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Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity.

Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity.
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Bassani-Sternberg M, Chong C, Guillaume P, Solleder M, Pak H, Gannon PO, Kandalaft LE, Coukos G, Gfeller D,


Bassani-Sternberg M, Chong C, Guillaume P, Solleder M, Pak H, Gannon PO, Kandalaft LE, Coukos G, Gfeller D, (click to view)

Bassani-Sternberg M, Chong C, Guillaume P, Solleder M, Pak H, Gannon PO, Kandalaft LE, Coukos G, Gfeller D,

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PLoS computational biology 2017 08 2313(8) e1005725 doi 10.1371/journal.pcbi.1005725
Abstract

The precise identification of Human Leukocyte Antigen class I (HLA-I) binding motifs plays a central role in our ability to understand and predict (neo-)antigen presentation in infectious diseases and cancer. Here, by exploiting co-occurrence of HLA-I alleles across ten newly generated as well as forty public HLA peptidomics datasets comprising more than 115,000 unique peptides, we show that we can rapidly and accurately identify many HLA-I binding motifs and map them to their corresponding alleles without any a priori knowledge of HLA-I binding specificity. Our approach recapitulates and refines known motifs for 43 of the most frequent alleles, uncovers new motifs for 9 alleles that up to now had less than five known ligands and provides a scalable framework to incorporate additional HLA peptidomics studies in the future. The refined motifs improve neo-antigen and cancer testis antigen predictions, indicating that unbiased HLA peptidomics data are ideal for in silico predictions of neo-antigens from tumor exome sequencing data. The new motifs further reveal distant modulation of the binding specificity at P2 for some HLA-I alleles by residues in the HLA-I binding site but outside of the B-pocket and we unravel the underlying mechanisms by protein structure analysis, mutagenesis and in vitro binding assays.

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