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Building proteomic tool boxes to monitor MHC class I and class II peptides
Author(s) -
Schumacher FrancesRose,
Delamarre Lélia,
Jhunjhunwala Suchit,
Modrusan Zora,
Phung Qui T.,
Elias Joshua E.,
Lill Jennie R.
Publication year - 2017
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201600061
Subject(s) - computational biology , major histocompatibility complex , epitope , mhc class i , biology , informatics , class (philosophy) , workflow , computer science , immune system , bioinformatics , immunology , antigen , artificial intelligence , engineering , database , electrical engineering
Major histocompatibility complex Class I (MHCI) and Class II (MHCII) presented peptides powerfully modulate T cell immunity and play a vital role in generating effective anti‐tumor and anti‐viral immune responses in mammals. Characterizing these MHCI or MHCII presented peptides can help generate therapeutic treatments, afford information on T cell mediated biomarkers, provide insight into disease progression, and reduce adverse anti‐drug side effects from engineered biotherapeutics. Here, we explore the tools and techniques commonly employed to discover both MHCI‐ and MHCII‐presented peptides. We describe complementary strategies that enhance the characterization of these peptides and the informatics tools employed for both predicting and characterizing MHCI‐ and MHCII‐presented epitopes. The evolution of methodologies for isolating MHC‐presented peptides is discussed, as are the mass spectrometric workflows that can be employed for their characterization. We provide a perspective on where this field is headed, and how these tools may be applicable to the discovery and monitoring of epitopes in a variety of scenarios.