2023 Spring Poster Symposium

HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes

The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptide/HLA (pHLA, the human MHC) structures has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within a curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these representative backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer peptide/HLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in terms of structural accuracy and consistently predicts blind targets not included in our training set. Insights from our work provide a framework for linking conformational diversity with antigen immunogenicity and receptor cross-reactivity.

PRESENTED BY
Other
College of Arts & Sciences 2024
Advised By
Nikolaos G. Sgourakis
Associate Professor of Biochemistry and Biophysics
PRESENTED BY
Other
NIAID (5R01AI143997), NIGMS (5R35GM125034), and NIDDK (5U01DK112217)
College of Arts & Sciences 2024
Advised By
Nikolaos G. Sgourakis
Associate Professor of Biochemistry and Biophysics

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