Molecular docking of balanol to dynamics snapshots of protein kinase A.
Even if the structure of a receptor has been determined experimentally, it may not be a conformation to which a ligand would bind when induced fit effects are significant. Molecular docking using such a receptor structure may thus fail to recognize a ligand to which the receptor can bind with reasonable affinity. Here, we examine one way to alleviate this problem by using an ensemble of receptor conformations generated from a molecular dynamics simulation for molecular docking. Two molecular dynamics simulations were conducted to generate snapshots for protein kinase A: one with the ligand bound, the other without. The ligand, balanol, was then docked to conformations of the receptors presented by these trajectories. The Lamarckian genetic algorithm in Autodock [Goodsell et al. J Mol Recognit 1996;9(1):1-5; Morris et al. J Comput Chem 1998;19(14):1639-1662] was used in the docking. Three ligand models were used: rigid, flexible, and flexible with torsional potentials. When the snapshots were taken from the molecular dynamics simulation of the protein-ligand complex, the correct docking structure could be recovered easily by the docking algorithm in all cases. This was an easier case for challenging the docking algorithm because, by using the structure of the protein in a protein-ligand complex, one essentially assumed that the protein already had a pocket to which the ligand can fit well. However, when the snapshots were taken from the ligand-free protein simulation, which is more useful for a practical application when the structure of the protein-ligand complex is not known, several clusters of structures were found. Of the 10 docking runs for each snapshot, at least one structure was close to the correctly docked structure when the flexible-ligand models were used. We found that a useful way to identify the correctly docked structure was to locate the structure that appeared most frequently as the lowest energy structure in the docking experiments to different snapshots.
Wong
Chung F
CF
Department of Chemistry and Biochemistry, University of Missouri-St. Louis, Missouri 63121, USA. wongch@umsl.edu
Kua
Jeremy
J
Zhang
Yingkai
Y
Straatsma
T P
TP
McCammon
J Andrew
JA
D001381:Azepines / Q000737:chemistry* / Q000494:pharmacology; D003198:Computer Simulation; D017868:Cyclic AMP-Dependent Protein Kinases / Q000037:antagonists & inhibitors / Q000737:chemistry* / Q000378:metabolism*; D004791:Enzyme Inhibitors / Q000737:chemistry / Q000494:pharmacology; D062385:Hydroxybenzoates / Q000737:chemistry* / Q000494:pharmacology; D007700:Kinetics; D008024:Ligands; D008958:Models, Molecular; D008968:Molecular Conformation; D011485:Protein Binding; D013314:Stress, Mechanical
D001381:Azepines; D004791:Enzyme Inhibitors; D062385:Hydroxybenzoates; D008024:Ligands; C015405:ophiocordin; D017868:Cyclic AMP-Dependent Protein Kinases