Protein-Protein Interaction Prediction by using Amino Acids Interaction Pattern in Rigid-Body Docking Process

Abstract

We approached to prediction of protein-protein interactions using rigid-body docking algorithm, generating many decoys including false positives. To search near-native decoys from a decoy set generated by a docking process, cluster analysis is useful with calculating similarities between decoys. However, this analysis goes well only in the case that a decoy set includes near-native decoys. Actually, there are some cases of protein pairs with no near-native decoys after an initial docking process.This problem is related with a size of docking search spaces. When a size of search space is small, near-native decoys cannot be obtained after a rigid-body docking process. We then applied a profile method to obtain a region including native interacting residue pairs for re-docking process by using Profile of Interaction FingerPrints (P-IFP).Interaction FingerPrints (IFP) has been developed for the post-docking analysis of protein-protein rigid-body docking. IFP is composed of binary states of interacting amino acid residues of each interacting proteins, as a scale for measuring unique similarities between the complex structures. Then, IFP can be used more easily to evaluate similarities between decoys than RMSD method, which depends on methods of superposing their structures. Additionally, IFP can be useful to assemble interaction profiles from various decoys.In this work, we examined re-docking process after generating P-IFP for rigid-body docking decoys. As results, we could obtain a set of decoys with higher similarities than that of decoys generated in the initial docking process. Re-docking method using the IFP method is expected to improve cases without near-native decoys in an initial docking process.