Water dynamics at the binding interface of four different HLA-A2-peptide complexes

Molecular dynamics study of naturally existing cavity couplings in proteins

Couplings between protein sub-structures are a common property of protein dynamics. Some of these couplings are especially interesting since they relate to function and its regulation. In this article we have studied the case of cavity couplings because cavities can host functional sites, allosteric sites, and are the locus of interactions with the cell milieu. We have divided this problem into two parts. In the first part, we have explored the presence of cavity couplings in the natural dynamics of 75 proteins, using 20 ns molecular dynamics simulations. For each of these proteins, we have obtained two trajectories around their native state. After applying a stringent filtering procedure, we found significant cavity correlations in 60% of the proteins. We analyze and discuss the structure origins of these correlations, including neighbourhood, cavity distance, etc. In the second part of our study, we have used longer simulations (≥100 ns) from the MoDEL project, to obtain a broader view of cavity couplings, particularly about their dependence on time. Using moving window computations we explored the fluctuations of cavity couplings along time, finding that these couplings could fluctuate substantially during the trajectory, reaching in several cases correlations above 0.25/0.5. In summary, we describe the structural origin and the variations with time of cavity couplings. We complete our work with a brief discussion of the biological implications of these results.

T-cell epitope vaccine design by immunoinformatics

Vaccination is generally considered to be the most effective method of preventing infectious diseases. All vaccinations work by presenting a foreign antigen to the immune system in order to evoke an immune response. The active agent of a vaccine may be intact but inactivated ('attenuated') forms of the causative pathogens (bacteria or viruses), or purified components of the pathogen that have been found to be highly immunogenic. The increased understanding of antigen recognition at molecular level has resulted in the development of rationally designed peptide vaccines. The concept of peptide vaccines is based on identification and chemical synthesis of B-cell and T-cell epitopes which are immunodominant and can induce specific immune responses. The accelerating growth of bioinformatics techniques and applications along with the substantial amount of experimental data has given rise to a new field, called immunoinformatics. Immunoinformatics is a branch of bioinformatics dealing with in silico analysis and modelling of immunological data and problems. Different sequence- and structure-based immunoinformatics methods are reviewed in the paper.

Dynamic influence of the two membrane-proximal immunoglobulin-like domains upon the peptide-binding platform domain in class I and class II major histocompatibility complexes: normal mode analysis

Major histocompatibility complexes (MHCs) mainly fall into class I and class II. The two classes have similar structures, with two membrane-proximal immunoglobulin-like domains and a peptide-binding platform domain, though their organizations are different. We simulated the dynamics of a whole and partial model deficient in either of the two membrane-proximal domains for class I and class II using normal mode analysis. Our study showed that the influence of the two membrane-proximal domains upon the dynamics of the platform domain were decisively different between class II and class I. Both membrane-proximal domains (the alpha2 and beta2 domains) of class II MHC, especially the alpha2 domain, influenced the most important pocket that accommodates a large hydrophobic anchor side chain of the N-terminal side of the bound peptide, though the pocket was not in the alpha2 domain neighborhood. By contrast, the two membrane-proximal domains (the alpha3 and beta2m domains) of class I MHC had little influence upon the most important pocket that accommodates the N-terminal residue of the bound peptide. These results suggest that the two membrane-proximal domains of class II MHC have a greater influence upon peptide-binding than those of class I MHC.

WATGEN: an algorithm for modeling water networks at protein-protein interfaces

Water molecules at protein-protein interfaces contribute to the close packing of atoms and ensure complementarity between the protein surfaces, as well as mediating polar interactions. Therefore, modeling of interface water is of importance in understanding the structural basis of biomolecular association. We present an algorithm, WATGEN, which predicts locations for water molecules at a protein-protein or protein-peptide interface, given the atomic coordinates of the protein and peptide. A key element of the WATGEN algorithm is the prediction of water sites that can form multiple hydrogen bonds that bridge the binding interface. Trial calculations were performed on water networks predicted by WATGEN at 126 protein-peptide interfaces (X-ray resolutions <or= 2.0 A), using different criteria for water placement. The energies of the predicted water networks were evaluated in AMBER8 and used in the choice of parameters for WATGEN. The 126 interfaces include 1264 experimentally determined bridging water sites, and the WATGEN algorithm predicts 72 and 88% of these sites within 1.5 and 2.0 A, respectively. The predicted number of water molecules at each interface was much higher than the number of water molecules identified experimentally. Therefore, random placement of the same number of water molecules as that predicted at each interface was performed as a control, and resulted in only 22 and 40% of water sites placed within 1.5 and 2.0 A of experimental sites, respectively. Based on these data, we conclude that WATGEN can accurately predict the location of water molecules at a protein-peptide interface, and this may be of value for understanding the energetics and specificity of biomolecular association.

Comprehensive epitope mapping of the Epstein-Barr virus latent membrane protein-2 in normal, non tumor-bearing individuals

Latent membrane protein (LMP)-2 is one of the Epstein-Barr virus (EBV)-encoded proteins consistently expressed by nasopharyngeal carcinoma (NPC). EBV-transformed lymphoblastoid cell lines (LCL) have been used in patients with NPC to induce LMP-2-recognizing T cell lines which have been in turn utilized for protein-wide mapping of T cell epitopes. However, comprehensive mapping of naturally recognized LMP-2 epitopes in non tumor-bearing individuals has not been reported. Here, we applied a low sensitivity epitope-defining technique for the identification of LMP-2 CTL responses detectable ex vivo in EBV-experienced individuals. This screening tool has been previously validated by analyzing memory CTL responses to Flu, cytomegalovirus (CMV), and the melanoma associated antigen gp100/Mel17. Peripheral blood monocytes (PBMC) from ten Caucasian and ten Chinese individuals were stimulated ex vivo with pools of nonamer (9-mer) peptides overlapping in a stepwise fashion each single amino acid of the LMP-2 sequence. No obvious differences were observed between the immune response of the two ethnic groups save for those related to the divergence in the ethnic prevalence of HLA haplotypes. Several novel and known LMP-2 epitopes were identified. Reactivity toward at least one LMP-2 epitope was detected in 18 of the 20 donors but no prevalent human leukocyte antigen (HLA)/epitope combination was observed confirming that LMP-2 reactivity in the context of common HLA alleles is more pleiotropic than that of FLU and CMV. We believe that the usefulness of these epitopes occurring naturally in non-cancer bearing patients as reagents for the immunization of patients with early or advanced stage NPC deserves further evaluation.

Comparative molecular dynamics analysis of tapasin-dependent and -independent MHC class I alleles

MHC class I molecules load antigenic peptides in the endoplasmic reticulum and present them at the cell surface. Efficiency of peptide loading depends on the class I allele and can involve interaction with tapasin and other proteins of the loading complex. Allele HLA-B*4402 (Asp at position 116) depends on tapasin for efficient peptide loading, whereas HLA-B*4405 (identical to B*4402 except for Tyr116) can efficiently load peptides in the absence of tapasin. Both alleles adopt very similar structures in the presence of the same peptide. Comparative unrestrained molecular dynamics simulations on the alpha(1)/alpha(2) peptide binding domains performed in the presence of bound peptides resulted in structures in close agreement with experiments for both alleles. In the absence of peptides, allele-specific conformational changes occurred in the first segment of the alpha(2)-helix that flanks the peptide C-terminal binding region (F-pocket) and contacts residue 116. This segment is also close to the proposed tapasin contact region. For B*4402, a shift toward an altered F-pocket structure deviating significantly from the bound form was observed. Subsequent free energy simulations on induced F-pocket opening in B*4402 confirmed a conformation that deviated significantly from the bound structure. For B*4405, a free energy minimum close to the bound structure was found. The simulations suggest that B*4405 has a greater tendency to adopt a peptide receptive conformation in the absence of peptide, allowing tapasin-independent peptide loading. A possible role of tapasin could be the stabilization of a peptide-receptive class I conformation for HLA-B*4402 and other tapasin-dependent alleles.

Structure-based prediction of MHC-peptide association: algorithm comparison and application to cancer vaccine design

Peptide vaccination for cancer immunotherapy requires identification of peptide epitopes derived from antigenic proteins associated with the tumor. Such peptides can bind to MHC proteins (MHC molecules) on the tumor-cell surface, with the potential to initiate a host immune response against the tumor. Computer prediction of peptide epitopes can be based on known motifs for peptide sequences that bind to a certain MHC molecule, on algorithms using experimental data as a training set, or on structure-based approaches. We have developed an algorithm, which we refer to as PePSSI, for flexible structural prediction of peptide binding to MHC molecules. Here, we have applied this algorithm to identify peptide epitopes (of nine amino acids, the common length) from the sequence of the cancer-testis antigen KU-CT-1, based on the potential of these peptides to bind to the human MHC molecule HLA-A2. We compared the PePSSI predictions with those of other algorithms and found that several peptides predicted to be strong HLA-A2 binders by PePSSI were similarly predicted by another structure-based algorithm, PREDEP. The results show how structure-based prediction can identify potential peptide epitopes without known binding motifs and suggest that side chain orientation in binding peptides may be obtained using PePSSI.

Structural prediction of peptides binding to MHC class I molecules

Peptide binding to class I major histocompatibility complex (MHCI) molecules is a key step in the immune response and the structural details of this interaction are of importance in the design of peptide vaccines. Algorithms based on primary sequence have had success in predicting potential antigenic peptides for MHCI, but such algorithms have limited accuracy and provide no structural information. Here, we present an algorithm, PePSSI (peptide-MHC prediction of structure through solvated interfaces), for the prediction of peptide structure when bound to the MHCI molecule, HLA-A2. The algorithm combines sampling of peptide backbone conformations and flexible movement of MHC side chains and is unique among other prediction algorithms in its incorporation of explicit water molecules at the peptide-MHC interface. In an initial test of the algorithm, PePSSI was used to predict the conformation of eight peptides bound to HLA-A2, for which X-ray data are available. Comparison of the predicted and X-ray conformations of these peptides gave RMSD values between 1.301 and 2.475 A. Binding conformations of 266 peptides with known binding affinities for HLA-A2 were then predicted using PePSSI. Structural analyses of these peptide-HLA-A2 conformations showed that peptide binding affinity is positively correlated with the number of peptide-MHC contacts and negatively correlated with the number of interfacial water molecules. These results are consistent with the relatively hydrophobic binding nature of the HLA-A2 peptide binding interface. In summary, PePSSI is capable of rapid and accurate prediction of peptide-MHC binding conformations, which may in turn allow estimation of MHCI-peptide binding affinity.

Secondary anchor substitutions in an HLA-A*0201-restricted T-cell epitope derived from Her-2/neu

We investigated analogues of GP2 (IISAVVGIL), an HLA-A*0201-restricted T-cell epitope derived from residues 654-662 in the tumor-associated antigen (TAA) Her-2/neu. One limiting factor of GP2 is its poor affinity for HLA-A*0201. Conformational analysis revealed the P5-P7 region in GP2 appears to be linked to the stability of P9 side chain interaction with the MHC molecule. To identify variants of GP2 with enhanced presentation to HLA-A*0201, we tested V6S, V6T, V6Q, G7P, G7F, T6F7, and Q6F7 for their capacity to stabilize cell surface HLA-A*0201 molecules. Of the mono-substituted variants, V6Q and G7F exhibited superior stabilization as compared to GP2. Molecular dynamics simulations suggest the improved binding can be attributed to concerted motions in the central and C-terminal regions of the peptide. These data support the notion that amino acids in HLA-A*0201 epitopes may be inter-dependent. Priming HLA-A*0201 transgenic mice with G7F-loaded syngeneic dendritic cells stimulated mouse T cells to produce a higher level of INFgamma than mice immunized with GP2.

Structural prediction of peptides bound to MHC class I

An ab initio structure prediction approach adapted to the peptide-major histocompatibility complex (MHC) class I system is presented. Based on structure comparisons of a large set of peptide-MHC class I complexes, a molecular dynamics protocol is proposed using simulated annealing (SA) cycles to sample the conformational space of the peptide in its fixed MHC environment. A set of 14 peptide-human leukocyte antigen (HLA) A0201 and 27 peptide-non-HLA A0201 complexes for which X-ray structures are available is used to test the accuracy of the prediction method. For each complex, 1000 peptide conformers are obtained from the SA sampling. A graph theory clustering algorithm based on heavy atom root-mean-square deviation (RMSD) values is applied to the sampled conformers. The clusters are ranked using cluster size, mean effective or conformational free energies, with solvation free energies computed using Generalized Born MV 2 (GB-MV2) and Poisson-Boltzmann (PB) continuum models. The final conformation is chosen as the center of the best-ranked cluster. With conformational free energies, the overall prediction success is 83% using a 1.00 Angstroms crystal RMSD criterion for main-chain atoms, and 76% using a 1.50 Angstroms RMSD criterion for heavy atoms. The prediction success is even higher for the set of 14 peptide-HLA A0201 complexes: 100% of the peptides have main-chain RMSD values < or =1.00 Angstroms and 93% of the peptides have heavy atom RMSD values < or =1.50 Angstroms. This structure prediction method can be applied to complexes of natural or modified antigenic peptides in their MHC environment with the aim to perform rational structure-based optimizations of tumor vaccines.

Conformational flexibility of the MHC class I alpha1-alpha2 domain in peptide bound and free states: a molecular dynamics simulation study

Major histocompatibility complex class I proteins play a key role in the recognition and presentation of peptide antigens to the host immune system. The structure of various major histocompatibility complex class I proteins has been determined experimentally in complex with several antigenic peptides. However, the structure in the unbound (empty) form is not known. To study the conformational dynamics of the empty major histocompatibility complex class I molecule comparative molecular dynamics simulations have been performed starting from the crystal structure of a peptide bound class I peptide-binding domain in the presence and absence of a peptide ligand. Simulations including the bound peptide stayed close to the experimental start structure at both simulation temperatures (300 and 355 K) during the entire simulation of 26 ns. Several independent simulations in the absence of peptide indicate that the empty domain may not adopt a single defined conformation but is conformationally significantly more heterogeneous in particular within the alpha-helices that flank the peptide binding cleft. The calculated conformational dynamics along the protein chain correlate well with available spectroscopic data and with the observed site-specific sensitivity of the empty class I protein to proteolytic digestion. During the simulations at 300 K the binding region for the peptide N-terminus stayed close to the conformation in the bound state, whereas the anchor region for the C-terminus showed significantly larger conformational fluctuations. This included a segment at the beginning of the second alpha-helix in the domain that is likely to be involved in the interaction with the chaperone protein tapasin during the peptide-loading process. The simulation studies further indicate that peptide binding at the C- and N-terminus may follow different mechanisms that involve different degrees of induced conformational changes in the peptide-binding domain. In particular binding of the peptide C-terminus may require conformational stabilization by chaperone proteins during peptide loading.

Large-scale molecular dynamics simulations of HLA-A*0201 complexed with a tumor-specific antigenic peptide: can the alpha3 and beta2m domains be neglected?

Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histocompatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVYDGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available for this study allow us to compare directly differences in the behavior of very large molecular models; in this case, the entire extracellular portion of the peptide-MHC complex vs. the isolated peptide binding domain. Comparison of the results from the partial and the whole system simulations indicates that the peptide is less tightly bound in the partial system than in the whole system. From a detailed study of conformations, solvent-accessible surface area, the nature of the water network structure, and the binding energies, we conclude that, when considering the conformation of the alpha1-alpha2 domain, the alpha3 and beta2m domains cannot be neglected.

MHC–Peptide Binding is Assisted by Bound Water Molecules

Water plays an important role in determining the high affinity of epitopes to the class I MHC complex. To study the energy and dynamics of water interactions in the complex we performed molecular dynamics simulation of the class I MHC-HLA2 complex bound to the HIV reverse transcriptase epitope, ILKEPVHGV, and in the absence of the epitope. Each simulation was extended for 5ns. We studied the processes of water penetration in the interface between MHC and peptide, and identified 14 water molecules that stay bound for periods longer than 1ns in regions previously identified by crystallography. These water molecules in the interface perform definite "tasks" contributing to the binding energy: hydrogen bond bridges between MHC and peptide and filling empty spaces in the groove which enhance affinity without contributing to epitope specificity. We calculate the binding energy for interfacial water molecules and find that there is an overall gain in free energy resulting from the formation of water clusters at the epitope-MHC interface. Water molecules serving the task of filling empty spaces bind at the interface with a net gain in entropy, relative to their entropy in bulk. We conclude that water molecules at the interface play the role of active mediators in the MHC-peptide interaction, and might be responsible for the large binding affinity of the MHC complex to a large number of epitope sequences.

Physicochemical explanation of peptide binding to HLA-A*0201 major histocompatibility complex: a three-dimensional quantitative structure-activity relationship study

A three-dimensional quantitative structure-activity relationship method for the prediction of peptide binding affinities to the MHC class I molecule HLA-A*0201 was developed by applying the CoMSIA technique on a set of 266 peptides. To increase the self consistency of the initial CoMSIA model, the poorly predicted peptides were excluded from the training set in a stepwise manner and then included in the study as a test set. The final model, based on 236 peptides and considering the steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond acceptor fields, had q2 = 0.683 and r2 = 0.891. The stability of this model was proven by cross-validations in two and five groups and by a bootstrap analysis of the non-cross-validated model. The residuals between the experimental pIC50 (-logIC50) values and those calculated by "leave-one-out" cross-validation were analyzed. According to the best model, 63.2% of the peptides were predicted with /residuals/ < or = 0.5 log unit; 29.3% with 1.0 < or = /residuals/ < 0.5; and 7.5% with /residuals/ > 1.0 log unit. The mean /residual/ value was 0.489. The coefficient contour maps identify the physicochemical property requirements at each position in the peptide molecule and suggest amino acid sequences for high-affinity binding to the HLA-A*0201 molecule.

Conserved water molecules in MHC class-I molecules and their putative structural and functional roles

A set of conserved water positions making direct contacts with the alpha1 and alpha2 domains of the MHC class-I protein was identified by a cluster analysis in 12 high-resolution crystal structures of proteins from different allele types and different species, comprising human, mouse and rat. The analysis revealed a total of 63 clusters, corresponding to water molecules, whose positions are conserved in half or more of the analyzed structures. Analysis of these clusters shows that the most conserved water positions-those appearing in the largest fraction of the structures-were also the most accurately defined, as measured by their normalized crystallographic B-factor. Not too surprisingly, these positions displayed better overlap and formed more H-bonds with the protein. In a second part of this work, a detailed analysis is presented of three of the most conserved water positions and their putative structural and functional roles are discussed. The most highly conserved of the three appears to play an important role in stabilizing the conformation of a twisted beta-turn between residues 118 and 122 (numbering of HLA-B3501, PDB code 1A1N). An equivalent water molecule was found to be associated with a similar beta-turn in 43 unrelated structures surveyed in the PDB, leading to the suggestion that this water molecule plays an important structural role in this type of turn. The second water molecule makes hydrogen bonds with residues lining pocket B in the peptide-binding groove and is suggested to play a role in modulating peptide recognition. The third highly conserved water molecule is located at the first kink of the alpha2 helix, possibly playing a role in determining the position of the N-terminal segment of that helix, which also carries side chains in contact with the bound peptide. This information on conserved water positions in MHC class-I molecules should be helpful in modeling interactions with bound peptide antigens and in designing new peptides with tailor-made affinities.

Rational design of peptide-based tumor vaccines

Administration of synthetic peptides derived from proteins uniquely or overexpressed in tumor cells (tumor-associated antigens) can elicit tumor-specific immune responses in vivo. This is because cytotoxic T lymphocytes can recognize and lyse tumor cells that display peptides derived from tumor-associated antigens (TAAs) in the context of class I major histocompatibility complex (MHC) molecules. TAA peptides, in contrast to peptides of viral origin, generally bind weakly to the MHC molecule. In many cases, this explains the poor magnitude of T cell response directed at the tumor in vivo. Improving MHC binding as a strategy to upregulate antigen recognition can convert low affinity TAA peptides into useful tools in clinical trial settings. High-resolution structures of class I MHC molecules reported over the past two decades provided the framework for designing peptides that can induce optimal T cell response. This review will discuss the basic and clinical aspects of modifying native TAA peptides as tumor vaccines.

Fine specificity analysis of an HLA-A2.1-restricted immunodominant T cell epitope derived from human alpha-fetoprotein

Human alpha-fetoprotein (AFP) is a potentially important target for the immunotherapy of hepatocellular carcinoma (HCC). AFP(542-550) (GVALQTMKQ) is one of several HLA-A2.1-restricted immunodominant AFP peptides that consistently generate AFP-specific T cell responses in human T cell cultures and in HLA-A2.1/K(b) transgenic (A2.1 tg) mice. We performed a fine specificity analysis of this nonamer to determine which amino acid side chains were critical for T cell priming and recognition. Using peptide-pulsed dendritic cells (DC) as an immunization strategy, we characterized the effects of AFP(542-550) amino acid substitutions on priming and recognition in A2.1 tg mice. Replacing the glutamine at anchor position 9 with a leucine enhanced MHC binding and AFP-specific T cell responses. Substitution of leucine at non-anchor position 4 with an alanine did not alter binding but greatly diminished T cell recognition. Computer-generated three-dimensional models provided the structural rationale for these observed effects in MHC binding and T cell responses resulted from the modifications in the AFP(542-550) sequence.