Structure-based Methods for Binding Mode and Binding Affinity Prediction for Peptide-MHC Complexes

(E-pub Ahead of Print)

Author(s): Dinler A. Antunes, Jayvee R. Abella, Didier Devaurs, Mauricio M. Rigo, Lydia E. Kavraki*.

Journal Name: Current Topics in Medicinal Chemistry

Abstract:

Understanding the mechanisms involved in the activation of an immune response is essential to many fields in human health, including vaccine development and personalized cancer immunotherapy. A central step in the activation of the adaptive immune response is the recognition, by T-cell lymphocytes, of peptides displayed by a special type of receptor known as Major Histocompatibility Complex (MHC). Considering the key role of MHC receptors in T-cell activation, the computational prediction of peptide binding to MHC has been an important goal for many immunological applications. Sequence-based methods have become the gold standard for peptide-MHC binding affinity prediction, but structure-based methods are expected to provide more general predictions (i.e., predictions applicable to all types of MHC receptors). In addition, structural modeling of peptide-MHC complexes has the potential to uncover yet unknown drivers of T-cell activation, thus allowing for the development of better and safer therapies. In this review, we discuss the use of computational methods for the structural modeling of peptide-MHC complexes (i.e., binding mode prediction) and for the structure-based prediction of binding affinity.

Keywords: molecular docking, binding mode prediction, binding affinity prediction, peptide-MHC complexes, immunogenicity, T-cell activation

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(E-pub Ahead of Print)
DOI: 10.2174/1568026619666181224101744
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