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Citation
Tags
HERO ID
847601
Reference Type
Journal Article
Subtype
Review
Title
Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools
Author(s)
Zhang, L; Udaka, K; Mamitsuka, H; Zhu, S
Year
2012
Is Peer Reviewed?
Yes
Journal
Briefings in Bioinformatics
ISSN:
1467-5463
EISSN:
1477-4054
Volume
13
Issue
3
Page Numbers
350-364
Language
English
PMID
21949215
DOI
10.1093/bib/bbr060
Abstract
Binding of short antigenic peptides to major histocompatibility complex (MHC) molecules is a core step in adaptive immune response. Precise identification of MHC-restricted peptides is of great significance for understanding the mechanism of immune response and promoting the discovery of immunogenic epitopes. However, due to the extremely high MHC polymorphism and huge cost of biochemical experiments, there is no experimentally measured binding data for most MHC molecules. To address the problem of predicting peptides binding to these MHC molecules, recently computational approaches, called pan-specific methods, have received keen interest. Pan-specific methods make use of experimentally obtained binding data of multiple alleles, by which binding peptides (binders) of not only these alleles but also those alleles with no known binders can be predicted. To investigate the possibility of further improvement in performance and usability of pan-specific methods, this article extensively reviews existing pan-specific methods and their web servers. We first present a general framework of pan-specific methods. Then, the strategies and performance as well as utilities of web servers are compared. Finally, we discuss the future direction to improve pan-specific methods for MHC-peptide binding prediction.
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