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.
authors.affiliation: Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain.
authors.forename: Miguel
authors.initials: M
authors.lastname: Romero-Durana
authors.affiliation: Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain.
authors.forename: Chiara
authors.initials: C
authors.lastname: Pallara
authors.affiliation: Bioinformatics Knowledge Unit, The Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering Technion, Haifa, Israel.
authors.forename: Fabian
authors.initials: F
authors.lastname: Glaser
authors.affiliation: Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain. juanf@bsc.es.
authors.forename: Juan
authors.initials: J
authors.lastname: Fernández-Recio
mesh_terms: D000596:Amino Acids / Q000737:chemistry; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D030562:Databases, Protein; D008958:Models, Molecular; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D009154:Mutation; D011485:Protein Binding; D011487:Protein Conformation; D015202:Protein Engineering / Q000379:methods; D025941:Protein Interaction Mapping / Q000379:methods; D011506:Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D012984:Software; D064878:Web Browser
chemical_list: D000596:Amino Acids; D011506:Proteins
keywords: AMBER package; Biomolecular dynamics simulation; ConSurf; Evolutionary conservation; Hot-spots identification; In silico alanine scanning; Interface prediction; Protein–protein docking; Protein–protein interactions; pyDock