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Detalle de: Modeling binding affinity of pathological mutations for computational protein design

Title Modeling binding affinity of pathological mutations for computational protein design
Abstract

An important aspect of protein functionality is the formation of specific complexes with other proteins, which are involved in the majority of biological processes. The functional characterization of such interactions at molecular level is necessary, not only to understand biological and pathological phenomena but also to design improved, or even new interfaces, or to develop new therapeutic approaches. X-ray crystallography and NMR spectroscopy have increased the number of 3D protein complex structures deposited in the Protein Data Bank (PDB). However, one of the more challenging objectives in biological research is to functionally characterize protein interactions and thus identify residues that significantly contribute to the binding. Considering that the experimental characterization of protein interfaces remains expensive, time-consuming, and labor-intensive, computational approaches represent a significant breakthrough in proteomics, assisting or even replacing experimental efforts. Thanks to the technological advances in computing and data processing, these techniques now cover a vast range of protocols, from the estimation of the evolutionary conservation of amino acid positions in a protein, to the energetic contribution of each residue to the binding affinity. In this chapter, we review several existing computational protocols to model the phylogenetic, structural, and energetic properties of residues within protein-protein interfaces.

Apa Reference Romero-Durana, M., Pallara, C., Glaser, F., & Fernández-Recio, J. (2016). Modeling Binding Affinity of Pathological Mutations for Computational Protein Design. Computational Protein Design, 139–159. 10.1007/978-1-4939-6637-0_6
Doi 10.1007/978-1-4939-6637-0_6
Publication Date 3 Dec 2016
Publication Type Book / chapter
Researcher Juan Fernández Recio
Ontology Experimental structure determination, Conservation Analysis, Phylogenetic Analysis, Proteomics, Molecular Interactions/Docking, Protein/Nucleic Acid design
Research Groups Structural Bioinformatics, Modeling and Biological Mechanisms
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