPO42–) binds strongly to the micelle as individual ions, with most of them forming more than three hydrogen bonds.

Figure 3.

Figure 3

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Simulated phosphate-binding results of the multicomponent micelle systems. (A) Phosphate-binding performance as measured by the extent of hydrogen bonding. The x-axis refers to the Filler PA composition, and the y-axis denotes % probability of a phosphate forming x H-bonds to the micelle. The Filler PA composition is varied from 0% to 100% at 25% increments. A pH of 6 is represented by a protonated lysine ε-ammonium group and H2PO4–. A pH of 11 is represented by the neutral lysine ε-amino group and HPO42–. The optimized condition contains a protonated lysine ε-ammonium group and HPO42–. The error bar comes from 22 phosphate ions in a single simulation. (B) Representative snapshots of the micelle cross-section at pH 6 and at the optimized condition. Under each protonation condition, the snapshots are arranged as a function of Filler PA composition. The C16 hydrophobic core is shown in gray, phosphates are shown in red, Filler PA are shown in orange, and Binding PA are shown in cyan.

Next, we consider why we observe binding across systems independent of the composition or P-loop. To do this, we analyze the binding mechanisms of both the unimer PAs and the assembled PAs. Studying the Filler PA as a unimer allows us to determine if the phosphate-binding functionality of the non-sequence-specific Filler PA arises at the single-molecular level or can only be achieved by micelle assembly.

To study unimer PA binding, we employed MD simulations with the adaptive biasing force (ABF) sampling method to obtain the free energy surfaces describing the binding of a unimer PA to a phosphate. The free energy results are shown in Figure 4, evaluated under the three pH conditions. Informed by our previous work, the free energy surfaces are constructed in terms of two distance CVs. d1 denotes the distance from the phosphate to the center of the region-3 moiety (SGAGKT for Binding PA and K for Filler PA), and d2 denotes the distance from the phosphate to the center of region 2. At pH 6 and for both Binding PA and Filler PA systems, the free energy difference between the bound state and the unbound states is below 5 kJ/mol, indicating no strong preference to bind. While it is enthalpically favorable for the oppositely charged phosphate and PA to form a charge-neutral complex, such an enthalpic gain is offset by a comparable loss of entropy. Similar comments have been made for the free-standing, zwitterionic hexapeptide.56 We observe a similar preferred unbound state at pH 11 for both PAs, since neither enthalpic nor entropic driving force is present to facilitate binding.

Figure 4.

Figure 4

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Free energy surface for a unimer (A) Filler PA (C16G5K) and (B) Binding PA (C16G5hex) binding to a phosphate. The free energy difference between two adjacent contour lines is 5 kJ/mol. The free energy is described in terms of two distance CVs. d1 denotes the distance from the phosphate to the center of the region-3 moiety (SGAGKT for Binding PA and K for Filler PA), and d2 denotes the distance from the phosphate to the center of the region 2, allowing one to determine a phosphate location that is stabilized or bound to a peptide. For each system, the free energy surface is close to converged and obtained at the end of 400 ns of ABF biased simulation. At pH 10, there is a local minimum that indicates that phosphate binds for both the Filler PA and the Binding PA.

At pH 10, the Binding PA shows a favorable binding with free energy between −20 and −25 kJ/mol, with is very close to the binding free energy estimated experimentally for the free-standing hexapeptide (−4 ± 0.1 kcal/mol).52 The free energy surface for the Filler PA also shows a minimum for the bound state, with an energy difference of ∼5 kJ/mol. For both systems, the wide free energy wells for bound states suggest that the overall bound structures are not fully constrained but instead can freely adopt different conformations. Overall, the free energy surface suggests that the phosphate is bound exclusively to the charged lysine side chain, while the flexible G5 linker aids to wrap around the phosphate in many different ways. While both systems show relatively flexible binding provided by the G5 region, the bound state of Binding PA is better-defined and deeper, suggesting that the P-loop provides stronger binding and leads to a specific bound conformation.

The single-chain simulations confirm the functionality of the P-loop. More importantly, however, they reveal that phosphate binding can also be realized by combining electrostatic attraction from the protonated lysine amine and flexible accommodation from the G5 region. The finding provides us with an alternative route to access and engineer the phosphate-binding functionality. The self-assembled micelle system is one way to harness such an alternative binding route. As the PAs self-assemble, the functional peptide headgroup becomes dramatically condensed at the micelle corona. The rise in concentration can potentially amplify the access to the alternative binding route since a phosphate will be able to simultaneously interact with multiple lysine amine sites and flexible G5 segments, neither of which are required to preorganize into specific conformations.

Finally, we move to the third aim of the MD study: deriving design insights from the altered binding mechanism in this synthetic platform. So far, both experimental and simulated observations suggest an overall improvement in binding performance as PA unimers self-assemble into micelles. At pH 6, while as a unimer, neither Binding PA nor Filler PA shows preferential binding; as micelles, they exhibit nearly complete binding. At pH 10, while the Binding PA unimer exhibits stronger binding than the Filler PA, the binding performance as micelles remains constant at all compositions. The remaining question lies in explaining why the binding performance improves in micelle systems.

Informed by the unimer binding results, we hypothesize that the multicomponent micelle systems can have two phosphate binding routes, one relying on the P-loop motif and the other utilizing one or more positively charged lysine amine tails. To understand how each contributes to phosphate binding under different circumstances, we start by examining the dihedral conformation for the P-loop sequence and then characterize how and where the phosphates are mostly bound on the micelle. Our Ramachandran plots (Figure S6) show that, in the micelle systems, the P-loop motif tends to adopt a particular dihedral conformation that resembles an LRL compound nest. The G5 region shows a typical glycine dihedral distribution, meaning that the Filler PA does not adopt any nest conformation. However, since the binding performance is found to be constant regardless of the presence of nests, we employ a second analysis to determine whether, and if so to what extent, the compound nests are indeed employed to bind phosphate. Figure S7 presents the statistics for the bound location along the peptide sequence at pH 6 and at the optimized protonation condition. Under both conditions, over 50% of the total hydrogen bonds are contributed by the G5 linker domain, lysine residue, and amidated C-termini, which are the common domains present in both Binding PA and Filler PA. This binding contribution resembles the alternative binding route utilized by the Filler PA unimer for phosphate binding. The rest of the hydrogen bonds are contributed by the remaining P-loop hexapeptide (excluding lysine and amidated C-termini) that is unique to the Binding PA. As the Filler PA composition increases, the contribution from the P-loop motif diminishes and becomes substituted by that from the common domains. The result confirms that the alternative binding route, discovered from the unimer’s binding behavior, continues to function in the micelle. It also shows that the compound nest formed at the P-loop is not the predominant binding location for phosphate, which consistently explains why the phosphate-binding performance is independent of the presence of nests. As the Filler PA composition increases, the gradual transition from P-loop contributed binding to charged lysine amine-contributed binding aligns with our hypothesis that the alternative binding route takes over the phosphate binding as Filler PA becomes the majority.

Another point of discussion is that the alternative binding route is amplified in the micelle, which could be the main reason for the overall improved binding in the micelle. To evaluate this idea, we categorized the binding environment of a phosphate ion into binding motifs, where a motif of x–y denotes that the phosphate is bound by x Binding PA and y Filler PA. Figure 5A reports the percent population of the five most-observed binding motifs. We used data obtained under the optimized conditions for better statistics and informative insights. Similar trends are observed from the results at pH 6 (Figure S8). In this analysis, bound phosphates are found to adopt diverse binding motifs with comparable probability. Among them, multichain binding motifs, such as 0–2, 1–1, 2–0, and 1–2, contribute significantly. Representative snapshots for the prevalent multichain binding route seen in the 50% Filler PA system are included in Figure 5B–D. We also notice that in this system, despite the symmetric composition, popular motifs are predominantly contributed by Filler PA. The mismatch (or shift) between the stoichiometry in binding motifs and the composition shows that the alternative binding route, once amplified by multichain binding, becomes more favorable than the P-loop binding route.

Figure 5.

Figure 5

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Population and snapshots of the top phosphate binding motifs. (A) The population of the top five most-observed binding motifs at the optimized protonation condition. The Filler PA composition is varied from 0% to 100% at 25% increments. The binding motif of a phosphate ion is denoted as x–y, where x refers to the number of Binding PA bound to the phosphate and y refers to the number of Filler PA bound to the phosphate. The numeric population for each motif is printed on top of the bar. (B–D) Representative snapshots for the (B) 2–0, (C) 1–1, and (D) 1–2 multichain binding motifs at 50% Filler PA composition, optimized protonation condition. The snapshots are taken along the micelle cross-section. The C16 hydrophobic core is shown in gray, phosphates are shown in red, Filler PAs are shown in orange, and Binding PAs are shown in cyan.

The binding motif analysis points us to an important free energy contribution: the loss of entropy associated with molecular binding. As seen in the unimer binding simulation at pH 6, the favorable enthalpic gain is offset by the entropy loss, resulting in an overall zero binding free energy favor. For multichain binding in micelles, the enthalpic gain is amplified, as there will be more pairs of electrostatic interactions. Meanwhile, the entropy loss is minimized for multichain binding for two reasons. First, the micelle can accommodate the phosphate via a diverse range of interchangeable binding motifs. Second, each binding motif also includes numerous degenerate states because a PA in the motif can be indistinguishably substituted by another neighboring PA of the same kind. As a result, increased enthalpic gain and minimized entropic loss both act to improve phosphate binding to micelles compared to the unimer counterpart.

In sum, we determined that, for the protein-analogous micelle, binding is retained but the binding mechanism shifts from native proteins. Certain factors remain consistent, namely, H-bonding and electrostatic attraction. However, in this platform, the design element of a conformationally constrained nested cavity is disregarded in favor of a new factor unique to this synthetic platform, namely, that of minimized entropy loss through the flexibility of multichain binding conformation using nonspecific residues. This intriguing design element aligns with recently published work, where flexibility is introduced as a critical design factor in engineered protein binding.57 Their flexible proteins are selectively bound to unfavorable metals by adopting previously inaccessible conformations in the native protein. This PA platform intrinsically accesses this feature to selectively bind to phosphate, making it an intriguing platform to optimize in future rounds of design.

Case Study: Evaluating Design Principles through Single-Peptide Binding of Phosphate

We are poised to translate these design insights and physical principles to engineer de novo peptide sequences to determine whether we can mimic the protein binding of phosphate without the predetermined conformational restrictions that are characteristic of protein binding. To engineer de novo peptide sequences for phosphate binding, we designed a series of simplified motifs to manipulate the effects of hydrogen bonding, electrostatic interactions, and chain flexibility. We chose only to build the motifs using glycine and lysine residues, as those were the only residues necessary to achieve binding in the Filler PA. We also wanted to isolate more precisely the individual molecular mechanistic binding principles, so we switched material platforms from the highly interactive peptide micelle corona to a polystyrene–polyethylene–peptide Tentagel resin system that has been used to characterize single-peptide binding.12

Using glycine and lysine residues, we constructed five peptide motifs. The first was a single lysine (K) residue to determine if binding could be achieved by a single charge alone, without significant hydrogen bond contributions. The other four motifs varied two design variables: (i) charge number, through controlling the number of lysine residues, and (ii) charge spacing and their corresponding conformational freedom, adjusted through the number of glycine residues that spaced the lysine residues. From these guiding principles, the four synthesized sequences were KGK, KGGK, KGKGK, and KGGKGGK. Their phosphate binding performance is shown in Figure 6 at pH 6 and 1:1, 2:1, 4:1, and 8:1 peptide:PO4 molar ratios, all at a phosphate concentration of 10 ppm.

Figure 6.

Figure 6

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Phosphate-binding results of five single-peptide motifs, (A) K, (B) KGK, (C) KGKGK, (D) KGGK, and (E) KGGKGGK, at pH 6, 10 ppm of PO4, and 1:1, 2:1, 4:1, and 8:1 peptide:PO4 molar ratios.

Significantly, the phosphate-binding results demonstrate that binding can be achieved by de novo peptide systems. All systems excluding the K system bound phosphate to a noteworthy degree as the ratio of peptide increased. The KGK, KGGK, and KGKGK systems all performed similarly, with roughly half of the phosphate bound at 4:1 and 8:1 ratios of peptide to phosphate. KGGKGGK bound the highest percentage of phosphate at 78% ± 4.8% for an 8:1 ratio of peptide:PO4. The K system shows minimal binding, indicating that a single charge alone is insufficient to bind to phosphate. None of the systems achieved 100% binding of phosphate at the ratios tested.

The de novo systems also offer a valuable conformational design insight toward synthetic mimicking of protein-binding. Comparing KGKGK to KGGKGGK, we see that increased spacing and conformational freedom between charges promote higher binding performance, aligning with our newly derived flexibility design factor. Binding in these systems is similarly likely correlated to entropy maximization of the chains, where chains are not forced to adopt a specific constrained conformation to bind but rather can bind through multiple flexible binding factors. The flexible PA micelle and the KGGKGGK systems are better poised to adopt a favorable binding conformation than the other three more rigid counterparts.

Despite not achieving complete binding in these single-peptide resin systems, we were nevertheless able to demonstrate that synthetic binding sequences can still be employed to bind to phosphate. This intriguing result indicates that we no longer need to be limited to protein-derived sequences and particular tertiary and quaternary structures to mimic protein binding. While these systems present a reduced design approach, we are positioned to translate these features and principles to more sophisticated sequences and systems in an effort to engineer precise biomimetic materials.

Conclusions

In this work, we determined that complete and selective phosphate binding by peptides can be achieved independently of sequence when facilitated by the densely packed, highly flexible micelle peptide corona environment. This micelle platform has the unique advantage of presenting a high density of adaptable hydrogen bond donors that can readily adopt the conformations necessary to bind to phosphate. While proteins must rely on adopting a specific conformation to bind, the protein-analogous micelle can adapt more readily to achieve binding conformations within the headgroup that utilize both charge and hydrogen bond donors. We began the study with two well-established design parameters—hydrogen bonding and charge—and identified the importance of entropy maximization and flexibility of the binding moieties, offering insight into how conformational freedom can affect functionality in synthetic materials. Ion capture mechanisms that take advantage of highly flexible binding sites and the associated increase in entropy are often nonaccessible in naturally occurring proteins, which must resort to a highly constrained conformation to bind. These results make the peptide micelle platform highly intriguing for future rounds of protein-inspired binding design, presenting a high concentration of highly flexible and tunable binding contributors in one local environment. Finally, we demonstrated that de novo phosphate-binding peptide sequences can be engineered from these design principles, opening an intriguing opportunity for biomimetic materials to overcome the highly complex binding mechanisms of proteins to outperform them through informed engineered design.

Methods

Synthesis of Peptide Amphiphile Micelles and PS–PEG–Peptide Resin Systems

Two peptide sequences (GGGGGK and GGGGGSGAGKT) were synthesized on 0.25 mmol of rink amide resin (Novabiochem) through standard FMOC solid phase peptide synthesis using an automated Prelude X Benchtop Synthesizer (Protein Technologies, Tuscon, AZ, USA). For each coupling step, the FMOC protecting group was first removed from the resin using 20% piperidine in dimethylformamide (DMF). Separately, the amino acid was activated with N,N,N′,N′-tetramethyl-O-(1H-benzotriazol-1-yl)uranium hexafluorophosphate (HBTU) and N,N-diisopropylethylamine (DIPEA) in a molar ratio of 1:4:3.95:8 of resin:amino acid:HATU:DIPEA. The activated amino acid cocktail was then added to the deprotected resin and then allowed to mix to conjugate. After the amino acid couplings were completed, the deprotected glycine N-terminus was then coupled to a palmitic acid tail.

After drying the resin under nitrogen, the peptide amphiphiles were then cleaved from the resin using a 95:2.5:2.5 by volume trifluoroacetic acid:triisopropylsilane:Milli-Q water cleavage cocktail for 2 h while shaking. The cleaved peptide amphiphiles were then precipitated through dropwise addition of the cleavage solution in a 50:50 by volume hexanes:–80 °C diethyl ether solution. The peptide amphiphiles were dried under nitrogen and dissolved in water.

The peptide amphiphiles were purified using reverse-phase HPLC (Prominence, Shimadzu, Columbia, MD, USA) on a C8 column (Waters, Milford, MA, USA) at 50 °C with acetonitrile and water with 0.1% formic acid as gradient mobile phases. The molecular weight of the products in the HPLC fractions were characterized by MALDI-TOF mass spectral analysis (Biflex III, Bruker, Billerica, MA, USA). The product-verified fractions were lyophilized and stored as powders at −20 °C. The purity was analyzed using a similar gradient method on an Agilent 6130 LCMS system in the University of Chicago’s Mass Spectrometry Facility, using a Waters column, C8, XBridge, 4.6 × 150 mm2, 5 μm particle size, and 130 Å pore size. The purity was calculated by integrating the area under the peaks during the elution time and dividing the area of the product peak by the area of all peaks, excluding peaks that were artifacts of the method. The purity was confirmed to be greater than 95% for both PAs.

The PS–PEG–peptide systems were synthesized on 0.25 mmol of TentaGel S-NH2 resin (90 μm) for the following peptide sequences: K, KGK, KGGK, KGKGK, and KGGKGGK. The synthesis protocol was identical to that of the rink amide resin systems with the exception that a double coupling step was performed for each amino acid to ensure complete conjugation. The peptides were not cleaved from the resin. After the coupling steps were completed, the resin was rinsed with dichloromethane, dried under nitrogen, weighed on an analytical balance, and submerged in Milli-Q water to reach the desired molar concentration of peptide given the loading (mmol/g) of the TentaGel resin.

Micelle Fabrication Procedure

The multicomponent PA micelles were fabricated to ensure homogeneous mixing of both PA components in each micelle. To do this, the purified single-component PAs were lyophilized, and the lyophilized powder was dissolved in hexafluoroisopropanol (HFIP), which is a good solvent for PAs that does not promote hydrophobically driven self-assembly into micelles. The PA-in-HFIP solutions of each PA were combined to achieve the desired ratio and molar concentration. The HFIP was evaporated until nitrogen flowed, leaving behind a thin film. The film was dissolved in Milli-Q water at the desired concentration, heated at 70 °C for 1 h on a mechanical shaker, and left to equilibrate to room temperature before experimental use.

Critical Micelle Concentration (CMC) Determination

The CMC was calculated by marking an increase of fluorescence intensity, corresponding to an increased micelle concentration, of a dissolved dye that fluoresces in the presence of hydrophobic micelle cores. To execute this experiment, 1,6-diphenyl-1,3,5-hexatriene (DPH) dye was dissolved in tetrahydrofuran at a concentration of 100 mM and then diluted in water to a final concentration of 1 μM. Each PA was dissolved in 1 μM DPH solution and serially diluted from 500 to 0.05 μM PA, performed in triplicates for each PA. The dilutions were allowed to equilibrate for 1 h while covered with aluminum foil at room temperature and then were transferred to a 96-well plate. Their fluorescence intensity was measured using a Tecan Infinite 200 plate reader (Mannedorf, Switzerland) with an excitation wavelength of 360 nm and an emission wavelength of 430 nm. The data were plotted with a log-transformed concentration. The CMC was identified as the concentration at which the fluorescence value is greater than 20% above the zero-slope baseline region.

Cryogenic Transmission Electron Microscopy (Cryo-TEM) Imaging

Cryo-TEM samples were flash-frozen in liquid ethane onto Quantifoil R1.2/1.3 grids (copper, 200 mesh; Q210CR1.3, EMS, Hatfield, PA) by using a Vitrobot Mark IV (FEI, Hillsboro, OR). Grids were imaged at 300 kV accelerating voltage on a Titan Krios (Thermo Scientific, Hillsboro, OR). The images were processed and measured digitally by using ImageJ software.

Analysis of pH-Dependent Phosphate Binding

Samples were prepared in Milli-Q water in molar ratios of 1:1, 2:1, and 4:1 of peptide:PO4, equivalent to 10 ppm PO4 using a Na2HPO4 salt. The pH was adjusted to the desired pH condition using minimal HCl and NaOH, and the pH was measured using a Fisher Scientific Accumet XL500 pH/ISE/Conductivity Benchtop Meter (Vernon Hills, IL, USA) and a Fisherbrand Accumet Micro Glass Mercury-Free Combination Electrode. Upon reaching the target pH, the solution was filtered using a 13 mm 0.22 μm GHP Acrodisc syringe filter to separate the unbound anions from the PA-anion bound complexes. The filtrate was analyzed using ion chromatography using a Thermo Scientific Dionex ICS-5000+ equipped with a Dionex AS-DV autosampler and a Dionex IonPac AS22 column (Product No. 064141, Thermo Scientific, California, USA). The analysis was run using an eluent of 4.5 mM sodium carbonate and 1.4 mM sodium bicarbonate (Product No. 063965 from Thermo Scientific, California, USA) and a Dionex AERS 500 Carbonate 4 mm Electrolutically Regenerated Suppressor (Product No. 085029 from Thermo Scientific, California, USA). The experiments were performed in duplicate for each condition.

Simulation Methods

Atomistic Model

The simulations used the GROningen MAchine for Chemical Simulations (GROMACS)58 package and the ABF enhanced sampling methods implemented in SSAGES.59 The PAs were modeled using the CHARMM force field,60 and water was modeled using the TIP3P model.61 Custom force field parameters used for phosphate ions are described in our previous work.37 The Lorentz–Berthelot mixing rule was used for unlike nonbonded interactions involving phosphate atoms. Nonbonded interactions were calculated by using a 12 Å cutoff distance. Long-range electrostatic interactions were handled using fast smooth particle-mesh Ewald (SPME)62 with a 0.12 nm Fourier spacing. Covalent bonds involving hydrogens were constrained using the LINCS algorithm.63 All simulations were integrated using the leapfrog algorithm with a 2 fs time step.

Simulations of PA Unimer

The starting configuration and simulation protocol for unimer phosphate binding from ref (37) are adopted exactly for Filler PA and Binding PA. The temperature was maintained at 300 K using a Nosé–Hoover thermostat with a time constant of 0.1 ps. Volume was held constant. The two distance CVs used in this work are defined as the following. For Binding PA, d1 is defined as the distance between the center of mass of the phosphate and the center of mass of the main chain heavy atoms of SGAGKT and the ε-amino N in lysine. For Filler PA, d1 is defined as the distance between the center of mass of the phosphate, the center of mass of the main chain heavy atoms, and the ε-amino N in the lysine residue. d2 is defined as the distance between the center of mass of the phosphate and the center of mass of the main chain heavy atoms of the GGGGG linker. Readers are referred to ref (37) for detailed settings for ABF sampling. Each ABF simulation was carried out with 4 walkers, and output was monitored at intervals of 40 ns until the free energy features no longer changed between the two most recent outputs, resulting in 400 ns total simulation time per walker for each pH condition.

Starting Configuration of Multicomponent Micelles

The protocol to generate starting configurations for multicomponent micelles is adapted from ref (37). First, nine PA molecules were packed in the x–y plane to form a layer, with the C16 tails pointing inward and with 40° angle between adjacent chains. To achieve a target composition, a probabilistic criterion was used to initialize the identity of each PA. For example, to achieve a Filler PA fraction of 0.25, a random number R was generated for each PA. The corresponding PA would be initialized as a Filler PA if R < 0.25. Then, 10 multicomponent layers were independently generated and stacked in the z-direction. Phosphate ions were subsequently inserted at random positions avoiding position overlap with the PA molecules. At a PAtotal:PO4 ratio of 4:1, each simulation box contains 90 PA chains and 22 phosphate ions. The simulation box was 16 nm in x and y and 5 nm in z. After solvation, sodium or chloride ions were added to neutralize the system.

Simulations of Multicomponent Micelles

The starting configuration was first energy-minimized and subsequently equilibrated under an NVT ensemble for 4 ns. During the equilibration, harmonic position restraint was applied to the first carbon in the C16 group. Subsequently, the position restraint was removed, and the system evolved under the NPT ensemble. In NVT and NPT simulations, the temperature was maintained at 300 K using a Nosé–Hoover thermostat with a time constant of 0.1 ps. In NPT simulations, the pressure was maintained at 1.0 bar using a Berendsen barostat. The barostat was anisotropic so that the pressure in the z direction was coupled independently from that in the x–y direction. The total simulation time was 150 ns for the system. Trajectories collected during the final 50 ns were used for analysis.

Hydrogen Bonding Analysis

The GROMACS hydrogen bond tool was used to identify H-bonds formed between PA chains and phosphate ions. The H-bond criterion used a donor–acceptor distance cutoff of 0.38 nm and a hydrogen-donor–acceptor angle cutoff of 45°.64 Visual Molecular Dynamics (VMD) was used for trajectory visualization.65

Acknowledgments

This work was supported by the National Science Foundation DMR-1710357. W.C.F. acknowledges support from the National Science Foundation (NSF) Graduate Research Fellowship Program under Grant No. DGE-1746045. The authors would like to acknowledge the University of Chicago’s Advanced Electron Microscopy Core Facility for acquiring the TEM images, as well as the University of Chicago’s Mass Spectroscopy Core Facility, where LC-MS data were acquired. Analyte analysis by ion chromatography was performed at the Northwestern University Quantitative Bioelement Imaging Center. The simulations were completed on computational resources provided by the University of Chicago Research Computing Center.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.bioconjchem.3c00454.

  • Author contributions and additional data, including LC-MS verification and purity analysis, CMC, and additional simulation results (PDF)

Author Contributions

§ W.C.F., C.D., O.T.T.: These authors contributed equally to this work.

The authors declare no competing financial interest.

Supplementary Material

bc3c00454_si_001.pdf (530.4KB, pdf)

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