Achieving reliability and high accuracy in automated protein docking: ClusPro, PIPER, SDU, and stability analysis in CAPRI rounds 13-19

Abstract

Our approach to protein-protein docking includes three main steps. First, we run PIPER, a rigid body docking program based on the Fast Fourier Transform (FFT) correlation approach, extended to use pairwise interactions potentials. Second, the 1000 best energy conformations are clustered, and the 30 largest clusters are retained for refinement. Third, the stability of the clusters is analyzed by short Monte Carlo simulations, and the structures are refined by the medium-range optimization method SDU. The first two steps of this approach are implemented in the ClusPro 2.0 protein-protein docking server. Despite being fully automated, the last step is computationally too expensive to be included in the server. When comparing the models obtained in CAPRI rounds 13-19 by ClusPro, by the refinement of the ClusPro predictions and by all predictor groups, we arrived at three conclusions. First, for the first time in the CAPRI history, our automated ClusPro server was able to compete with the best human predictor groups. Second, selecting the top ranked models, our current protocol reliably generates high-quality structures of protein-protein complexes from the structures of separately crystallized proteins, even in the absence of biological information, provided that there is limited backbone conformational change. Third, despite occasional successes, homology modeling requires further improvement to achieve reliable docking results.

Figure 1

(A) Rnd1/RBD of plexin B1 (target T30). Refined prediction of the Plexin-B1 RBD domain (cyan), superimposed on the bound structure of RBD (green). The bound receptor, Rnd1, is shown in gray (PDB code 2REX). (B) Savinase - BASI complex (target T32). Comparison of the ClusPro starting model M05 (brown) and the top refined model M01 (cyan). The refinement results in a shift of the interacting loop of the ligand along the receptor cavity (gray). (C) Savinase - BASI complex (target T32). The high quality prediction M01 (cyan) is very close to the position of the bound ligand (green) in the x-ray structure of the complex (PDB code 3BX1). The receptor surface is shown in gray. (D) Centaurin-α1/KF13B FHA complex (target T39). Refined prediction of FHA (cyan), superimposed on the bound structure of FHA (green). The receptor, Centaurin-α1, is shown in gray (PDB code 3FM8). (E) Bovine trypsin - double arrowhead protease inhibitor complex (target T40), interaction mode CA. We compare our high quality prediction, model M01 (cyan), to the experimental ligand position shown in green (pdb code 3E8L). The Lys145 loop of the ligand is involved in the interface. Trypsin is shown as gray surface. (F) Bovine trypsin - double arrowhead protease inhibitor complex (target T40), interaction mode CB. We compare our high quality prediction, model M02 (cyan), to the experimental ligand position shown in green (pdb code 3E8L). The Leu87 loop of the ligand is involved in the interface. Trypsin is shown as gray surface. (G) Designed TPR trimer (target T42). ClusPro model M08 of one subunit (cyan), superimposed on the bound dimer subunits shown in green and gray (PDB code 2WQH). (H) Designed TPR trimer (Target T42). ClusPro model M01 (cyan), and symmetry mates in 1NA0 (magenta) and 1NA3 (cyan) relative to bound receptor (gray).