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dc.contributor.authorPierce, Brian G.
dc.contributor.authorWeng, Zhiping
dc.date2022-08-11T08:07:59.000
dc.date.accessioned2022-08-23T15:38:21Z
dc.date.available2022-08-23T15:38:21Z
dc.date.issued2013-01-01
dc.date.submitted2013-02-22
dc.identifier.citationProtein Sci. 2013 Jan;22(1):35-46. doi: 10.1002/pro.2181. <a href="http://dx.doi.org/10.1002/pro.2181">Link to article on publisher's site</a>
dc.identifier.issn0961-8368 (Linking)
dc.identifier.doi10.1002/pro.2181
dc.identifier.pmid23109003
dc.identifier.urihttp://hdl.handle.net/20.500.14038/25919
dc.description.abstractT cell receptors (TCRs) are immune proteins that specifically bind to antigenic molecules, which are often foreign peptides presented by major histocompatibility complex proteins (pMHCs), playing a key role in the cellular immune response. To advance our understanding and modeling of this dynamic immunological event, we assembled a protein-protein docking benchmark consisting of 20 structures of crystallized TCR/pMHC complexes for which unbound structures exist for both TCR and pMHC. We used our benchmark to compare predictive performance using several flexible and rigid backbone TCR/pMHC docking protocols. Our flexible TCR docking algorithm, TCRFlexDock, improved predictive success over the fixed backbone protocol, leading to near-native predictions for 80% of the TCR/pMHC cases among the top 10 models, and 100% of the cases in the top 30 models. We then applied TCRFlexDock to predict the two distinct docking modes recently described for a single TCR bound to two different antigens, and tested several protein modeling scoring functions for prediction of TCR/pMHC binding affinities. This algorithm and benchmark should enable future efforts to predict, and design of uncharacterized TCR/pMHC complexes.
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=23109003&dopt=Abstract">Link to Article in PubMed</a>
dc.relation.urlhttp://dx.doi.org/10.1002/pro.2181
dc.subjectReceptors, Antigen, T-Cell
dc.subjectGenes, MHC Class II
dc.subjectMajor Histocompatibility Complex
dc.subjectMolecular Docking Simulation
dc.subjectBiochemistry, Biophysics, and Structural Biology
dc.subjectBioinformatics
dc.subjectComputational Biology
dc.subjectImmunity
dc.subjectMolecular Biology
dc.titleA flexible docking approach for prediction of T cell receptor-peptide-MHC complexes
dc.typeJournal Article
dc.source.journaltitleProtein science : a publication of the Protein Society
dc.source.volume22
dc.source.issue1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/bioinformatics_pubs/6
dc.identifier.contextkey3761387
html.description.abstract<p>T cell receptors (TCRs) are immune proteins that specifically bind to antigenic molecules, which are often foreign peptides presented by major histocompatibility complex proteins (pMHCs), playing a key role in the cellular immune response. To advance our understanding and modeling of this dynamic immunological event, we assembled a protein-protein docking benchmark consisting of 20 structures of crystallized TCR/pMHC complexes for which unbound structures exist for both TCR and pMHC. We used our benchmark to compare predictive performance using several flexible and rigid backbone TCR/pMHC docking protocols. Our flexible TCR docking algorithm, TCRFlexDock, improved predictive success over the fixed backbone protocol, leading to near-native predictions for 80% of the TCR/pMHC cases among the top 10 models, and 100% of the cases in the top 30 models. We then applied TCRFlexDock to predict the two distinct docking modes recently described for a single TCR bound to two different antigens, and tested several protein modeling scoring functions for prediction of TCR/pMHC binding affinities. This algorithm and benchmark should enable future efforts to predict, and design of uncharacterized TCR/pMHC complexes.</p>
dc.identifier.submissionpathbioinformatics_pubs/6
dc.contributor.departmentProgram in Bioinformatics and Integrative Biology
dc.contributor.departmentDepartment of Biochemistry and Molecular Pharmacology
dc.source.pages35-46


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