Literature DB >> 21383422

Antibody-specified B-cell epitope prediction in line with the principle of context-awareness.

Liang Zhao1, Limsoon Wong, Jinyan Li.   

Abstract

Context-awareness is a characteristic in the recognition between antigens and antibodies, highlighting the reconfiguration of epitope residues when an antigen interacts with a different antibody. A coarse binary classification of antigen regions into epitopes, or nonepitopes without specifying antibodies may not accurately reflect this biological reality. Therefore, we study an antibody-specified epitope prediction problem in line with this principle. This problem is new and challenging as we pinpoint a subset of the antigenic residues from an antigen when it binds to a specific antibody. We introduce two kinds of associations of the contextual awareness: 1) residues-residues pairing preference, and 2) the dependence between sets of contact residue pairs. Preference plays a bridging role to link interacting paratope and epitope residues while dependence is used to extend the association from one-dimension to two-dimension. The paratope/epitope residues' relative composition, cooperativity ratios, and Markov properties are also utilized to enhance our method. A nonredundant data set containing 80 antibody-antigen complexes is compiled and used in the evaluation. The results show that our method yields a good performance on antibody-specified epitope prediction. On the traditional antibody-ignored epitope prediction problem, a simplified version of our method can produce a competitive, sometimes much better, performance in comparison with three structure-based predictors.

Mesh:

Substances:

Year:  2011        PMID: 21383422     DOI: 10.1109/TCBB.2011.49

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  19 in total

Review 1.  Antibody specific epitope prediction-emergence of a new paradigm.

Authors:  Inbal Sela-Culang; Yanay Ofran; Bjoern Peters
Journal:  Curr Opin Virol       Date:  2015-03-31       Impact factor: 7.090

2.  In Silico Prediction of Linear B-Cell Epitopes on Proteins.

Authors:  Yasser El-Manzalawy; Drena Dobbs; Vasant G Honavar
Journal:  Methods Mol Biol       Date:  2017

3.  Learning context-aware structural representations to predict antigen and antibody binding interfaces.

Authors:  Srivamshi Pittala; Chris Bailey-Kellogg
Journal:  Bioinformatics       Date:  2020-07-01       Impact factor: 6.937

Review 4.  How repertoire data are changing antibody science.

Authors:  Claire Marks; Charlotte M Deane
Journal:  J Biol Chem       Date:  2020-05-14       Impact factor: 5.157

5.  NEP: web server for epitope prediction based on antibody neutralization of viral strains with diverse sequences.

Authors:  Gwo-Yu Chuang; David Liou; Peter D Kwong; Ivelin S Georgiev
Journal:  Nucleic Acids Res       Date:  2014-04-29       Impact factor: 16.971

6.  Residue-level prediction of HIV-1 antibody epitopes based on neutralization of diverse viral strains.

Authors:  Gwo-Yu Chuang; Priyamvada Acharya; Stephen D Schmidt; Yongping Yang; Mark K Louder; Tongqing Zhou; Young Do Kwon; Marie Pancera; Robert T Bailer; Nicole A Doria-Rose; Michel C Nussenzweig; John R Mascola; Peter D Kwong; Ivelin S Georgiev
Journal:  J Virol       Date:  2013-07-10       Impact factor: 5.103

7.  Conformational epitope matching and prediction based on protein surface spiral features.

Authors:  Ying-Tsang Lo; Tao-Chuan Shih; Tun-Wen Pai; Li-Ping Ho; Jen-Leih Wu; Hsin-Yiu Chou
Journal:  BMC Genomics       Date:  2021-05-31       Impact factor: 3.969

8.  Structural and functional analysis of multi-interface domains.

Authors:  Liang Zhao; Steven C H Hoi; Limsoon Wong; Tobias Hamp; Jinyan Li
Journal:  PLoS One       Date:  2012-12-14       Impact factor: 3.240

Review 9.  The structural basis of antibody-antigen recognition.

Authors:  Inbal Sela-Culang; Vered Kunik; Yanay Ofran
Journal:  Front Immunol       Date:  2013-10-08       Impact factor: 7.561

10.  B-cell epitope prediction through a graph model.

Authors:  Liang Zhao; Limsoon Wong; Lanyuan Lu; Steven C H Hoi; Jinyan Li
Journal:  BMC Bioinformatics       Date:  2012-12-13       Impact factor: 3.169

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