Structure-based Methods for Binding Mode and Binding Affinity Prediction for Peptide-MHC Complexes

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dc.citation.firstpage2239en_US
dc.citation.issueNumber26en_US
dc.citation.journalTitleCurrent Topics in Medicinal Chemistryen_US
dc.citation.lastpage2255en_US
dc.citation.volumeNumber18en_US
dc.contributor.authorAntunes, Dinler A.en_US
dc.contributor.authorAbella, Jayvee R.en_US
dc.contributor.authorDevaurs, Didieren_US
dc.contributor.authorRigo, Maurício M.en_US
dc.contributor.authorKavraki, Lydia E.en_US
dc.date.accessioned2019-12-12T17:25:30Zen_US
dc.date.available2019-12-12T17:25:30Zen_US
dc.date.issued2018en_US
dc.description.abstractUnderstanding the mechanisms involved in the activation of an immune response is essential to many fields in human health, including vaccine development and personalized cancer immunotherapy. A central step in the activation of the adaptive immune response is the recognition, by T-cell lymphocytes, of peptides displayed by a special type of receptor known as Major Histocompatibility Complex (MHC). Considering the key role of MHC receptors in T-cell activation, the computational prediction of peptide binding to MHC has been an important goal for many immunological applications. Sequence- based methods have become the gold standard for peptide-MHC binding affinity prediction, but structure-based methods are expected to provide more general predictions (i.e., predictions applicable to all types of MHC receptors). In addition, structural modeling of peptide-MHC complexes has the potential to uncover yet unknown drivers of T-cell activation, thus allowing for the development of better and safer therapies. In this review, we discuss the use of computational methods for the structural modeling of peptide-MHC complexes (i.e., binding mode prediction) and for the structure-based prediction of binding affinity.en_US
dc.identifier.citationAntunes, Dinler A., Abella, Jayvee R., Devaurs, Didier, et al.. "Structure-based Methods for Binding Mode and Binding Affinity Prediction for Peptide-MHC Complexes." <i>Current Topics in Medicinal Chemistry,</i> 18, no. 26 (2018) Bentham Science: 2239-2255. https://doi.org/10.2174/1568026619666181224101744.en_US
dc.identifier.digitalnihms-1008660en_US
dc.identifier.doihttps://doi.org/10.2174/1568026619666181224101744en_US
dc.identifier.urihttps://hdl.handle.net/1911/107872en_US
dc.language.isoengen_US
dc.publisherBentham Scienceen_US
dc.rightsThis is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Bentham Scienceen_US
dc.subject.keywordT-cell activationen_US
dc.subject.keywordBinding affinity predictionen_US
dc.subject.keywordBinding mode predictionen_US
dc.subject.keywordImmunogenicityen_US
dc.subject.keywordMolecular dockingen_US
dc.subject.keywordPeptide- MHC complexesen_US
dc.titleStructure-based Methods for Binding Mode and Binding Affinity Prediction for Peptide-MHC Complexesen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpost-printen_US
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