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Predictive Models of Peptide RMS Fluctuations in the Context of HLA‐A*02:01 Through Sequence Alone
Author(s) -
Ayres Cory,
Riley Timothy,
Corcelli Steven,
Baker Brian
Publication year - 2017
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.31.1_supplement.601.4
Subject(s) - t cell receptor , peptide , context (archaeology) , immunogenicity , human leukocyte antigen , molecular dynamics , major histocompatibility complex , sequence (biology) , computational biology , chemistry , physics , biophysics , biology , t cell , antigen , biochemistry , genetics , gene , immune system , computational chemistry , paleontology
Much of the current day understanding of T‐Cell receptor (TCR) recognition of peptide major histocompatibility complexes (pMHCs) is based on studies of crystal structures of TCR/pMHC complexes. Though insightful, these studies fail to directly investigate the role of dynamics in these interactions. Accordingly, recent effort has gone into characterizing differences in dynamics of these proteins, and relating them to affinity, stability and immunogenicity. In particular, in a recent study we observed a relationship between differences in RMS fluctuations of wild‐type and tumor derived peptides, and whether the tumor derived peptide was immunogenic. While utilizing differences in peptide dynamics to predict immunogenicity seems promising, the method is limited by computational cost and time required to generate the necessary molecular dynamics simulations. As such, we sought to generate models to predict RMS fluctuations of a peptide through sequence alone. Predictive models based on 53 1μs simulations of HLA‐A*02:01 presenting different nonameric peptides. Through differences in chemical composition, seven models were generated which predict the Cα RMS fluctuations of a theoretical nonameric peptide. These models provide accurate predictions of expected RMS fluctuations, and also highlight how a single point mutation can impact the fluctuations of distal peptide residues.