Dataset Information

An effective and effecient peptide binding prediction approach for a broad set of HLA-DR molecules based on ordered weighted averaging of binding pocket profiles.

ABSTRACT: BACKGROUND:The immune system must detect a wide variety of microbial pathogens, such as viruses, bacteria, fungi and parasitic worms, to protect the host against disease. Antigenic peptides displayed by MHC II (class II Major Histocompatibility Complex) molecules is a pivotal process to activate CD4+ TH cells (Helper T cells). The activated TH cells can differentiate into effector cells which assist various cells in activating against pathogen invasion. Each MHC locus encodes a great number of allele variants. Yet this limited number of MHC molecules are required to display enormous number of antigenic peptides. Since the peptide binding measurements of MHC molecules by biochemical experiments are expensive, only a few of the MHC molecules have suffecient measured peptides. To perform accurate binding prediction for those MHC alleles without suffecient measured peptides, a number of computational algorithms were proposed in the last decades. RESULTS:Here, we propose a new MHC II binding prediction approach, OWA-PSSM, which is a significantly extended version of a well known method called TEPITOPE. The TEPITOPE method is able to perform prediction for only 50 MHC alleles, while OWA-PSSM is able to perform prediction for much more, up to 879 HLA-DR molecules. We evaluate the method on five benchmark datasets. The method is demonstrated to be the best one in identifying binding cores compared with several other popular state-of-the-art approaches. Meanwhile, the method performs comparably to the TEPITOPE and NetMHCIIpan2.0 approaches in identifying HLA-DR epitopes and ligands, and it performs significantly better than TEPITOPEpan in the identification of HLA-DR ligands and MultiRTA in identifying HLA-DR T cell epitopes. CONCLUSIONS:The proposed approach OWA-PSSM is fast and robust in identifying ligands, epitopes and binding cores for up to 879 MHC II molecules.

SUBMITTER: Shen WJ

PROVIDER: S-EPMC3908610 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An effective and effecient peptide binding prediction approach for a broad set of HLA-DR molecules based on ordered weighted averaging of binding pocket profiles.

Shen Wen-Jun WJ Zhang Shaohong S Wong Hau-San HS

Proteome science 20131107 Suppl 1

<h4>Background</h4>The immune system must detect a wide variety of microbial pathogens, such as viruses, bacteria, fungi and parasitic worms, to protect the host against disease. Antigenic peptides displayed by MHC II (class II Major Histocompatibility Complex) molecules is a pivotal process to activate CD4+ TH cells (Helper T cells). The activated TH cells can differentiate into effector cells which assist various cells in activating against pathogen invasion. Each MHC locus encodes a great num ...[more]

PMID: 24565049

Similar Datasets

Project description:MOTIVATION:Accurate identification of peptides binding to specific Major Histocompatibility Complex Class II (MHC-II) molecules is of great importance for elucidating the underlying mechanism of immune recognition, as well as for developing effective epitope-based vaccines and promising immunotherapies for many severe diseases. Due to extreme polymorphism of MHC-II alleles and the high cost of biochemical experiments, the development of computational methods for accurate prediction of binding peptides of MHC-II molecules, particularly for the ones with few or no experimental data, has become a topic of increasing interest. TEPITOPE is a well-used computational approach because of its good interpretability and relatively high performance. However, TEPITOPE can be applied to only 51 out of over 700 known HLA DR molecules. METHOD:We have developed a new method, called TEPITOPEpan, by extrapolating from the binding specificities of HLA DR molecules characterized by TEPITOPE to those uncharacterized. First, each HLA-DR binding pocket is represented by amino acid residues that have close contact with the corresponding peptide binding core residues. Then the pocket similarity between two HLA-DR molecules is calculated as the sequence similarity of the residues. Finally, for an uncharacterized HLA-DR molecule, the binding specificity of each pocket is computed as a weighted average in pocket binding specificities over HLA-DR molecules characterized by TEPITOPE. RESULT:The performance of TEPITOPEpan has been extensively evaluated using various data sets from different viewpoints: predicting MHC binding peptides, identifying HLA ligands and T-cell epitopes and recognizing binding cores. Among the four state-of-the-art competing pan-specific methods, for predicting binding specificities of unknown HLA-DR molecules, TEPITOPEpan was roughly the second best method next to NETMHCIIpan-2.0. Additionally, TEPITOPEpan achieved the best performance in recognizing binding cores. We further analyzed the motifs detected by TEPITOPEpan, examining the corresponding literature of immunology. Its online server and PSSMs therein are available at http://www.biokdd.fudan.edu.cn/Service/TEPITOPEpan/.

Project description:Zwitterionic polysaccharide antigens (ZPSs) were recently shown to activate T cells in a class II major histocompatibility complex (MHCII)-dependent fashion requiring antigen presenting cell (APC)-mediated oxidative processing although little is known about the mechanism or affinity of carbohydrate presentation (Cobb BA, Wang Q, Tzianabos AO, Kasper DL. 2004. Polysaccharide processing and presentation by the MHCII pathway. Cell. 117:677-687). A recent study showed that the helical conformation of ZPSs (Wang Y, Kalka-Moll WM, Roehrl MH, Kasper DL. 2000. Structural basis of the abscess-modulating polysaccharide A2 from Bacteroides fragilis. Proc Natl Acad Sci USA. 97:13478-13483; Choi YH, Roehrl MH, Kasper DL, Wang JY. 2002. A unique structural pattern shared by T-cell-activating and abscess-regulating zwitterionic polysaccharides. Biochemistry. 41:15144-15151) is closely linked with immunogenic activity (Tzianabos AO, Onderdonk AB, Rosner B, Cisneros RL, Kasper DL. 1993. Structural features of polysaccharides that induce intra-abdominal abscesses. Science. 262:416-419) and is stabilized by a zwitterionic charge motif (Kreisman LS, Friedman JH, Neaga A, Cobb BA. 2007. Structure and function relations with a T-cell-activating polysaccharide antigen using circular dichroism. Glycobiology. 17:46-55), suggesting a strong carbohydrate structure-function relationship. In this study, we show that PSA, the ZPS from Bacteroides fragilis, associates with MHCII at high affinity and 1:1 stoichiometry through a mechanism mirroring peptide presentation. Interestingly, PSA binding was mutually exclusive with common MHCII antigens and showed significant allelic differences in binding affinity. The antigen exchange factor HLA-DM that catalyzes peptide antigen association with MHCII also increased the rate of ZPS association and was required for APC presentation and ZPS-mediated T cell activation. Finally, the zwitterionic nature of these antigens was required only for MHCII binding, and not endocytosis, processing, or vesicular trafficking to MHCII-containing vesicles. This report is the first quantitative analysis of the binding mechanism of carbohydrate antigens with MHCII and leads to a novel model for nontraditional MHCII antigen presentation during bacterial infections.

Dataset Information

An effective and effecient peptide binding prediction approach for a broad set of HLA-DR molecules based on ordered weighted averaging of binding pocket profiles.

Publications

An effective and effecient peptide binding prediction approach for a broad set of HLA-DR molecules based on ordered weighted averaging of binding pocket profiles.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets