title: Efficient molecular docking of NMR structures: application to HIV-1 protease.
abstract: Docking ligands into an ensemble of NMR conformers is essential to structure-based drug discovery if only NMR structures are available for the target. However, sequentially docking ligands into each NMR conformer through standard single-receptor-structure docking, referred to as sequential docking, is computationally expensive for large-scale database screening because of the large number of NMR conformers involved. Recently, we developed an efficient ensemble docking algorithm to consider protein structural variations in ligand binding. The algorithm simultaneously docks ligands into an ensemble of protein structures and achieves comparable performance to sequential docking without significant increase in computational time over single-structure docking. Here, we applied this algorithm to docking with NMR structures. The HIV-1 protease was used for validation in terms of docking accuracy and virtual screening. Ensemble docking of the NMR structures identified 91% of the known inhibitors under the criterion of RMSD < 2.0 A for the best-scored conformation, higher than the average success rate of single docking of individual crystal structures (66%). In the virtual screening test, on average, ensemble docking of the NMR structures obtained higher enrichments than single-structure docking of the crystal structures. In contrast, docking of either the NMR minimized average structure or a single NMR conformer performed less satisfactorily on both binding mode prediction and virtual screening, indicating that a single NMR structure may not be suitable for docking calculations. The success of ensemble docking of the NMR structures suggests an efficient alternative method for standard single docking of crystal structures and for considering protein flexibility.
authors.affiliation: Department of Biochemistry, University of Missouri, Columbia, MO 65211, USA.
authors.forename: Sheng-You
authors.initials: SY
authors.lastname: Huang
authors.forename: Xiaoqin
authors.initials: X
authors.lastname: Zou
mesh_terms: D000465:Algorithms; D015195:Drug Design; D004353:Drug Evaluation, Preclinical; D016333:HIV Protease / Q000737:chemistry* / Q000378:metabolism*; D017320:HIV Protease Inhibitors / Q000737:chemistry / Q000494:pharmacology; D015497:HIV-1 / Q000187:drug effects / Q000201:enzymology; D006801:Humans; D066298:In Vitro Techniques; D008024:Ligands; D008958:Models, Molecular; D019906:Nuclear Magnetic Resonance, Biomolecular; D011485:Protein Binding; D014584:User-Computer Interface
chemical_list: D017320:HIV Protease Inhibitors; D008024:Ligands; D016333:HIV Protease