Selection of peptides that bind to the HLA-A2.1 molecule by molecular modelling

Cited 37 time in scopus
Metadata Downloads

Full metadata record

DC FieldValueLanguage
dc.contributor.authorJong-Seok Lim-
dc.contributor.authorSeung Moak Kim-
dc.contributor.authorHee Gu Lee-
dc.contributor.authorKi Young Lee-
dc.contributor.authorT J Kwon-
dc.contributor.authorKil Hyoun Kim-
dc.date.accessioned2017-04-19T08:45:11Z-
dc.date.available2017-04-19T08:45:11Z-
dc.date.issued1996-
dc.identifier.issn0161-5890-
dc.identifier.urihttps://oak.kribb.re.kr/handle/201005/3670-
dc.description.abstractCytotoxic T lymphocytes recognize antigenic peptides in association with major histocompatibility complex class I proteins. Although a large set of class I binding peptides has been described, it is not yet easy to search for potentially antigenic peptides without synthesis of a panel of peptides, and subsequent binding assays. In order to predict HLA-A2.1-restricted antigenic epitopes, a computer model of the HLA-A2.1 molecule was established using X-ray crystallography data. In this model nonameric peptide sequences were aligned. In a molecular dynamics (MD) simulation with two sets of peptides known to be presented by HLA-A2.1, it was important to know the anchor amino acid residue preference and the distance between the anchor residues. We show here that the peptides bound to the HLA-A2.1 model structure possess a side chain of C-terminal anchor residue oriented into the binding groove with different distances between the two anchor residues from 15 to 21?. We also synthesized a set of nonamer peptides containing amino acid sequences of Hepatitis B virus protein that were selected on the basis of previously described HLA-A2.1 specific motifs. When results obtained from the MD simulation were compared with functional binding assays using the TAP-deficient cell line T2, it was evident that the MD simulation method improves prediction of the HLA-A2.1 binding epitope sequence. These results suggest that this approach can provide a way to predict peptide epitopes and search for antigenic regions in sequences in a variety of antigens without screening a large number of synthetic peptides.-
dc.publisherElsevier-
dc.titleSelection of peptides that bind to the HLA-A2.1 molecule by molecular modelling-
dc.title.alternativeSelection of peptides that bind to the HLA-A2.1 molecule by molecular modelling-
dc.typeArticle-
dc.citation.titleMolecular Immunology-
dc.citation.number2-
dc.citation.endPage230-
dc.citation.startPage221-
dc.citation.volume33-
dc.contributor.affiliatedAuthorJong-Seok Lim-
dc.contributor.affiliatedAuthorSeung Moak Kim-
dc.contributor.affiliatedAuthorHee Gu Lee-
dc.contributor.affiliatedAuthorKi Young Lee-
dc.contributor.affiliatedAuthorKil Hyoun Kim-
dc.contributor.alternativeName임종석-
dc.contributor.alternativeName김승목-
dc.contributor.alternativeName이희구-
dc.contributor.alternativeName이기영-
dc.contributor.alternativeName권태종-
dc.contributor.alternativeName김길현-
dc.identifier.bibliographicCitationMolecular Immunology, vol. 33, no. 2, pp. 221-230-
dc.identifier.doi10.1016/0161-5890(95)00065-8-
dc.subject.keywordcomputer modeling-
dc.subject.keywordepitope prediction-
dc.subject.keywordMHC binding peptide-
dc.subject.localcomputer modeling-
dc.subject.localComputer modeling-
dc.subject.localepitope prediction-
dc.subject.localMHC binding peptide-
dc.description.journalClassY-
Appears in Collections:
Division of A.I. & Biomedical Research > Immunotherapy Research Center > 1. Journal Articles
Files in This Item:
  • There are no files associated with this item.


Items in OpenAccess@KRIBB are protected by copyright, with all rights reserved, unless otherwise indicated.