A computational protein design protocol for optimization of the SARS-CoV-2 receptor-binding-motif affinity for human ACE2.

The present protocol describes the computational design of the SARS-CoV-2 receptor binding motif (RBD) to identify mutations that can potentially improve binding affinity for the human ACE2 (hACE2) receptor. We focus on four positions located at the interface with the hACE2 receptor in the RBD:hACE2 complex. We conduct the design with a high-throughput computational protein design (CPD) program, Proteus, incorporating an adaptive Monte Carlo (MC) protocol that promotes the selection of sequences with good binding affinities. For complete details on the use and execution of this protocol, please refer to Polydorides and Archontis (2021).

Computational Design of Peptides with Improved Recognition of the Focal Adhesion Kinase FAT Domain.

We describe a two-stage computational protein design (CPD) methodology for the design of peptides binding to the FAT domain of the protein focal adhesion kinase. The first stage involves high-throughput CPD calculations with the Proteus software. The energies of the folded state are described by a physics-based energy function and of the unfolded peptides by a knowledge-based model that reproduces aminoacid compositions consistent with a helicity scale. The obtained sequences are filtered in terms of the affinity and the stability of the complex. In the second stage, design sequences are further evaluated by all-atom molecular dynamics simulations and binding free energy calculations with a molecular mechanics/implicit solvent free energy function.

Computational optimization of the SARS-CoV-2 receptor-binding-motif affinity for human ACE2.

The coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is responsible for the coronavirus disease 2019 pandemic, and the closely related SARS-CoV coronavirus enter cells by binding at the human angiotensin converting enzyme 2 (hACE2). The stronger hACE2 affinity of SARS-CoV-2 has been connected with its higher infectivity. In this work, we study hACE2 complexes with the receptor-binding domains (RBDs) of the human SARS-CoV-2 and human SARS-CoV viruses, using all-atom molecular dynamics simulations and computational protein design with a physics-based energy function. The molecular dynamics simulations identify charge-modifying substitutions between the CoV-2 and CoV RBDs, which either increase or decrease the hACE2 affinity of the SARS-CoV-2 RBD. The combined effect of these mutations is small, and the relative affinity is mainly determined by substitutions at residues in contact with hACE2. Many of these findings are in line and interpret recent experiments. Our computational protein design calculations redesign positions 455, 493, 494, and 501 of the SARS-CoV-2 receptor binding motif, which contact hACE2 in the complex and are important for ACE2 recognition. Sampling is enhanced by an adaptive importance sampling Monte Carlo method. Sequences with increased affinity replace CoV-2 glutamine by a negative residue at position 493; serine by a nonpolar or aromatic residue or an asparagine at position 494; and asparagine by valine or threonine at position 501. Substitutions at positions 455 and 501 have a smaller effect on affinity. Substitutions suggested by our design are seen in viral sequences encountered in other species, including bat and pangolin. Our results might be used to identify potential virus strains with higher human infectivity and assist in the design of peptide-based or peptidomimetic compounds with the potential to inhibit SARS-CoV-2 binding at hACE2.

Physics-Based Computational Protein Design: An Update.

We describe methods for physics-based protein design and some recent applications from our work. We present the physical interpretation of a MC simulation in sequence space and show that sequences and conformations form a well-defined statistical ensemble, explored with Monte Carlo and Boltzmann sampling. The folded state energy combines molecular mechanics for solutes with continuum electrostatics for solvent. We usually assume one or a few fixed protein backbone structures and discrete side chain rotamers. Methods based on molecular dynamics, which introduce additional backbone and side chain flexibility, are under development. The redesign of a PDZ domain and an aminoacyl-tRNA synthetase enzyme were successful. We describe a versatile, adaptive, Wang-Landau MC method that can be used to design for substrate affinity, catalytic rate, catalytic efficiency, or the specificity of these properties. The methods are transferable to all biomolecules, can be systematically improved, and give physical insights.

Recognition of LD motifs by the focal adhesion targeting domains of focal adhesion kinase and proline-rich tyrosine kinase 2-beta: Insights from molecular dynamics simulations.

The focal adhesion kinase (FAK) and the proline-rich tyrosine kinase 2-beta (PYK2) are implicated in cancer progression and metastasis and represent promising biomarkers and targets for cancer therapy. FAK and PYK2 are recruited to focal adhesions (FAs) via interactions between their FA targeting (FAT) domains and conserved segments (LD motifs) on the proteins Paxillin, Leupaxin, and Hic-5. A promising new approach for the inhibition of FAK and PYK2 targets interactions of the FAK domains with proteins that promote localization at FAs. Advances toward this goal include the development of surface plasmon resonance, heteronuclear single quantum coherence nuclear magnetic resonance (HSQC-NMR) and fluorescence polarization assays for the identification of fragments or compounds interfering with the FAK-Paxillin interaction. We have recently validated this strategy, showing that Paxillin mimicking polypeptides with 2 to 3 LD motifs displace FAK from FAs and block kinase-dependent and independent functions of FAK, including downstream integrin signaling and FA localization of the protein p130Cas. In the present work we study by all-atom molecular dynamics simulations the recognition of peptides with the Paxillin and Leupaxin LD motifs by the FAK-FAT and PYK2-FAT domains. Our simulations and free-energy analysis interpret experimental data on binding of Paxillin and Leupaxin LD motifs at FAK-FAT and PYK2-FAT binding sites, and assess the roles of consensus LD regions and flanking residues. Our results can assist in the design of effective inhibitory peptides of the FAK-FAT: Paxillin and PYK2-FAT:Leupaxin complexes and the construction of pharmacophore models for the discovery of potential small-molecule inhibitors of the FAK-FAT and PYK2-FAT focal adhesion based functions.

Hybrid MC/MD for protein design.

Computational protein design relies on simulations of a protein structure, where selected amino acids can mutate randomly, and mutations are selected to enhance a target property, such as stability. Often, the protein backbone is held fixed and its degrees of freedom are modeled implicitly to reduce the complexity of the conformational space. We present a hybrid method where short molecular dynamics (MD) segments are used to explore conformations and alternate with Monte Carlo (MC) moves that apply mutations to side chains. The backbone is fully flexible during MD. As a test, we computed side chain acid/base constants or pKa's in five proteins. This problem can be considered a special case of protein design, with protonation/deprotonation playing the role of mutations. The solvent was modeled as a dielectric continuum. Due to cost, in each protein we allowed just one side chain position to change its protonation state and the other position to change its type or mutate. The pKa's were computed with a standard method that scans a range of pH values and with a new method that uses adaptive landscape flattening (ALF) to sample all protonation states in a single simulation. The hybrid method gave notably better accuracy than standard, fixed-backbone MC. ALF decreased the computational cost a factor of 13.

Toward Rational Design of Selective Molecularly Imprinted Polymers (MIPs) for Proteins: Computational and Experimental Studies of Acrylamide Based Polymers for Myoglobin.

Molecularly imprinted polymers (MIPs) have potential as alternatives to antibodies in the diagnosis and treatment of disease. However, atomistic level knowledge of the prepolymerization process is limited that would facilitate rational design of more efficient MIPs. Accordingly, we have investigated using computation and experiment the protein-monomer binding interactions that may influence the desired specificity. Myoglobin was used as the target protein and five different acrylamide-based monomers were considered. Protein binding sites were predicted using SiteMap and binding free energies of monomers at each site were calculated using MM-GBSA. Statistical thermodynamic analysis and study of atomistic interactions facilitated rationalization of monomer performance in MIP rebinding studies (% rebind; imprinting factors). CD spectroscopy was used to determine monomer effects on myoglobin secondary structure, with all monomers except the smallest monomer (acrylamide) causing significant changes. A complex interplay between different protein-monomer binding effects and MIP efficacy was observed. Validation of hypotheses for key binding features was achieved by rational selection of two different comonomer MIP combinations that produced experimental results in agreement with predictions. The comonomer studies revealed that uniform, noncompetitive binding of monomers around a target protein is favorable. This study represents a step toward future rational in silico design of MIPs for proteins.

Simple models for nonpolar solvation: Parameterization and testing.

Implicit solvent models are important for many biomolecular simulations. The polarity of aqueous solvent is essential and qualitatively captured by continuum electrostatics methods like Generalized Born (GB). However, GB does not account for the solvent-induced interactions between exposed hydrophobic sidechains or solute-solvent dispersion interactions. These "nonpolar" effects are often modeled through surface area (SA) energy terms, which lack realism, create mathematical singularities, and have a many-body character. We have explored an alternate, Lazaridis-Karplus (LK) gaussian energy density for nonpolar effects and a dispersion (DI) energy term proposed earlier, associated with GB electrostatics. We parameterized several combinations of GB, SA, LK, and DI energy terms, to reproduce 62 small molecule solvation free energies, 387 protein stability changes due to point mutations, and the structures of 8 protein loops. With optimized parameters, the models all gave similar results, with GBLK and GBDILK giving no performance loss compared to GBSA, and mean errors of 1.7 kcal/mol for the stability changes and 2 Å deviations for the loop conformations. The optimized GBLK model gave poor results in MD of the Trpcage mini-protein, but parameters optimized specifically for MD performed well for Trpcage and three other small proteins. Overall, the LK and DI nonpolar terms are valid alternatives to SA treatments for a range of applications. © 2017 Wiley Periodicals, Inc.

Proteus and the Design of Ligand Binding Sites.

This chapter describes the organization and use of Proteus, a multitool computational suite for the optimization of protein and ligand conformations and sequences, and the calculation of pK α shifts and relative binding affinities. The software offers the use of several molecular mechanics force fields and solvent models, including two generalized Born variants, and a large range of scoring functions, which can combine protein stability, ligand affinity, and ligand specificity terms, for positive and negative design. We present in detail the steps for structure preparation, system setup, construction of the interaction energy matrix, protein sequence and structure optimizations, pK α calculations, and ligand titration calculations. We discuss illustrative examples, including the chemical/structural optimization of a complex between the MHC class II protein HLA-DQ8 and the vinculin epitope, and the chemical optimization of the compstatin analog Ac-Val4Trp/His9Ala, which regulates the function of protein C3 of the complement system.

Crossreactivity to vinculin and microbes provides a molecular basis for HLA-based protection against rheumatoid arthritis.

The HLA locus is the strongest risk factor for anti-citrullinated protein antibody (ACPA)(+) rheumatoid arthritis (RA). Despite considerable efforts in the last 35 years, this association is poorly understood. Here we identify (citrullinated) vinculin, present in the joints of ACPA(+) RA patients, as an autoantigen targeted by ACPA and CD4(+) T cells. These T cells recognize an epitope with the core sequence DERAA, which is also found in many microbes and in protective HLA-DRB1*13 molecules, presented by predisposing HLA-DQ molecules. Moreover, these T cells crossreact with vinculin-derived and microbial-derived DERAA epitopes. Intriguingly, DERAA-directed T cells are not detected in HLA-DRB1*13(+) donors, indicating that the DERAA epitope from HLA-DRB1*13 mediates (thymic) tolerance in these donors and explaining the protective effects associated with HLA-DRB1*13. Together our data indicate the involvement of pathogen-induced DERAA-directed T cells in the HLA-RA association and provide a molecular basis for the contribution of protective/predisposing HLA alleles.

New compstatin peptides containing N-terminal extensions and non-natural amino acids exhibit potent complement inhibition and improved solubility characteristics.

Compstatin peptides are complement inhibitors that bind and inhibit cleavage of complement C3. Peptide binding is enhanced by hydrophobic interactions; however, poor solubility promotes aggregation in aqueous environments. We have designed new compstatin peptides derived from the W4A9 sequence (Ac-ICVWQDWGAHRCT-NH2, cyclized between C2 and C12), based on structural, computational, and experimental studies. Furthermore, we developed and utilized a computational framework for the design of peptides containing non-natural amino acids. These new compstatin peptides contain polar N-terminal extensions and non-natural amino acid substitutions at positions 4 and 9. Peptides with α-modified non-natural alanine analogs at position 9, as well as peptides containing only N-terminal polar extensions, exhibited similar activity compared to W4A9, as quantified via ELISA, hemolytic, and cell-based assays, and showed improved solubility, as measured by UV absorbance and reverse-phase HPLC experiments. Because of their potency and solubility, these peptides are promising candidates for therapeutic development in numerous complement-mediated diseases.

Combination of theoretical and experimental approaches for the design and study of fibril-forming peptides.

Self-assembling peptides that can form supramolecular structures such as fibrils, ribbons, and nanotubes are of particular interest to modern bionanotechnology and materials science. Their ability to form biocompatible nanostructures under mild conditions through non-covalent interactions offers a big biofabrication advantage. Structural motifs extracted from natural proteins are an important source of inspiration for the rational design of such peptides. Examples include designer self-assembling peptides that correspond to natural coiled-coil motifs, amyloid-forming proteins, and natural fibrous proteins. In this chapter, we focus on the exploitation of structural information from beta-structured natural fibers. We review a case study of short peptides that correspond to sequences from the adenovirus fiber shaft. We describe both theoretical methods for the study of their self-assembly potential and basic experimental protocols for the assessment of fibril-forming assembly.

Structure based inhibitor design targeting glycogen phosphorylase B. Virtual screening, synthesis, biochemical and biological assessment of novel N-acyl-ß-d-glucopyranosylamines.

Glycogen phosphorylase (GP) is a validated target for the development of new type 2 diabetes treatments. Exploiting the Zinc docking database, we report the in silico screening of 1888 N-acyl-ß-d-glucopyranosylamines putative GP inhibitors differing only in their R groups. CombiGlide and GOLD docking programs with different scoring functions were employed with the best performing methods combined in a 'consensus scoring' approach to ranking of ligand binding affinities for the active site. Six selected candidates from the screening were then synthesized and their inhibitory potency was assessed both in vitro and ex vivo. Their inhibition constants' values, in vitro, ranged from 5 to 377µM while two of them were effective at causing inactivation of GP in rat hepatocytes at low µM concentrations. The crystal structures of GP in complex with the inhibitors were defined and provided the structural basis for their inhibitory potency and data for further structure based design of more potent inhibitors.

Insights into the mechanism of C5aR inhibition by PMX53 via implicit solvent molecular dynamics simulations and docking.

BACKGROUND: The complement protein C5a acts by primarily binding and activating the G-protein coupled C5a receptor C5aR (CD88), and is implicated in many inflammatory diseases. The cyclic hexapeptide PMX53 (sequence Ace-Phe-[Orn-Pro-dCha-Trp-Arg]) is a full C5aR antagonist of nanomolar potency, and is widely used to study C5aR function in disease. RESULTS: We construct for the first time molecular models for the C5aR:PMX53 complex without the a priori use of experimental constraints, via a computational framework of molecular dynamics (MD) simulations, docking, conformational clustering and free energy filtering. The models agree with experimental data, and are used to propose important intermolecular interactions contributing to binding, and to develop a hypothesis for the mechanism of PMX53 antagonism. CONCLUSION: This work forms the basis for the design of improved C5aR antagonists, as well as for atomic-detail mechanistic studies of complement activation and function. Our computational framework can be widely used to develop GPCR-ligand structural models in membrane environments, peptidomimetics and other chemical compounds with potential clinical use.

Self-assembly of an aspartate-rich sequence from the adenovirus fiber shaft: insights from molecular dynamics simulations and experiments.

The self-assembly of short peptides into fibrous nanostructures (such as fibrils and tubes) has recently become the subject of intense theoretical and experimental scrutiny, as such assemblies are promising candidates for nanobiotechnological applications. The sequences of natural fibrous proteins may provide a rich source of inspiration for the design of such short self-assembling peptides. We describe the self-assembly of the aspartate-rich undecapeptide (NH3(+)-LSGSDSDTLTV-NH2), a sequence derived from the shaft of the adenovirus fiber. We demonstrate that the peptide assembles experimentally into amyloid-type fibrils according to widely accepted diagnostic criteria. In addition, we investigate an aqueous solution of undecapeptides by molecular dynamics simulations with an implicit (GB) solvent model. The peptides are frequently arranged in intermolecular ß-sheets, in line with their amyloidogenic propensity. On the basis of both experimental and theoretical insights, we suggest possible structural models of the fibrils and their potential use as scaffolds for templating of inorganic materials.

Computational protein design: the Proteus software and selected applications.

We describe an automated procedure for protein design, implemented in a flexible software package, called Proteus. System setup and calculation of an energy matrix are done with the XPLOR modeling program and its sophisticated command language, supporting several force fields and solvent models. A second program provides algorithms to search sequence space. It allows a decomposition of the system into groups, which can be combined in different ways in the energy function, for both positive and negative design. The whole procedure can be controlled by editing 2-4 scripts. Two applications consider the tyrosyl-tRNA synthetase enzyme and its successful redesign to bind both O-methyl-tyrosine and D-tyrosine. For the latter, we present Monte Carlo simulations where the D-tyrosine concentration is gradually increased, displacing L-tyrosine from the binding pocket and yielding the binding free energy difference, in good agreement with experiment. Complete redesign of the Crk SH3 domain is presented. The top 10000 sequences are all assigned to the correct fold by the SUPERFAMILY library of Hidden Markov Models. Finally, we report the acid/base behavior of the SNase protein. Sidechain protonation is treated as a form of mutation; it is then straightforward to perform constant-pH Monte Carlo simulations, which yield good agreement with experiment. Overall, the software can be used for a wide range of application, producing not only native-like sequences but also thermodynamic properties with errors that appear comparable to other current software packages.

Novel compstatin family peptides inhibit complement activation by drusen-like deposits in human retinal pigmented epithelial cell cultures.

We have used a novel human retinal pigmented epithelial (RPE) cell-based model that mimics drusen biogenesis and the pathobiology of age-related macular degeneration to evaluate the efficacy of newly designed peptide inhibitors of the complement system. The peptides belong to the compstatin family and, compared to existing compstatin analogs, have been optimized to promote binding to their target, complement protein C3, and to enhance solubility by improving their polarity/hydrophobicity ratios. Based on analysis of molecular dynamics simulation data of peptide-C3 complexes, novel binding features were designed by introducing intermolecular salt bridge-forming arginines at the N-terminus and at position -1 of N-terminal dipeptide extensions. Our study demonstrates that the RPE cell assay has discriminatory capability for measuring the efficacy and potency of inhibitory peptides in a macular disease environment.

Helix formation by alanine-based peptides in pure water and electrolyte solutions: insights from molecular dynamics simulations.

Specific ion effects on oligopeptide conformations in solution are attracting strong research attention, because of their impact on the protein-folding problem and on several important biological-biotechnological applications. In this work, we have addressed specific effects of electrolytes on the tendency of oligopeptides toward formation and propagation of helical segments. We have used replica-exchange molecular dynamics (REMD) simulations to study the conformations of two short hydrophobic peptides [Ace-(AAQAA)3-Nme (AQ), and Ace-A8-Nme (A8)] in pure water and in aqueous solutions of sodium chloride (NaCl) and sodium iodide (NaI) with concentrations of 1 and 3 M. The average helicities of the AQ peptide have been analyzed to yield Lifson-Roig (LR) parameters for helix nucleation and helix propagation. The salt dependence of these parameters suggests that electrolytes tend to stabilize the helical conformations of short peptides by enhancing the helix nucleation parameter. The helical conformations of longer oligopeptides are destabilized in the presence of salts, however, because the helix propagation parameters are reduced by electrolytes. On top of this general trend, we observe a significant specific salt effect in these simulations. The hydrophobic iodide ion in NaI solutions has a high affinity for the peptide backbone, which reflects itself in an enhanced helix nucleation and a reduced helix propagation parameter with respect to pure water or NaCl solutions. The present work thus explains the computational evidence that electrolytes tend to stabilize the compact conformations of short peptides and destabilize them for longer peptides, and it also sheds additional light on the specific salt effects on compact peptide conformations.

Molecular dynamics in drug design: new generations of compstatin analogs.

We report the computational and rational design of new generations of potential peptide-based inhibitors of the complement protein C3 from the compstatin family. The binding efficacy of the peptides is tested by extensive molecular dynamics-based structural and physicochemical analysis, using 32 atomic detail trajectories in explicit water for 22 peptides bound to human, rat or mouse target protein C3, with a total of 257 ns. The criteria for the new design are: (i) optimization for C3 affinity and for the balance between hydrophobicity and polarity to improve solubility compared to known compstatin analogs; and (ii) development of dual specificity, human-rat/mouse C3 inhibitors, which could be used in animal disease models. Three of the new analogs are analyzed in more detail as they possess strong and novel binding characteristics and are promising candidates for further optimization. This work paves the way for the development of an improved therapeutic for age-related macular degeneration, and other complement system-mediated diseases, compared to known compstatin variants.

Specific interactions of sodium salts with alanine dipeptide and tetrapeptide in water: insights from molecular dynamics.

We examine computationally the dipeptide and tetrapeptide of alanine in pure water and solutions of sodium chloride (NaCl) and iodide (NaI), with salt concentrations up to 3 M. Enhanced sampling of the configuration space is achieved by the replica exchange method. In agreement with other works, we observe preferential sodium interactions with the peptide carbonyl groups, which are enhanced in the NaI solutions due to the increased affinity of the less hydrophilic iodide anion for the peptide methyl side-chains and terminal blocking groups. These interactions have been associated with a decrease in the helicities of more complex peptides. In our simulations, both salts have a small effect on the dipeptide, but consistently stabilize the intramolecular hydrogen-bonding interactions and "α-helical" conformations of the tetrapeptide. This behavior, and an analysis of the intermolecular interaction energies show that ion-peptide interactions, or changes in the peptide hydration due to salts, are not sufficient determining factors of the peptide conformational preferences. Additional simulations suggest that the observed stabilizing effect is not due to the employed force-field, and that it is maintained in short peptides but is reversed in longer peptides. Thus, the peptide conformational preferences are determined by an interplay of energetic and entropic factors, arising from the peptide sequence and length and the composition of the solution.