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

Ovidiu Ivanciuc, Werner Braun

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

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 E1-E5. 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.

Original languageEnglish (US)
Pages (from-to)903-916
Number of pages14
JournalProtein and Peptide Letters
Volume14
Issue number9
DOIs
StatePublished - Sep 2007

Fingerprint

Major Histocompatibility Complex
Quantitative Structure-Activity Relationship
Peptides
Molecules
T-Cell Antigen Receptor
Protein Databases
Proteins
Amino Acids
Processing

Keywords

  • Amino acid descriptors
  • Major histocompatibility complex
  • Peptide binding affinity
  • Quantitative structure-activity relationships

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology

Cite this

Robust quantitative modeling of peptide binding affinities for MHC molecules using physical-chemical descriptors. / Ivanciuc, Ovidiu; Braun, Werner.

In: Protein and Peptide Letters, Vol. 14, No. 9, 09.2007, p. 903-916.

Research output: Contribution to journalArticle

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