Computational design of peptide ligands

Peptides possess several attractive features when compared to small molecule and protein therapeutics, such as high structural compatibility with target proteins, the ability to disrupt protein-protein interfaces, and small size. Efficient design of high-affinity peptide ligands via rational methods has been a major obstacle to the development of this potential drug class. However, structural insights into the architecture of protein-peptide interfaces have recently culminated in several computational approaches for the rational design of peptides that target proteins. These methods provide a valuable alternative to experimental high-resolution structures of target protein-peptide complexes, bringing closer the dream of in silico designed peptides for therapeutic applications.     

o-Nitrotyrosine and p-iodophenylalanine as spectroscopic probes for structural characterization of SH3 complexes

High-throughput screening of protein-protein and protein-peptide interactions is of high interest both for biotechnological and pharmacological applications. Here, we propose the use of the noncoded amino acids o-nitrotyrosine and p-iodophenylalanine as spectroscopic probes in combination with circular dichroism and fluorescence quenching techniques (i.e., collisional quenching and resonance energy transfer) as a means to determine the peptide orientation in complexes with SH3 domains. Proline-rich peptides bind SH3 modules in two alternative orientations, according to their sequence motifs, classified as class I and class II. The method was tested on an SH3 domain from a yeast myosin that is known to recognize specifically class I peptides. We exploited the fluorescence quenching effects induced by o-nitrotyrosine and p-iodophenylalanine on the fluorescence signal of a highly conserved Trp residue, which is the signature of SH3 domains and sits directly in the binding pocket. In particular, we studied how the introduction of the two probes at different positions of the peptide sequence (i.e., N-terminally or C-terminally) influences the spectroscopic properties of the complex. This approach provides clear-cut evidence of the orientation of the binding peptide in the SH3 pocket. The chemical strategy outlined here can be easily extended to other protein modules, known to bind linear sequence motifs in a highly directional manner.     

Structural resiliency of an EGF-like subdomain bound to its target protein, thrombin.

The thrombin-bound structures of native peptide fragments from the fifth EGF-like domain of thrombomodulin were determined by use of NMR and transferred NOE spectroscopy. The bound peptides assume an EGF-like structure of an antiparallel beta-sheet, a novel structural motif observed for a bound peptide in protein-peptide complexes. There is a remarkable structural resiliency of this structure motif manifested in its ability to accommodate a different number of residues within the disulfide loop. Docking experiments revealed that the key contacts with thrombin are hydrophobic interactions between the side chains of residues Ile 414 and Ile 424 of thrombomodulin and a hydrophobic pocket on the thrombin surface. Residues Leu 415, Phe 419, and Ile 420, which would have been buried in intact EGF-like domains, are unfavorably exposed in the complex of thrombin with the EGF-like thrombomodulin fragment, thus providing a rationale for the enhancement of binding affinity upon the deletion of Ile 420. The unique beta-sheet structures of the bound peptides are specified by the presence of disulfide bridges in the peptides because a corresponding linear thrombomodulin fragment folds into a sheet structure with a different backbone topology. The different bound conformations for the linear and the cyclized peptides indicate that side-chain interactions within a specific environment may dictate the folding of bound peptides in protein-peptide complexes.     

Binding of longer peptides to the H-2Kb heterodimer is restricted to peptides extended at their C terminus: refinement of the inherent MHC class I peptide binding criteria.

MHC class I molecules usually bind short peptides of 8-10 amino acids, and binding is dependent on allele-specific anchor residues. However, in a number of cellular systems, class I molecules have been found containing peptides longer than the canonical size. To understand the structural requirements for MHC binding of longer peptides, we used an in vitro class I MHC folding assay to examine peptide variants of the antigenic VSV 8 mer core peptide containing length extensions at either their N or C terminus. This approach allowed us to determine the ability of each peptide to productively form Kb/beta2-microglobulin/peptide complexes. We found that H-2Kb molecules can accommodate extended peptides, but only if the extension occurs at the C-terminal peptide end, and that hydrophobic flanking regions are preferred. Peptides extended at their N terminus did not promote productive formation of the trimolecular complex. A structural basis for such findings comes from molecular modeling of a H-2Kb/12 mer complex and comparative analysis of MHC class I structures. These analyses revealed that structural constraints in the A pocket of the class I peptide binding groove hinder the binding of N-terminal-extended peptides, whereas structural features at the C-terminal peptide residue pocket allow C-terminal peptide extensions to reach out of the cleft. These findings broaden our understanding of the inherent peptide binding and epitope selection criteria of the MHC class I molecule. Core peptides extended at their N terminus cannot bind, but peptide extensions at the C terminus are tolerated.     

A Unified Conformational Selection and Induced Fit Approach to Protein-Peptide Docking

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.     

In silico analysis of peptide binding features of HLA-B*4006

HLA-B*4006 is the most common allele amongst Indians. It belongs to the 'HLA-B44 supertype' family of alleles that constitute an important component of the peptide binding repertoire in populations world over. Its peptide binding characteristics remain poorly examined. The amino acid sequence and structural considerations suggest a small, poorly hydrophobic 'F' pocket for this allele that may adversely affect the interaction with the C terminal residue of the antigenic peptide. Contribution of auxiliary anchor residues (P3) of the peptide has also been indicated. To examine these aspects by in silico analysis, HLA-B*4001, 4002, and 4006 alleles were modeled using HLA-B*4402 as a template. Eleven peptides, known to bind alleles of this family, were used for docking and molecular dynamics studies. Interaction between the amino group (main-chain) of P3 residue and Tyr99 of the alleles was seen in majority of peptide-complexes. Hydrophobic interactions between Tyr7 and Tyr159 with N terminal residues of the peptide were also seen in all the complexes. Replacement of Trp95 by leucine in HLA-B*4006 resulted in reduction of binding free energy in 8 out of 9 complexes. In summary, the analysis of the modeled structures and HLA-peptide complexes strongly supports the adverse effect of Trp95 at pocket F and the possible role of the third residue of the antigenic peptide as an auxiliary anchor in HLA-B*4006 peptide complexes. In the light of suggested promiscuous peptide binding pattern and association with risk for tuberculosis/HIV for this allele, the ascertainment of the predicted effects of Trp95 and role of P3 residue as an auxiliary anchor by this preliminary in silico analysis thus helps define direction of the further studies.     

Empirical calculation of the relative free energies of peptide binding to the molecular chaperone DnaK

We describe a methodology to calculate the relative free energies of protein-peptide complex formation. The interaction energy was decomposed into nonpolar, electrostatic and entropic contributions. A free energy-surface area relationship served to calculate the nonpolar free energy term. The electrostatic free energy was calculated with the finite difference Poisson-Boltzmann method and the entropic contribution was estimated from the loss in the conformational entropy of the peptide side chains. We applied this methodology to a series of DnaK*peptide complexes. On the basis of the single known crystal structure of the peptide-binding domain of DnaK with a bound heptapeptide, we modeled ten other DnaK*heptapeptide complexes with experimentally measured K(d) values from 0.06 microM to 11 microM, using molecular dynamics to refine the structures of the complexes. Molecular dynamic trajectories, after equilibration, were used for calculating the energies with greater accuracy. The calculated relative binding free energies were compared with the experimentally determined free energies. Linear scaling of the calculated terms was applied to fit them to the experimental values. The calculated binding free energies were between -7.1 kcal/mol and - 9.4 kcal/mol with a correlation coefficient of 0.86. The calculated nonpolar contributions are mainly due to the central hydrophobic binding pocket of DnaK for three amino acid residues. Negative electrostatic fields generated by the protein increase the binding affinity for basic residues flanking the hydrophobic core of the peptide ligand. Analysis of the individual energy contributions indicated that the nonpolar contributions are predominant compared to the other energy terms even for peptides with low affinity and that inclusion of the change in conformational entropy of the peptide side chains does not improve the discriminative power of the calculation. The method seems to be useful for predicting relative binding energies of peptide ligands of DnaK and might be applicable to other protein-peptide systems, particularly if only the structure of one protein-ligand complex is available.     

Modulating calmodulin binding specificity through computational protein design

We report the computational redesign of the protein-binding interface of calmodulin (CaM), a small, ubiquitous Ca(2+)-binding protein that is known to bind to and regulate a variety of functionally and structurally diverse proteins. The CaM binding interface was optimized to improve binding specificity towards one of its natural targets, smooth muscle myosin light chain kinase (smMLCK). The optimization was performed using optimization of rotamers by iterative techniques (ORBIT), a protein design program that utilizes a physically based force-field and the Dead-End Elimination theorem to compute sequences that are optimal for a given protein scaffold. Starting from the structure of the CaM-smMLCK complex, the program considered 10(22) amino acid residue sequences to obtain the lowest-energy CaM sequence. The resulting eightfold mutant, CaM_8, was constructed and tested for binding to a set of seven CaM target peptides. CaM_8 displayed high binding affinity to the smMLCK peptide (1.3nM), similar to that of the wild-type protein (1.8nM). The affinity of CaM_8 to six other target peptides was reduced, as intended, by 1.5-fold to 86-fold. Hence, CaM_8 exhibited increased binding specificity, preferring the smMLCK peptide to the other targets. Studies of this type may increase our understanding of the origins of binding specificity in protein-ligand complexes and may provide valuable information that can be used in the design of novel protein receptors and/or ligands.     

Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods

Given the importance of protein-protein interactions for nearly all biological processes, the design of protein affinity reagents for use in research, diagnosis or therapy is an important endeavor. Engineered proteins would ideally have high specificities for their intended targets, but achieving interaction specificity by design can be challenging. There are two major approaches to protein design or redesign. Most commonly, proteins and peptides are engineered using experimental library screening and/or in vitro evolution. An alternative approach involves using protein structure and computational modeling to rationally choose sequences predicted to have desirable properties. Computational design has successfully produced novel proteins with enhanced stability, desired interactions and enzymatic function. Here we review the strengths and limitations of experimental library screening and computational structure-based design, giving examples where these methods have been applied to designing protein interaction specificity. We highlight recent studies that demonstrate strategies for combining computational modeling with library screening. The computational methods provide focused libraries predicted to be enriched in sequences with the properties of interest. Such integrated approaches represent a promising way to increase the efficiency of protein design and to engineer complex functionality such as interaction specificity.     

Anti-apoptotic Bcl-XL protein in complex with BH3 peptides of pro-apoptotic Bak, Bad, and Bim proteins: comparative molecular dynamics simulations

The Bcl-2 family of proteins plays a central role in the regulation of mitochondrial outer-membrane permeabilization, a critical step in apoptosis. Heterodimerization between the pro- and anti-apoptotic members of Bcl-2 family is a key event in this process. Anti-apoptotic proteins have high levels of expression in many cancers and they have different affinities for different pro-apoptotic proteins. Experimentally determined structures of all members of Bcl-2 proteins have remarkably similar helical fold despite poor amino acid sequence identity. Peptides representing BH3 region of pro-apoptotic proteins have been shown to bind the hydrophobic cleft of anti-apoptotic proteins and this segment is responsible in modulating the apoptotic pathways in living cells. Understanding the molecular basis of protein-protein recognition is required to develop inhibitors specific to a particular anti-apoptotic protein. We have carried out molecular dynamics simulations on the anti-apoptotic Bcl-X(L) protein in complex with three different BH3 peptides derived from pro-apoptotic Bak, Bad and Bim proteins. Each complex structure was simulated for a period of 50 ns after 2.5 ns equilibration. Analysis of the simulation results showed that in the Bcl-X(L) protein, the helix containing the BH3 region is more flexible than other helices in all three simulations. A network of strong hydrophobic interactions exists between four of the six helices and they contribute significantly to the stability of this helix bundle protein. Analysis of Bcl-X(L)-BH3 peptide interactions reveals the role of loop residues in the protein-peptide interactions in all three simulations. Bad and Bim peptides maintain strong hydrophobic and hydrophilic interactions with the helix preceding the central hydrophobic helix. Residues from this helix interact with an Arg residue in Bad and Bim peptides. This Arg residue is next to the conserved Leu residue and is replaced by Ala in Bak. Absence of these interactions and the helix propensity are likely to be the cause for Bak peptide's weaker binding affinity with the Bcl-X(L) protein. The results of this study have implications in the design of Bcl-X(L)-specific inhibitors.     

Structural and dynamic determinants of protein-peptide recognition

Protein-peptide interactions play important roles in many cellular processes, including signal transduction, trafficking, and immune recognition. Protein conformational changes upon binding, an ill-defined peptide binding surface, and the large number of peptide degrees of freedom make the prediction of protein-peptide interactions particularly challenging. To address these challenges, we perform rapid molecular dynamics simulations in order to examine the energetic and dynamic aspects of protein-peptide binding. We find that, in most cases, we recapitulate the native binding sites and native-like poses of protein-peptide complexes. Inclusion of electrostatic interactions in simulations significantly improves the prediction accuracy. Our results also highlight the importance of protein conformational flexibility, especially side-chain movement, which allows the peptide to optimize its conformation. Our findings not only demonstrate the importance of sufficient sampling of the protein and peptide conformations, but also reveal the possible effects of electrostatics and conformational flexibility on peptide recognition.     

Binding of antigenic peptide to the endoplasmic reticulum-resident protein gp96/GRP94 heat shock chaperone occurs in higher order complexes. Essential role of some aromatic amino acid residues in the peptide-binding site

Vaccination with heat shock protein gp96-antigenic peptide complexes produces a powerful specific immune response against cancers and infectious diseases in some experimental animal models, and gp96-peptide complexes are now being tested in human clinical trials. gp96 appears to serve as a natural adjuvant for chaperoning antigenic peptides into the immune surveillance pathways. A fundamental issue that needs to be addressed is the mechanism of binding of antigenic peptide to gp96. Here, we show using scanning transmission electron microscopy that recombinant gp96 binds peptide in stable multimeric complexes, which may have biological significance. To open the possibility for genetically engineering gp96 for improved immunogenicity and to understand if molecular recognition plays a role in the binding of antigenic peptide, we mutagenized some specific aromatic amino acids in the presumed peptide-binding pocket. Replacement of Tyr-667 or Tyr-678 to Ala reduced affinity for peptide whereas conversion of Trp-654 to Tyr increased peptide binding. Similarly, changing Trp-621 to Phe or Leu or Ala or Ile negatively affected peptide binding whereas changing Trp-621 to Tyr or Val positively affected peptide binding. Probing the peptide microenvironment in gp96-peptide complexes, suggested that hydrophobic interactions (and perhaps hydrogen bonding/stacking interactions) may play a role in peptide loading by gp96.     

Computational design of calmodulin mutants with up to 900-fold increase in binding specificity

Calmodulin (CaM) is a ubiquitous second messenger protein that regulates a variety of structurally and functionally diverse targets in response to changes in Ca²⁺ concentration. CaM-dependent protein kinase II (CaMKII) and calcineurin (CaN) are the prominent CaM targets that play an opposing role in many cellular functions including synaptic regulation. Since CaMKII and CaN compete for the available Ca²⁺/CaM, the differential affinity of these enzymes for CaM is crucial for achieving a balance in Ca²⁺ signaling. We used the computational protein design approach to modify CaM binding specificity for these two targets. Starting from the X-ray structure of CaM in complex with the CaM-binding domain of CaMKII, we optimized CaM interactions with CaMKII by introducing mutations into the CaM sequence. CaM optimization was performed with a protein design program, ORBIT, using a modified energy function that emphasized intermolecular interactions in the sequence selection procedure. Several CaM variants were experimentally constructed and tested for binding to the CaMKII and CaN peptides using the surface plasmon resonance technique. Most of our CaM mutants demonstrated small increase in affinity for the CaMKII peptide and substantial decrease in affinity for the CaN peptide compared to that of wild-type CaM. Our best CaM design exhibited an about 900-fold increase in binding specificity towards the CaMKII peptide, becoming the highest specificity switch achieved in any protein-protein interface through the computational protein design approach. Our results show that computational redesign of protein-protein interfaces becomes a reliable method for altering protein binding affinity and specificity.     

VitAL: Viterbi Algorithm for de novo Peptide Design

Background

Drug design against proteins to cure various diseases has been studied for several years. Numerous design techniques were discovered for small organic molecules for specific protein targets. The specificity, toxicity and selectivity of small molecules are hard problems to solve. The use of peptide drugs enables a partial solution to the toxicity problem. There has been a wide interest in peptide design, but the design techniques of a specific and selective peptide inhibitor against a protein target have not yet been established.

Methodology/Principal Findings

A novel de novo peptide design approach is developed to block activities of disease related protein targets. No prior training, based on known peptides, is necessary. The method sequentially generates the peptide by docking its residues pair by pair along a chosen path on a protein. The binding site on the protein is determined via the coarse grained Gaussian Network Model. A binding path is determined. The best fitting peptide is constructed by generating all possible peptide pairs at each point along the path and determining the binding energies between these pairs and the specific location on the protein using AutoDock. The Markov based partition function for all possible choices of the peptides along the path is generated by a matrix multiplication scheme. The best fitting peptide for the given surface is obtained by a Hidden Markov model using Viterbi decoding. The suitability of the conformations of the peptides that result upon binding on the surface are included in the algorithm by considering the intrinsic Ramachandran potentials.

Conclusions/Significance

The model is tested on known protein-peptide inhibitor complexes. The present algorithm predicts peptides that have better binding energies than those of the existing ones. Finally, a heptapeptide is designed for a protein that has excellent binding affinity according to AutoDock results.     

Computational design and experimental study of tighter binding peptides to an inactivated mutant of HIV-1 protease

Drug resistance in HIV-1 protease, a barrier to effective treatment, is generally caused by mutations in the enzyme that disrupt inhibitor binding but still allow for substrate processing. Structural studies with mutant, inactive enzyme, have provided detailed information regarding how the substrates bind to the protease yet avoid resistance mutations; insights obtained inform the development of next generation therapeutics. Although structures have been obtained of complexes between substrate peptide and inactivated (D25N) protease, thermodynamic studies of peptide binding have been challenging due to low affinity. Peptides that bind tighter to the inactivated protease than the natural substrates would be valuable for thermodynamic studies as well as to explore whether the structural envelope observed for substrate peptides is a function of weak binding. Here, two computational methods-namely, charge optimization and protein design-were applied to identify peptide sequences predicted to have higher binding affinity to the inactivated protease, starting from an RT-RH derived substrate peptide. Of the candidate designed peptides, three were tested for binding with isothermal titration calorimetry, with one, containing a single threonine to valine substitution, measured to have more than a 10-fold improvement over the tightest binding natural substrate. Crystal structures were also obtained for the same three designed peptide complexes; they show good agreement with computational prediction. Thermodynamic studies show that binding is entropically driven, more so for designed affinity enhanced variants than for the starting substrate. Structural studies show strong similarities between natural and tighter-binding designed peptide complexes, which may have implications in understanding the molecular mechanisms of drug resistance in HIV-1 protease.     

Epitope‐specificity of recombinant antibodies reveals promiscuous peptide‐binding properties

Protein–peptide interactions are a common occurrence and essential for numerous cellular processes, and frequently explored in broad applications within biology, medicine, and proteomics. Therefore, understanding the molecular mechanism(s) of protein–peptide recognition, specificity, and binding interactions will be essential. In this study, we report the first detailed analysis of antibody–peptide interaction characteristics, by combining large‐scale experimental peptide binding data with the structural analysis of eight human recombinant antibodies and numerous peptides, targeting tryptic mammalian and eukaryote proteomes. The results consistently revealed that promiscuous peptide‐binding interactions, that is, both specific and degenerate binding, were exhibited by all antibodies, and the discovery was corroborated by orthogonal data, indicating that this might be a general phenomenon for low‐affinity antibody–peptide interactions. The molecular mechanism for the degenerate peptide‐binding specificity appeared to be executed through the use of 2–3 semi‐conserved anchor residues in the C‐terminal part of the peptides, in analogue to the mechanism utilized by the major histocompatibility complex–peptide complexes. In the long‐term, this knowledge will be instrumental for advancing our fundamental understanding of protein–peptide interactions, as well as for designing, generating, and applying peptide specific antibodies, or peptide‐binding proteins in general, in various biotechnical and medical applications.     

NMR structure of alpha-bungarotoxin free and bound to a mimotope of the nicotinic acetylcholine receptor

A combinatorial library approach was used to produce synthetic peptides mimicking the snake neurotoxin binding site of nicotinic receptors. Among the sequences, which inhibited binding of alpha-bungarotoxin to muscle and neuronal nicotinic receptors, HRYYESSLPWYPD, a 14-amino acid peptide with considerably higher toxin-binding affinity than the other synthesized peptides, was selected, and the structure of its complex with the toxin was analyzed by NMR. Comparison of the solution structure of the free toxin and its complex with this peptide indicated that complex formation induced extensive conformational rearrangements mainly at finger II and the carboxy terminus of the protein. The peptidyl residues P10 and Y4 seemed to be critical for peptide folding and complex stability, respectively. The latter residue of the peptide strongly interacted with the protein by entering a small pocket delimited by D30, C33, S34, R36, and V39 toxin side chains.     

Reexamination of the recognition preference of the specificity pocket of the Abl SH3 domain

Src homology-3 (SH3) domains mediate important protein-protein interactions in a variety of normal and pathological cellular processes, thus providing an attractive target for the selective interference of SH3-dependent signaling events that govern these processes. Most SH3 domains recognize proline-rich peptides with low affinity and poor selectivity, and the goal to design potent and specific ligands for various SH3 domains remains elusive. Better understanding of the molecular basis for SH3 domain recognition is needed in order to design such ligands with potency and specificity. In this report, we seek to define a clear recognition preference of the specificity pocket of the Abl SH3 domain using targeted synthetic peptide libraries. High-resolution affinity panning coupled with mass spectrometric readout allows for quick identification of Trp as the preferred fourth residue in the decapeptide ligand APTWSPPPPP, which binds to Abl SH3 four times stronger than does the decapeptide containing Tyr or Phe in the fourth position. This finding is in contrast to several reports that Tyr is the only residue selected from phage displayed peptide libraries that interacts with the specificity pocket of Abl SH3. This simple, unbiased approach can fine-tune the affinity and selectivity of both natural and unnatural SH3 ligands whose consensus binding sequence has been pre-defined by combinatorial library methods.