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Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0: a quantitative molecular docking study.

ABSTRACT: BACKGROUND:HLA-DPs are class II MHC proteins mediating immune responses to many diseases. Peptides bind MHC class II proteins in the acidic environment within endosomes. Acidic pH markedly elevates association rate constants but dissociation rates are almost unchanged in the pH range 5.0 - 7.0. This pH-driven effect can be explained by the protonation/deprotonation states of Histidine, whose imidazole has a pK(a) of 6.0. At pH 5.0, imidazole ring is protonated, making Histidine positively charged and very hydrophilic, while at pH 7.0 imidazole is unprotonated, making Histidine less hydrophilic. We develop here a method to predict peptide binding to the four most frequent HLA-DP proteins: DP1, DP41, DP42 and DP5, using a molecular docking protocol. Dockings to virtual combinatorial peptide libraries were performed at pH 5.0 and pH 7.0. RESULTS:The X-ray structure of the peptide--HLA-DP2 protein complex was used as a starting template to model by homology the structure of the four DP proteins. The resulting models were used to produce virtual combinatorial peptide libraries constructed using the single amino acid substitution (SAAS) principle. Peptides were docked into the DP binding site using AutoDock at pH 5.0 and pH 7.0. The resulting scores were normalized and used to generate Docking Score-based Quantitative Matrices (DS-QMs). The predictive ability of these QMs was tested using an external test set of 484 known DP binders. They were also compared to existing servers for DP binding prediction. The models derived at pH 5.0 predict better than those derived at pH 7.0 and showed significantly improved predictions for three of the four DP proteins, when compared to the existing servers. They are able to recognize 50% of the known binders in the top 5% of predicted peptides. CONCLUSIONS:The higher predictive ability of DS-QMs derived at pH 5.0 may be rationalised by the additional hydrogen bond formed between the backbone carbonyl oxygen belonging to the peptide position before p1 (p-1) and the protonated ?-nitrogen of His79?. Additionally, protonated His residues are well accepted at most of the peptide binding core positions which is in a good agreement with the overall negatively charged peptide binding site of most MHC proteins.

SUBMITTER: Patronov A

PROVIDER: S-EPMC3508589 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0: a quantitative molecular docking study.

Patronov Atanas A Dimitrov Ivan I Flower Darren R DR Doytchinova Irini I

BMC structural biology 20120805

<h4>Background</h4>HLA-DPs are class II MHC proteins mediating immune responses to many diseases. Peptides bind MHC class II proteins in the acidic environment within endosomes. Acidic pH markedly elevates association rate constants but dissociation rates are almost unchanged in the pH range 5.0 - 7.0. This pH-driven effect can be explained by the protonation/deprotonation states of Histidine, whose imidazole has a pK(a) of 6.0. At pH 5.0, imidazole ring is protonated, making Histidine positivel ...[more]

PMID: 22862845

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Project description:The contribution of alloresponses to mismatched HLA-DP in solid organ transplantation and hematopoietic stem cell transplantation (HCT) has been well documented. Exploring the regulatory mechanisms of DPB1 alleles has become an important question to be answered. In this study, our initial investigation focused on examining the correlation between the rs9277534G/A SNP and DPB1 mRNA expression. The result showed that there was a significant increase in DPB1 mRNA expression in B lymphoblastoid cell lines (BLCLs) with the rs9277534GG genotype compared to rs9277534AA genotype. In addition, B cells with the rs9277534GG exhibited significantly higher DP protein expression than those carrying the rs9277534AA genotype in primary B cells. Furthermore, we observed a significant upregulation of DP expression in B cells following treatment with Interleukin 13 (IL-13) compared to untreated B cells carrying rs9277534GG-linked DPB1 alleles. Fluorescence in situ hybridization (FISH) analysis of DPB1 in BLCL demonstrated significant differences in both the cytoplasmic (p=0.0003) and nuclear (p=0.0001) localization of DP mRNA expression comparing DPB1*04:01 (rs9277534AA) and DPB1*05:01 (rs9277534GG) homozygous cells. The study of the correlation between differential DPB1 expression and long non-coding RNAs (lncRNAs) showed that lnc-HLA-DPB1-13:1 is strongly associated with DP expression (r=0.85), suggesting the potential involvement of lncRNA in regulating DP expression. The correlation of DP donor specific antibody (DSA) with B cell flow crossmatch (B-FCXM) results showed a better linear correlation of DP DSA against GG and AG donor cells (R2 = 0.4243, p=0.0025 and R2 = 0.6172, p=0.0003, respectively), compared to DSA against AA donor cells (R2 = 0.0649, p=0.4244). This explained why strong DP DSA with a low expression DP leads to negative B-FCXM. In conclusion, this study provides evidence supporting the involvement of lncRNA in modulating HLA-DP expression, shedding lights on the intricate regulatory mechanisms of DP, particularly under inflammatory conditions in transplantation.

Project description:CD4 positive T helper cells control many aspects of specific immunity. These cells are specific for peptides derived from protein antigens and presented by molecules of the extremely polymorphic major histocompatibility complex (MHC) class II system. The identification of peptides that bind to MHC class II molecules is therefore of pivotal importance for rational discovery of immune epitopes. HLA-DR is a prominent example of a human MHC class II. Here, we present a method, NetMHCIIpan, that allows for pan-specific predictions of peptide binding to any HLA-DR molecule of known sequence. The method is derived from a large compilation of quantitative HLA-DR binding events covering 14 of the more than 500 known HLA-DR alleles. Taking both peptide and HLA sequence information into account, the method can generalize and predict peptide binding also for HLA-DR molecules where experimental data is absent. Validation of the method includes identification of endogenously derived HLA class II ligands, cross-validation, leave-one-molecule-out, and binding motif identification for hitherto uncharacterized HLA-DR molecules. The validation shows that the method can successfully predict binding for HLA-DR molecules-even in the absence of specific data for the particular molecule in question. Moreover, when compared to TEPITOPE, currently the only other publicly available prediction method aiming at providing broad HLA-DR allelic coverage, NetMHCIIpan performs equivalently for alleles included in the training of TEPITOPE while outperforming TEPITOPE on novel alleles. We propose that the method can be used to identify those hitherto uncharacterized alleles, which should be addressed experimentally in future updates of the method to cover the polymorphism of HLA-DR most efficiently. We thus conclude that the presented method meets the challenge of keeping up with the MHC polymorphism discovery rate and that it can be used to sample the MHC "space," enabling a highly efficient iterative process for improving MHC class II binding predictions.

Project description:BACKGROUND:MHC class II proteins bind oligopeptide fragments derived from proteolysis of pathogen antigens, presenting them at the cell surface for recognition by CD4+ T cells. Human MHC class II alleles are grouped into three loci: HLA-DP, HLA-DQ and HLA-DR. In contrast to HLA-DR and HLA-DQ, HLA-DP proteins have not been studied extensively, as they have been viewed as less important in immune responses than DRs and DQs. However, it is now known that HLA-DP alleles are associated with many autoimmune diseases. Quite recently, the X-ray structure of the HLA-DP2 molecule (DPA*0103, DPB1*0201) in complex with a self-peptide derived from the HLA-DR ?-chain has been determined. In the present study, we applied a validated molecular docking protocol to a library of 247 modelled peptide-DP2 complexes, seeking to assess the contribution made by each of the 20 naturally occurred amino acids at each of the nine binding core peptide positions and the four flanking residues (two on both sides). RESULTS:The free binding energies (FBEs) derived from the docking experiments were normalized on a position-dependent (npp) and on an overall basis (nap), and two docking score-based quantitative matrices (DS-QMs) were derived: QMnpp and QMnap. They reveal the amino acid preferences at each of the 13 positions considered in the study. Apart from the leading role of anchor positions p1 and p6, the binding to HLA-DP2 depends on the preferences at p2. No effect of the flanking residues was found on the peptide binding predictions to DP2, although all four of them show strong preferences for particular amino acids. The predictive ability of the DS-QMs was tested using a set of 457 known binders to HLA-DP2, originating from 24 proteins. The sensitivities of the predictions at five different thresholds (5%, 10%, 15%, 20% and 25%) were calculated and compared to the predictions made by the NetMHCII and IEDB servers. Analysis of the DS-QMs indicated an improvement in performance. Additionally, DS-QMs identified the binding cores of several known DP2 binders. CONCLUSIONS:The molecular docking protocol, as applied to a combinatorial library of peptides, models the peptide-HLA-DP2 protein interaction effectively, generating reliable predictions in a quantitative assessment. The method is structure-based and does not require extensive experimental sequence-based data. Thus, it is universal and can be applied to model any peptide - protein interaction.

Dataset Information

Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0: a quantitative molecular docking study.

Publications

Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0: a quantitative molecular docking study.

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