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Summary Distinguishing biologically relevant interfaces from crystallographic ones in biological complexes is fundamental in order to associate cellular functions to the correct macromolecular assemblies. Recently, we described a detailed study reporting the differences in the type of intermolecular residue–residue contacts between biological and crystallographic interfaces. Our findings allowed us to develop a fast predictor of biological interfaces reaching an accuracy of 0.92 and competitive to the current state of the art. Here we present its web-server implementation, PRODIGY-CRYSTAL, aimed at the classification of biological and crystallographic interfaces. PRODIGY-CRYSTAL has the advantage of being fast, accurate and simple. This, together with its user-friendly interface and user support forum, ensures its broad accessibility. Availability and implementation PRODIGY-CRYSTAL is freely available without registration requirements at https://haddock.science.uu.nl/services/PRODIGY-CRYSTAL.

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 PROtein binDIng enerGY prediction (PRODIGY), a web server to predict the binding affinity of protein–protein complexes from their 3D structure. The PRODIGY server implements our simple but highly effective predictive model based on intermolecular contacts and properties derived from non-interface surface. Availability and Implementation: PRODIGY is freely available at: http://milou.science.uu.nl/services/PRODIGY. Contact: a.m.j.j.bonvin@uu.nl, a.vangone@uu.nl

Although many advanced and sophisticated ab initio approaches for modeling protein–protein complexes have been proposed in past decades, template-based modeling (TBM) remains the most accurate and widely used approach, given a reliable template is available. However, there are many different ways to exploit template information in the modeling process. Here, we systematically evaluate and benchmark a TBM method that uses conserved interfacial residue pairs as docking distance restraints [referred to as alpha carbon–alpha carbon (CA-CA)-guided docking]. We compare it with two other template-based protein–protein modeling approaches, including a conserved non-pairwise interfacial residue restrained docking approach [referred to as the ambiguous interaction restraint (AIR)-guided docking] and a simple superposition-based modeling approach. Our results show that, for most cases, the CA-CA-guided docking method outperforms both superposition with refinement and the AIR-guided docking method. We emphasize the superiority of the CA-CA-guided docking on cases with medium to large conformational changes, and interactions mediated through loops, tails or disordered regions. Our results also underscore the importance of a proper refinement of superimposition models to reduce steric clashes. In summary, we provide a benchmarked TBM protocol that uses conserved pairwise interface distance as restraints in generating realistic 3D protein–protein interaction models, when reliable templates are available. The described CA-CA-guided docking protocol is based on the HADDOCK platform, which allows users to incorporate additional prior knowledge of the target system to further improve the quality of the resulting models.

We here present a detailed study of the ligand-receptor interactions between single and triple-helical strands of collagen and the α2A domain of integrin (α2A), providing valuable new insights into the mechanisms and dynamics of collagen-integrin binding at a sub-molecular level. The occurrence of single and triple-helical strands of the collagen fragments was scrutinized with atom force microscopy (AFM) techniques. Strong interactions of the triple-stranded fragments comparable to those of collagen can only be detected for the 42mer triple-helical collagen-like peptide under study (which contains 42 amino acid residues per strand) by solid phase assays as well as by surface plasmon resonance (SPR) measurements. However, changes in NMR signals during titration and characteristic saturation transfer difference (STD) NMR signals are also detectable when α2A is added to a solution of the 21mer single-stranded collagen fragment. Molecular dynamics (MD) simulations employing different sets of force field parameters were applied to study the interaction between triple-helical or single-stranded collagen fragments with α2A. It is remarkable that even single-stranded collagen fragments can form various complexes with α2A showing significant differences in the complex stability with identical ligands. The results of MD simulations are in agreement with the signal alterations in our NMR experiments, which are indicative of the formation of weak complexes between single-stranded collagen and α2A in solution. These results provide useful information concerning possible interactions of α2A with small collagen fragments that are of relevance to the design of novel therapeutic A-domain inhibitors.