HLA-DP2 binding prediction by molecular dynamics simulations

Major histocompatibility complex (MHC) II proteins bind peptide fragments derived from pathogen antigens and present them at the cell surface for recognition by T cells. MHC proteins are divided into Class I and Class II. Human MHC Class II alleles are grouped into three loci: HLA-DP, HLA-DQ, and HLA-DR. They are involved in many autoimmune diseases. In contrast to HLA-DR and HLA-DQ proteins, the X-ray structure of the HLA-DP2 protein has been solved quite recently. In this study, we have used structure-based molecular dynamics simulation to derive a tool for rapid and accurate virtual screening for the prediction of HLA-DP2-peptide binding. A combinatorial library of 247 peptides was built using the "single amino acid substitution" approach and docked into the HLA-DP2 binding site. The complexes were simulated for 1 ns and the short range interaction energies (Lennard-Jones and Coulumb) were used as binding scores after normalization. The normalized values were collected into quantitative matrices (QMs) and their predictive abilities were validated on a large external test set. The validation shows that the best performing QM consisted of Lennard-Jones energies normalized over all positions for anchor residues only plus cross terms between anchor-residues.     

Candidate epitope identification using peptide property models: application to cancer immunotherapy

Peptides derived from pathogens or tumors are selectively presented by the major histocompatibility complex proteins (MHC) to the T lymphocytes. Antigenic peptide-MHC complexes on the cell surface are specifically recognized by T cells and, in conjunction with co-factor interactions, can activate the T cells to initiate the necessary immune response against the target cells. Peptides that are capable of binding to multiple MHC molecules are potential T cell epitopes for diverse human populations that may be useful in vaccine design. Bioinformatical approaches to predict MHC binding peptides can facilitate the resource-consuming effort of T cell epitope identification. We describe a new method for predicting MHC binding based on peptide property models constructed using biophysical parameters of the constituent amino acids and a training set of known binders. The models can be applied to development of anti-tumor vaccines by scanning proteins over-expressed in cancer cells for peptides that bind to a variety of MHC molecules. The complete algorithm is described and illustrated in the context of identifying candidate T cell epitopes for melanomas and breast cancers. We analyzed MART-1, S-100, MBP, and CD63 for melanoma and p53, MUC1, cyclin B1, HER-2/neu, and CEA for breast cancer. In general, proteins over-expressed in cancer cells may be identified using DNA microarray expression profiling. Comparisons of model predictions with available experimental data were assessed. The candidate epitopes identified by such a computational approach must be evaluated experimentally but the approach can provide an efficient and focused strategy for anti-cancer immunotherapy development.     

Circular dichroism determination of class I MHC-peptide equilibrium dissociation constants

Class I major histocompatibility complex (MHC) molecules bind peptides derived from degraded proteins for display to T cells of the immune system. Peptides bind to MHC proteins with varying affinities, depending upon their sequence and length. We demonstrate that the thermal stability of the MHC-peptide complex depends directly on peptide binding affinity. We use this correlation to develop a convenient method to determine peptide dissociation constants by measuring MHC-peptide complex stability using thermal denaturation profiles monitored by circular dichroism.     

Cysteinylation of MHC class II ligands: peptide endocytosis and reduction within APC influences T cell recognition

Peptides bind cell surface MHC class II proteins to yield complexes capable of activating CD4(+) T cells. By contrast, protein Ags require internalization and processing by APC before functional presentation. Here, T cell recognition of a short peptide in the context of class II proteins occurred only after delivery of this ligand to mature endosomal/lysosomal compartments within APC. Functional and biochemical studies revealed that a central cysteine within the peptide was cysteinylated, perturbing T cell recognition of this epitope. Internalization and processing of the modified epitope by APC, was required to restore T cell recognition. Peptide cysteinylation and reduction could occur rapidly and reversibly before MHC binding. Cysteinylation did not disrupt peptide binding to class II molecules, rather the modified peptide displayed an enhanced affinity for MHC at neutral pH. However, once the peptide was bound to class II proteins, oxidation or reduction of cysteine residues was severely limited. Cysteinylation has been shown to radically influence T cell responses to MHC class I ligands. The ability of professional APC to reductively cleave this peptide modification presumably evolved to circumvent a similar problem in MHC class II ligand recognition.     

pH stability of HLA-DR4 complexes with antigenic peptides

Complexes between antigenic peptides and class II proteins of the major histocompatibility complex (MHC) trigger cellular immune responses. These complexes usually dissociate more rapidly at mildly acidic pH, where they are formed intracellularly, as compared to neutral pH, where they function at the cell surface. This paper describes the pH dependence of the dissociation kinetics of complexes between MHC proteins and antigenic peptides containing aspartic and glutamic acid residues. Some of these complexes show an unusual pH dependence, dissociating much more rapidly at pH 7 than at pH 5.3. This occurs when the carboxylate group of the aspartic or glutamic acid residue is located in a neutral pocket of the protein. In contrast, solvent-exposed carboxylate groups or carboxylate groups buried in pockets where they form salt bridges with the protein do not show this unusual pH dependence. The kinetic data having the unusual pH dependence conform closely to a model in which there is a rapid reversible equilibration between a less stable deprotonated complex and a more stable protonated complex. In this model, the pK(a) of the protonation reaction for the partially buried peptide carboxylate group ranges from 7.7 to 8.3, reflecting the strongly basic conditions required for deprotonation. One of the few peptide/MHC complexes demonstrated to play a role in autoimmunity in humans contains a buried peptide carboxylate and shows this unusual pH dependence. The relevance of this finding to understanding the chemical basis of autoimmunity is briefly discussed.     

Recombinant HLA-DP2 binds beryllium and tolerizes beryllium-specific pathogenic CD4+ T cells

Chronic beryllium disease is a lung disorder caused by beryllium exposure in the workplace and is characterized by granulomatous inflammation and the accumulation of beryllium-specific, HLA-DP2-restricted CD4+ T lymphocytes in the lung that proliferate and secrete Th1-type cytokines. To characterize the interaction among HLA-DP2, beryllium, and CD4+ T cells, we constructed rHLA-DP2 and rHLA-DP4 molecules consisting of the alpha-1 and beta-1 domains of the HLA-DP molecules genetically linked into single polypeptide chains. Peptide binding to rHLA-DP2 and rHLA-DP4 was consistent with previously published peptide-binding motifs for these MHC class II molecules, with peptide binding dominated by aromatic residues in the P1 pocket. 9Be nuclear magnetic resonance spectroscopy showed that beryllium binds to the HLA-DP2-derived molecule, with no binding to the HLA-DP4 molecule that differs from DP2 by four amino acid residues. Using beryllium-specific CD4+ T cell lines derived from the lungs of chronic beryllium disease patients, beryllium presentation to those cells was independent of Ag processing because fixed APCs were capable of presenting BeSO4 and inducing T cell proliferation. Exposure of beryllium-specific CD4+ T cells to BeSO4 -pulsed, plate-bound rHLA-DP2 molecules induced IFN-gamma secretion. In addition, pretreatment of beryllium-specific CD4+ T cells with BeSO4-pulsed, plate-bound HLA-DP2 blocked proliferation and IL-2 secretion upon re-exposure to beryllium presented by APCs. Thus, the rHLA-DP2 molecules described herein provide a template for engineering variants that retain the ability to tolerize pathogenic CD4+ T cells, but do so in the absence of the beryllium Ag.     

Crystal structure analysis of oxidized Pseudomonas aeruginosa azurin at pH 5.5 and pH 9.0. A pH-induced conformational transition involves a peptide bond flip

The X-ray crystal structure of recombinant wild-type azurin from Pseudomonas aeruginosa was determined by difference Fourier techniques using phases derived from the structure of the mutant His35Leu. Two data sets were collected from a single crystal of oxidized azurin soaked in mother liquor buffered at pH 5.5 and pH 9.0, respectively. Both data sets extend to 1.93 A resolution. The two pH forms were refined independently to crystallographic R-factors of 17.6% (pH 5.5) and 17.5% (pH 9.0). The conformational transition previously attributed to the protonation/deprotonation of residue His35 (pKa(red) = 7.3, pKa(ox) = 6.2), which lies in a crevice of the protein close to the copper binding site, involves a concomitant Pro36-Gly37 main-chain peptide bond flip. At the lower pH, the protonated imidazole N delta 1 of His35 forms a strong hydrogen bond with the carbonyl oxygen from Pro36, while at alkaline pH the deprotonated N delta 1 acts as an acceptor of a weak hydrogen bond from HN Gly37. The structure of the remainder of the azurin molecule, including the copper binding site, is not significantly affected by this transition.     

A study of the mechanism of ferritin formation. The effect of pH, ionic strength and temperature, inhibition by imidazole and kinetic analysis

The rate of ferritin formation in the buffers 4-morpholinepropanesulphonic acid (Mops), 4-morpholineethanesulphonic acid (Mes) and imidazole at pH values from 5.0 to 6.5 is quite similar. However, the rate of iron deposition is much greater in Mops and Mes at pH values above 6.5 than in imidazole. Increasing the concentration of imidazole inhibits ferritin formation and also leads to a transformation in the shape of the kinetic curves observed. This inhibiton is also observed at constant ionic strength but is not found for non-complexing buffers such as Mops. An inhibition of ferritin formation in imidazole and in Mops buffers is also observed with increasing ionic strength. We conclude that the unprotonated form of imidazole inhibits iron deposition, possibly by binding to the active site of the apoferritin molecule. The temperature dependence of iron deposition was examined. An optimum temperature of 50 degrees C was found but the Arrhenius plots were non-linear. On the basis of these and previous results, a kinetic model is developed which accounts well for ferritin formation at pH values below 6.5 and above 7.0 in non-complexing buffers. The model does not account for the kinetics observed at pH values close to neutrality.     

Binding of adenovirus and its external proteins to Triton X-114. Dependence on pH

35S-Labeled adenovirus type 2 (Ad2) (10 ng/ml) was incubated with 1% Triton X-114 at various pH values varying from 3.0 to 8.0. The detergent phase was separated from the aqueous phase by centrifugation, and the amounts of Ad2 were determined in the two phases. At pH 7.0-8.0, less than 5% of Ad2 was associated with the detergent phase; at pH 5.0 or below, about 60% of Ad2 was associated with the detergent phase. When a mixture of 35S-labeled capsid proteins was used at pH 7.0, 60-70% of the total proteins were associated with the detergent at pH 5.0, but less than 5% of the proteins interacted with detergent at pH 7.0. Among the three major external proteins (hexon, penton base, and fiber), penton base had the highest association with Triton X-114 at pH 5.0. Both intact virus and the capsid proteins that were associated with Triton X-114 at pH 5.0 were released into the aqueous phase on subsequent incubation at pH 7.0. On the basis of these results, it is suggested that mildly acidic pH induces amphiphilic properties in adenovirus capsid proteins and may help Ad2 escape from acidic endocytic vesicles.     

Kinetics of registry selection of chimeric peptides binding to MHC II

Major histocompatability complex type II proteins (MHC II) are alphabeta-heterodimeric glycoproteins that present peptides to the T cell receptor (TCR) of CD4(+) T-cells. This presentation may result in activation of these T-cells, depending on the nature of the peptide. Peptides interact specifically with MHC II with nine peptide amino acid positions, and the corresponding MHC II pocket positions are usually labeled P1-P9. However, the length of peptides binding to MHC II may be greater than nine amino acids, and therefore these peptides may potentially bind to the MHC II in more than one registry. To investigate the mechanism by which a long peptide binds to I-E(k), a murine MHC II, a chimeric peptide with two nonoverlapping registries, f-IAYLKQATKQLRMATPLLMR was designed. The IAYLKQATK peptide segment is based on moth cytochrome c 95-103 (MCC 95-103), and the QLRMATPLLMR segment is based on murine Ii CLIP 89-99 M90L (Ii CLIP 89-99 M90L). This chimeric peptide forms two isomeric complexes. The MCC and Ii CLIP registries dissociate from I-E(k) with t(1/2) values of >800 and 4.94 h, respectively. The registry composition of this MHC II/chimeric peptide complex was found to change as a function of time in approaching thermodynamic equilibrium: the results are consistent with a kinetic model that involves no intramolecular isomer interconversion. The model depicts uncorrelated binding to the MHC II determined by relative association rates to the two registries. This is followed by dissociation and subsequent rebinding, leading ultimately to a preponderance of the most stable complex. Similar results were obtained at pH 5.3. The behavior of this chimeric peptide approximates the binding of a 1:1 solution mixture of two peptides to MHC II, where the more stable complex is selected over time. We have also found that a chimeric peptide and a human MHC II, HLA-DR40401, form isomers with relative association rates to DR0401 at pH 5.3 of 15% for one isomer and 85% for the second isomer.     

Comparative analysis of epitope predictions: proposed library of putative vaccine candidates for HIV

Designing a vaccine for a disease is one of the crucial tasks that involve millions and billions of dollars, several decades and yet there is no guarantee of successful results. Several pharmaceutical companies are investing their money and time in such activities. Computational biology could be of great help in these activities by proving a library of plausible candidates that might actually show some positive responses. MHC binding peptide prediction is one such area where the immense power of computers could be used to get a breakthrough. In this direction several databases and servers have been developed by many labs to predict the MHC binding peptides. These short peptides on the antigen surface are recognized by the MHC molecule and are presented to the receptors of T-cells for further immune response. Peptides that bind to a given MHC molecule share sequence similarity. Here we present a comparative study of servers that can predict the MHC binding peptides in a given protein sequence of the antigen. Based on this comparative analysis on HIV data, we are able to propose a library of putative vaccine candidates for the env GP-160 protein of HIV-1.     

NetMHCIIpan-3.0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ

Major histocompatibility complex class II (MHCII) molecules play an important role in cell-mediated immunity. They present specific peptides derived from endosomal proteins for recognition by T helper cells. The identification of peptides that bind to MHCII molecules is therefore of great importance for understanding the nature of immune responses and identifying T cell epitopes for the design of new vaccines and immunotherapies. Given the large number of MHC variants, and the costly experimental procedures needed to evaluate individual peptide–MHC interactions, computational predictions have become particularly attractive as first-line methods in epitope discovery. However, only a few so-called pan-specific prediction methods capable of predicting binding to any MHC molecule with known protein sequence are currently available, and all of them are limited to HLA-DR. Here, we present the first pan-specific method capable of predicting peptide binding to any HLA class II molecule with a defined protein sequence. The method employs a strategy common for HLA-DR, HLA-DP and HLA-DQ molecules to define the peptide-binding MHC environment in terms of a pseudo sequence. This strategy allows the inclusion of new molecules even from other species. The method was evaluated in several benchmarks and demonstrates a significant improvement over molecule-specific methods as well as the ability to predict peptide binding of previously uncharacterised MHCII molecules. To the best of our knowledge, the NetMHCIIpan-3.0 method is the first pan-specific predictor covering all HLA class II molecules with known sequences including HLA-DR, HLA-DP, and HLA-DQ. The NetMHCpan-3.0 method is available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.0.     

Towards universal structure-based prediction of class II MHC epitopes for diverse allotypes

The binding of peptide fragments of antigens to class II MHC proteins is a crucial step in initiating a helper T cell immune response. The discovery of these peptide epitopes is important for understanding the normal immune response and its misregulation in autoimmunity and allergies and also for vaccine design. In spite of their biomedical importance, the high diversity of class II MHC proteins combined with the large number of possible peptide sequences make comprehensive experimental determination of epitopes for all MHC allotypes infeasible. Computational methods can address this need by predicting epitopes for a particular MHC allotype. We present a structure-based method for predicting class II epitopes that combines molecular mechanics docking of a fully flexible peptide into the MHC binding cleft followed by binding affinity prediction using a machine learning classifier trained on interaction energy components calculated from the docking solution. Although the primary advantage of structure-based prediction methods over the commonly employed sequence-based methods is their applicability to essentially any MHC allotype, this has not yet been convincingly demonstrated. In order to test the transferability of the prediction method to different MHC proteins, we trained the scoring method on binding data for DRB1*0101 and used it to make predictions for multiple MHC allotypes with distinct peptide binding specificities including representatives from the other human class II MHC loci, HLA-DP and HLA-DQ, as well as for two murine allotypes. The results showed that the prediction method was able to achieve significant discrimination between epitope and non-epitope peptides for all MHC allotypes examined, based on AUC values in the range 0.632-0.821. We also discuss how accounting for peptide binding in multiple registers to class II MHC largely explains the systematically worse performance of prediction methods for class II MHC compared with those for class I MHC based on quantitative prediction performance estimates for peptide binding to class II MHC in a fixed register.     

In vitro maximum binding of antigenic peptides to murine MHC class II molecules does not always take place at the acidic pH of the in vivo endosomal compartment.

Presentation of Ag to the T cell requires binding of specific peptide fragments of the Ag to MHC II molecules. The ability of a peptide to bind to MHC class II appears to be pH dependent. Recent reports indicate that the binding of peptide to MHC class II molecules takes place primarily within an endosomal compartment of the cell at around pH 5. In this study, we have explored the in vitro pH dependence of peptide binding to different haplotypes of murine MHC class II molecules. The binding of peptides to MHC II was analyzed and quantitated by silica gel TLC, using radiolabeled peptides. The MBP peptide fragments, MBP(1-14)A4 and MBP(88-101)Y88, bound maximally at pH 8 to IAk and IAs, respectively. The binding of PLP peptide fragment, PLP(138-151)Y138, to IAs was maximal at around neutral pH. The maximum binding of an OVA peptide fragment, OVA(323-340)Y340, to IAd, was found to occur at pH 6. Results presented in this report thus suggest that the in vitro maximum binding of peptide is pH dependent and does not always occur at pH 5. The optimum pH range for maximum binding may depend on the nature and net charge of the peptide and its interaction with MHC class II molecules.     

Low-pH-induced effects on patterns of protein synthesis and on internal pH in Escherichia coli and Salmonella typhimurium

Escherichia coli and Salmonella typhimurium were grown in a supplemented minimal medium (SMM) at a pH of 7.0 or 5.0 or were shifted from pH 7.0 to 5.0. Two-dimensional gel electrophoretic analysis of proteins labeled with H2(35)SO4 for 20 min during the shift showed that in E. coli, 13 polypeptides were elevated 1.5- to 4-fold, whereas in S. typhimurium, 19 polypeptides were increased 2- to 14-fold over the pH 7.0 control. Upon long-term growth at pH 5.0, almost double the number of polypeptides were elevated twofold or more in S. typhimurium compared with E. coli. In E. coli, there was no apparent induction of heat shock proteins upon growth at pH 5.0 in SMM. However, growth of E. coli in a complex broth to pH 5.0, or subsequent growth of fresh E. coli cells in the filtrate from this culture, showed that a subset of five polypeptides is uniquely induced by low pH. Two of these polypeptides, D60.5, the inducible lysyl-tRNA synthetase, and C62.5, are known heat shock proteins. Measurements of the internal pH (pHi) and growth rates of both organisms were made during growth in SMM at pH 7.0, pH 5.0, and upon the pH shift. The data show that the pHi of E. coli decreases more severely than that of S. typhimurium at an external pH of 5.0; the growth rate of E. coli is about one-half that of S. typhimurium at this pH, whereas the two organisms have the same growth rate at pH 7.0. The two-dimensional gel, growth, and pHi experiments collectively suggest that, at least in SMM, S. typhimurium is more adaptive to low-pH stress than is E. coli.     

Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models

Background  

The binding between peptide epitopes and major histocompatibility complex proteins (MHCs) is an important event in the cellular immune response. Accurate prediction of the binding between short peptides and the MHC molecules has long been a principal challenge for immunoinformatics. Recently, the modeling of MHC-peptide binding has come to emphasize quantitative predictions: instead of categorizing peptides as "binders" or "non-binders" or as "strong binders" and "weak binders", recent methods seek to make predictions about precise binding affinities.     

Low-pH-induced effects on patterns of protein synthesis and on internal pH in Escherichia coli and Salmonella typhimurium.

Escherichia coli and Salmonella typhimurium were grown in a supplemented minimal medium (SMM) at a pH of 7.0 or 5.0 or were shifted from pH 7.0 to 5.0. Two-dimensional gel electrophoretic analysis of proteins labeled with H2(35)SO4 for 20 min during the shift showed that in E. coli, 13 polypeptides were elevated 1.5- to 4-fold, whereas in S. typhimurium, 19 polypeptides were increased 2- to 14-fold over the pH 7.0 control. Upon long-term growth at pH 5.0, almost double the number of polypeptides were elevated twofold or more in S. typhimurium compared with E. coli. In E. coli, there was no apparent induction of heat shock proteins upon growth at pH 5.0 in SMM. However, growth of E. coli in a complex broth to pH 5.0, or subsequent growth of fresh E. coli cells in the filtrate from this culture, showed that a subset of five polypeptides is uniquely induced by low pH. Two of these polypeptides, D60.5, the inducible lysyl-tRNA synthetase, and C62.5, are known heat shock proteins. Measurements of the internal pH (pHi) and growth rates of both organisms were made during growth in SMM at pH 7.0, pH 5.0, and upon the pH shift. The data show that the pHi of E. coli decreases more severely than that of S. typhimurium at an external pH of 5.0; the growth rate of E. coli is about one-half that of S. typhimurium at this pH, whereas the two organisms have the same growth rate at pH 7.0. The two-dimensional gel, growth, and pHi experiments collectively suggest that, at least in SMM, S. typhimurium is more adaptive to low-pH stress than is E. coli.     

Class I and class II MHC bind self peptide sets that are strikingly different in their evolutionary characteristics

 Comparison of peptides eluted from human class I and class II major histocompatibility complex (MHC) molecules and the proteins from which they are derived (source proteins) revealed that class I MHC bind peptides derived from proteins that are highly conserved, hydrophilic, and universally expressed, while the peptides themselves are hydrophobic and even more conserved than their source proteins. In contrast, source proteins for class II-bound peptides were not significantly more conserved than a random sample of proteins. Class II-bound peptides were generally more conserved than their source proteins but were significantly less conserved than class I-bound peptides. The characteristics of class I-bound peptides can probably be explained by the selectivity of processing and transport of peptides for binding by class I, while the relative lack of selectivity of peptide binding for class II may explain the high incidence of autoimmune diseases associated with alleles of these molecules. Received: 17 May 1999 / Revised: 5 August 1999     

Cathepsin B cleavage of Ii from class II MHC alpha- and beta-chains

Class II MHC-associated invariant chain (Ii) might regulate binding of digested peptides to the Ag binding site (desetope) of class II MHC proteins by directly or allosterically blocking that site until cleavage and release of Ii from MHC alpha- and beta-chains at the time of peptide charging. We examined the cleavage and release of Ii from class II MHC alpha/beta Ii trimers by cathepsin B, which has been shown by others to colocalize with class II MHC molecules in intracellular compartments and to generate antigenic peptide fragments. Cathepsin B at pH 5.0 cleaved and released Ii from class II MHC alpha- and beta-chains. Cathepsin B digested Ii from alpha- and beta-chains in a dose-dependent fashion, yielding 23-, 21-, and 10-kDa fragments. Blockage of cathepsin B activity with leupeptin restored the 2D(nonequilibrium pH gradient gel electrophoresis/SDS) PAGE patterns of Ii and sialic acid-derivatized forms of Ii seen without the protease. The fragmentation pattern of cathepsin D treatment was different from that of cathepsin B, yielding 25-kDa intermediates.     

The pH dependence of kinetic parameters of Penicillium brevicompactum RNAase]

The effect of pH on the kinetic parameters (Km and Ki) for extracellular acid Penicillium brevicompactum RNAse (pH max 4.7+/-0.1), non-specific to the chemical nature of nucleic bases, was studied. The pKm--pH dependence curve showed bends within the following intervals of pH: 3.5--4.0 and 5.6--6.0 (upward side concavity) and 6.2--6.8 (downward side concavity). The pKi--pH dependence for adenosine-3'-monophosphate as an inhibitor is identical to the pH dependence on pKm for the substrate. On the other hand, the pKi--pH dependence curves obtained for the base-free inhibitors (ribose-5'-monophosphate, or phosphate (adenosine) show no bends within the pH intervals of 3.0--4.0 and 5.6--7.0 respectively. A possibility is discussed of the presence of a carboxylic (pK 3.58+/-0.1) and two imidazole groups (pK 6.42+/-0.1--a weakly protonated and 5.8+/-+/-0.1--a strongly protonated group) in the RNAse active site and their participation in the formation of the RNAse-nucleotide (RNAse-substrate) complex.