Consistent improvement of cross-docking results using binding site ensembles generated with elastic network normal modes

Abstract

The representation of protein flexibility is still a challenge for the state-of-the-art flexible ligand docking protocols. In this article, we use a large and diverse benchmark to prove that is possible to improve consistently the cross-docking performance against a single receptor conformation, using an equilibrium ensemble of binding site conformers. The benchmark contained 28 proteins, and our method predicted the top-ranked near native ligand poses 20% more efficiently than using a single receptor. The multiple conformations were derived from the collective variable space defined by all heavy-atom elastic network normal modes, including backbone and side chains. We have found that the binding site displacements for best positioning of the ligand seem rather independent from the global collective motions of the protein. We also found that the number of binding site conformations needed to represent nonredundant flexibility was < 100. The ensemble of receptor conformations can be generated at our Web site at http://abagyan.scripps.edu/MRC.

Figure 1

A schematic outline of the Normal Mode Analysis MRC algorithm.

Figure 2

MRC methodology applied to the estrogen receptor protein, PDBid: 3ERT. (a) Example of the residues included in the elastic network normal mode analysis with a sphere radius of 10 Å around 4-Hydroxytamoxifene. (b) Cross docking of Raloxifene in the pocket of conformation of 3ERT. Mainly due to the positions of M421, L523 and L539, the best result that can be achieved employing a single receptor is a high energy pose at 1.7 Å RMSD to crystallographic position. (c) Using MRC is it possible to obtain a very low energy ligand pose at 1.2 Å RMSD. The experimental structures are reported in blue, the multiple receptor conformations are grey and the cross docking ligand poses are coloured by atom type.

Figure 3

Success rate for cross docking experiments using 1, 5, 10, 25, 50 and 200 protein conformations. A value of 100% indicates success in the 28 proteins. The colours show if the rank of the first near native solution (NNs) has the lowest energy score, is within the first 5 or within the first 10. Note that for MRC, the results are shown with the experimental protein included (+EXP) and excluded (-EXP).

Figure 4

Effect of the geometric clustering (side chains) on the global success in cross docking experiments. A value of 100% indicates success in the 28 proteins. The colours show if the rank of the first near native solution (NNs) has the lowest energy score, is within the first 5 or within the first 10. Note that the convergence is obtained with a 0.6 Å vicinity.