4.2 Article

Robust quantitative modeling of peptide binding affinities for MHC molecules using physical-chemical descriptors

Journal

PROTEIN AND PEPTIDE LETTERS
Volume 14, Issue 9, Pages 903-916

Publisher

BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/092986607782110257

Keywords

major histocompatibility complex; peptide binding affinity; quantitative structure-activity relationships; amino acid descriptors

Funding

  1. NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [R01AI064913] Funding Source: NIH RePORTER
  2. NIAID NIH HHS [R01 AI064913-03, R01 AI064913, R01 AI064913-04, R01 AI 064193] Funding Source: Medline

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Major histocompatibility complex (MHC) molecules bind short peptides resulting from intracellular processing of foreign and self proteins, and present them on the cell surface for recognition by T-cell receptors. We propose a new robust approach to quantitatively model the binding affinities of MHC molecules by quantitative structure-activity relationships (QSAR) that use the physical-chemical amino acid descriptors E-1-E-5. These QSAR models are robust, sequence-based, and can be used as a fast and reliable filter to predict the MHC binding affinity for large protein databases.

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