A knowledge-based scoring function to assess the stability of quaternary protein assemblies

Motivation: Elucidation of protein-protein interactions is a necessary step towards understanding the complete repertoire of cellular biochemistry. Given the enormity of the problem, the expenses and limitations of experimental methods, it is imperative that this problem is tackled computationally. In silico predictions of protein interactions entail sampling different conformations of the purported complex and then scoring these to assess for interaction viability. In this study we have devised a new scheme for scoring protein-protein interactions. Results: Our method, PIZSA (Protein Interaction Z Score Assessment) is a binary classification scheme for identification of stable protein quaternary assemblies (binders/non-binders) based on statistical potentials. The scoring scheme incorporates residue-residue contact preference on the interface with per residue-pair atomic contributions and accounts for clashes. PIZSA can accurately discriminate between native and non-native structural conformations from protein docking experiments and outperform other recently published scoring functions, demonstrated through testing on a benchmark set and the CAPRI Score_set. Though not explicitly trained for this purpose, PIZSA potentials can identify spurious interactions that are artefacts of the crystallization process. Availability: PIZSA is implemented as a webserver at http://cospi.iiserpune.ac.in/pizsa/.