BP-Dock: a flexible docking scheme for exploring protein-ligand interactions based on unbound structures

Abstract

Molecular docking serves as an important tool in modeling protein-ligand interactions. However, it is still challenging to incorporate overall receptor flexibility, especially backbone flexibility, in docking due to the large conformational space that needs to be sampled. To overcome this problem, we developed a novel flexible docking approach, BP-Dock (Backbone Perturbation-Dock) that can integrate both backbone and side chain conformational changes induced by ligand binding through a multi-scale approach. In the BP-Dock method, we mimic the nature of binding-induced events as a first-order approximation by perturbing the residues along the protein chain with a small Brownian kick one at a time. The response fluctuation profile of the chain upon these perturbations is computed using the perturbation response scanning method. These response fluctuation profiles are then used to generate binding-induced multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, we applied our approach on a large and diverse data set using unbound structures as receptors. We also compared the BP-Dock results with bound and unbound docking, where overall receptor flexibility was not taken into account. Our results highlight the importance of modeling backbone flexibility in docking for recapitulating the experimental binding affinities, especially when an unbound structure is used. With BP-Dock, we can generate a wide range of binding site conformations realized in nature even in the absence of a ligand that can help us to improve the accuracy of unbound docking. We expect that our fast and efficient flexible docking approach may further aid in our understanding of protein-ligand interactions as well as virtual screening of novel targets for rational drug design.

Figure 1

Correlation plots of binding energy scores evaluated from X-Score vs experimental binding energies for HIV-1 protease (PR), carbonic anhydrase II (CA II), alcohol dehydrogenase (AD), alpha-thrombin (AT), and cytochrome C peroxidase (CCP).

Figure 2

Plot of average accuracy of χ₁ angle prediction as a function of χ₁ angle threshold (deg) for BP-Dock cross-docking and rigid cross-docking on HIV-1 protease bound structures (A) for two flexible residues (two ARG8s) and (B) for four flexible residues (two ARG8s and two ILE50s).

Figure 3

(A) Bound (2FZB) and unbound (2ACR) ribbon diagrams of aldose reductase are shown in red and blue, respectively. The RMSD for the loop region (encircled, Phe121–Val130) between the bound and unbound structures is ~0.6 Å. One of the perturbed conformations using the BP-Dock scheme (shown in green) is similar to the bound structure, especially around the specified loop. Hydrogen bond interactions are shown of the best docked poses from unbound docking of four tolrestat molecules with (B) rigid docking and (C) with flexible BP-Dock. The specified loop region is colored red. The hydrogen bond interactions are studied with Chimera, and the images are prepared using PyMOL.

Figure 4

(A) RosettaLigand energy score vs RMSD of the docked complex of CIPP with Class I and Class II peptides of syntenin. (B) Hydrogen bond interactions of CIPP with Class I and Class II peptides are shown as analyzed using the best docked pose obtained from flexible BP-Dock docking. Ribbon diagrams are prepared using PyMOL.

Figure 5

RosettaLigand energy score vs RMSD of PSD-95 with CRIPT and liprin peptides obtained from the flexible docking with (A) BP-Dock and (B) Backrub ensembles. Hydrogen bond interactions are shown for the CRIPT peptide with PSD-95 as analyzed using the lowest energy docked pose obtained from (C) BP-Dock and (D) Backrub ensembles. Ribbon diagrams are prepared using PyMOL.