title: Contacts-based prediction of binding affinity in protein-protein complexes.
abstract: Almost all critical functions in cells rely on specific protein-protein interactions. Understanding these is therefore crucial in the investigation of biological systems. Despite all past efforts, we still lack a thorough understanding of the energetics of association of proteins. Here, we introduce a new and simple approach to predict binding affinity based on functional and structural features of the biological system, namely the network of interfacial contacts. We assess its performance against a protein-protein binding affinity benchmark and show that both experimental methods used for affinity measurements and conformational changes have a strong impact on prediction accuracy. Using a subset of complexes with reliable experimental binding affinities and combining our contacts and contact-types-based model with recent observations on the role of the non-interacting surface in protein-protein interactions, we reach a high prediction accuracy for such a diverse dataset outperforming all other tested methods.
authors.affiliation: Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Faculty of Science-Chemistry, Utrecht University, Utrecht, Netherlands.
authors.forename: Anna
authors.initials: A
authors.lastname: Vangone
authors.affiliation: Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Faculty of Science-Chemistry, Utrecht University, Utrecht, Netherlands.
authors.forename: Alexandre Mjj
authors.identifier: http://orcid.org/0000-0001-7369-1322
authors.initials: AM
authors.lastname: Bonvin
mesh_terms: D019295:Computational Biology / Q000379:methods*; D008967:Molecular Biology / Q000379:methods*; D011485:Protein Binding; D060066:Protein Interaction Maps
keywords: binding affinity; biophysics; buried surface area; non-interacting surface; none; protein contacts; protein–protein complexes; protein–protein interactions; structural biology