Summary: Gaining insights into the structural determinants of protein-protein interactions holds the key for a deeper understanding of biological functions, diseases and development of therapeutics. An important aspect of this is the ability to accurately predict the binding strength for a given protein-protein complex. Here we present PRODIGY, a web server to predict the binding affinity of protein-protein complexes from their three-dimensional structure. The PRODIGY server implements our simple but highly effective predictive model based on intermolecular contacts and properties derived from non-interface surface.

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.

Summary: Herein we present COCOMAPS, a novel tool for analyzing, visualizing and comparing the interface in protein–protein and protein–nucleic acids complexes. COCOMAPS combines traditional analyses and 3D visualization of the interface with the effectiveness of intermolecular contact maps. Availability: COCOMAPS is accessible as a public web tool at http://www.molnac.unisa.it/BioTools/cocomaps Contact:romina.oliva@uniparthenope.it; lcavallo@unisa.it

Summary: Recently we published PROtein binDIng enerGY (PRODIGY), a web-server for the prediction of binding affinity in protein–protein complexes. By using a combination of simple structural properties, such as the residue-contacts made at the interface, PRODIGY has demonstrated a top performance compared with other state-of-the-art predictors in the literature. Here we present an extension of it, named PRODIGY-LIG, aimed at the prediction of affinity in protein-small ligand complexes. The predictive method, properly readapted for small ligand by making use of atomic instead of residue contacts, has been successfully applied for the blind prediction of 102 protein–ligand complexes during the D3R Grand Challenge 2. PRODIGY-LIG has the advantage of being simple, generic and applicable to any kind of protein-ligand complex. It provides an automatic, fast and user-friendly tool ensuring broad accessibility.Availability and implementation: PRODIGY-LIG is freely available without registration requirements at http://milou.science.uu.nl/services/PRODIGY-LIG.

Biomolecular interactions between proteins regulate and control almost every biological process in the cell. Understanding these interactions is therefore a crucial step in the investigation of biological systems and in drug design. Many efforts have been devoted to unravel principles of protein-protein interactions. Recently, we introduced a simple but robust descriptor of binding affinity based only on structural properties of a protein-protein complex. In Vangone and Bonvin (2015), we demonstrated that the number of interfacial contacts at the interface of a protein-protein complex correlates with the experimental binding affinity. Our findings have led one of the best performing predictor so far reported (Pearson’s Correlation r = 0.73; RMSE = 1.89 kcal mol-1). Despite the importance of the topic, there is surprisingly only a limited number of online tools for fast and easy prediction of binding affinity. For this reason, we implemented our predictor into the user-friendly PRODIGY web-server. In this protocol, we explain the use of the PRODIGY web-server to predict the affinity of a protein-protein complex from its three-dimensional structure. The PRODIGY server is freely available at: http://milou.science.uu.nl/services/PRODIGY.