A flexible docking approach for prediction of T cell receptor-peptide-MHC complexes

UMMS Affiliation

Department of Biochemistry and Molecular Pharmacology; Program in Bioinformatics and Integrative Biology

Publication Date


Document Type



Receptors, Antigen, T-Cell; Genes, MHC Class II; Major Histocompatibility Complex; Molecular Docking Simulation


Biochemistry, Biophysics, and Structural Biology | Bioinformatics | Computational Biology | Immunity | Molecular Biology


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.

DOI of Published Version



Protein Sci. 2013 Jan;22(1):35-46. doi: 10.1002/pro.2181. Link to article on publisher's site

Journal/Book/Conference Title

Protein science : a publication of the Protein Society

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Link to Article in PubMed

PubMed ID