Identifying Protein-Protein Binding Sites with a Combined Energy Function

Determination of binding sites between proteins is widely applied in many fields, such as drug design and the structural and functional analysis. The protein-protein binding sites can be formed by two subunits in a complex. Understanding energetics and mechanisms of complexes remains one of the essential problems in binding site prediction. We develop a system, P-Binder, for identifying binding sites based on shape complementarity, side-chain conformations and interacting amino acid information. P-Binder utilizes an enumeration method to generate all possible configurations between two proteins, and uses a side-chain packing program to identify the bound states. The system reports the binding sites with the highest ranked configurations, evaluated through a linear combination of four statistical energy items. The experiments show that our method performs better than other prediction methods. A comparison with some existing approaches shows P-Binder to improve the success rate by at least 12.3%. We test P-Binder on 176 protein-protein complexes in Benchmark v4.0. The overall values of accuracy and coverage are 63.8% and 68.8% for the bound state, and 51.0% and 60.9% for the unbound state.