Applying Side-chain Flexibility in Motifs for Protein Docking

Conventional rigid docking algorithms have been unsatisfactory in their computational results, largely due to the fact that protein structures are flexible in live environments. In response, we propose to introduce the side-chain flexibility in protein motif into the docking. First, the Morse theory is applied to curvature labeling and surface region growing, for segmentation of the protein surface into smaller patches. Then, the protein is described by an ensemble of conformations that incorporate the flexibility of interface side chains and are sampled using rotamers. Next, a 3D rotation invariant shape descriptor is proposed to deal with the flexible motifs and surface patches; thus, pairwise complementarity matching is needed only between the convex patches of ligand and the concave patches of receptor. The iterative closest point (ICP) algorithm is implemented for geometric alignment of the two 3D protein surface patches. Compared with the fast Fourier transform-based global geometric matching algorithm and other methods, our FlexDock system generates much less false-positive docking results, which benefits identification of the complementary candidates. Our computational experiments show the advantages of the proposed flexible docking algorithm over its counterparts.