Journal of Chemical Information and Modeling
Journal of Chemical Information and Modeling
5 years ago

Proteochemometrics-Based Prediction of Peptide Binding to HLA-DP Proteins

Proteochemometrics-Based Prediction of Peptide Binding to HLA-DP Proteins
Ivan Dimitrov, Ventsislav Yordanov, Irini Doytchinova
Human leukocyte antigens (HLA) class II proteins are involved in the antigen processing in the antigen presenting cells. They form complexes with antigen peptide fragments. The peptide–HLA protein complexes are presented on the cell surface where they are recognized by helper T cells (Th cells). HLA-DP is one of the three HLA class II loci. The HLA-DP proteins are associated with a significant number of autoimmune diseases, as well as with a susceptibility or resistance to a number of infectious agents. In the present study, we apply proteochemometrics—a method for bioactivity modeling of multiple ligands binding to multiple target proteins—to derive and validate a robust model for peptide binding prediction to the 7 most frequent HLA-DP proteins. The model is able to identify 86% of the binders in the top 10% of the best predicted nonamers generated from one protein.

Publisher URL: http://dx.doi.org/10.1021/acs.jcim.7b00026

DOI: 10.1021/acs.jcim.7b00026

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