Enhancing antigenic peptide discovery: Improved MHC-I binding prediction and methodology

被引:1
|
作者
Gizinski, Stanislaw [1 ]
Preibisch, Grzegorz [1 ,2 ]
Kucharski, Piotr [1 ]
Tyrolski, Michal [1 ]
Rembalski, Michal [1 ]
Grzegorczyk, Piotr [1 ]
Gambin, Anna [2 ]
机构
[1] Deepflare, Warsaw, Poland
[2] Univ Warsaw, Dept Math Informat & Mech, Warsaw, Poland
关键词
Major histocompatibility complex; BERT; Peptide presentation prediction; Benchmark dataset; DECONVOLUTION;
D O I
10.1016/j.ymeth.2024.01.016
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The Major Histocompatibility Complex (MHC) is a critical element of the vertebrate cellular immune system, responsible for presenting peptides derived from intracellular proteins. MHC-I presentation is pivotal in the immune response and holds considerable potential in the realms of vaccine development and cancer immunotherapy. This study delves into the limitations of current methods and benchmarks for MHC-I presentation. We introduce a novel benchmark designed to assess generalization properties and the reliability of models on unseen MHC molecules and peptides, with a focus on the Human Leukocyte Antigen (HLA)-a specific subset of MHC genes present in humans. Finally, we introduce HLABERT, a pretrained language model that outperforms previous methods significantly on our benchmark and establishes a new state-of-the-art on existing benchmarks.
引用
收藏
页码:1 / 9
页数:9
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