Retrospective docking study of PDE4B ligands and an analysis of the behavior of selected scoring functions.
Scoring forms a major obstacle to the success of any docking study. In general, fast scoring functions perform poorly when used to determine the relative affinity of ligands for their receptors. In this study, the objective was not to rank compounds with confidence but simply to identify a scoring method which could provide a 4-fold hit enrichment in a screening sample over random selection. To this end, LigandFit, a fast shape matching docking algorithm, was used to dock a variety of known inhibitors of type 4 phosphodiesterase (PDE4B) into its binding site determined crystallographically for a series of pyrazolopyridine inhibitors. The success of identifying good poses with this technique was explored through RMSD comparisons with 19 known inhibitors for which crystallographic structures were available. The effectiveness of five scoring functions (PMF, JAIN, PLP2, LigScore2, and DockScore) was then evaluated through consideration of the success in enriching the top ranked fractions of nine artificial databases, constructed by seeding 1980 inactive ligands (pIC50 < 5) with 20 randomly selected inhibitors (pIC50 > 6.5). PMF and JAIN showed high average enrichment factors (greater than 4 times) in the top 5-10% of the ranked databases. Rank-based consensus scoring was then investigated, and the rational combination of 3 scoring functions resulted in more robust scoring schemes with (cScore)-DPmJ (consensus score of DockScore, PMF, and JAIN) and (cScore)-PPmJ (PLP2, PMF, and JAIN) yielding particularly good results. These cScores are believed to be of greater general application. Finally, the analysis of the behavior of the scoring functions across different chemotypes uncovered the inherent bias of the docking and scoring toward compounds in the same structural family as that employed for the crystal structure, suggesting the need to use multiple versions of the binding site for more successful virtual screening strategies.
Mpamhanga
Chidochangu P
CP
Department of Chemistry, University of Sheffield, Dainton Building, Brookhill, Sheffield S3 7HF, U.K.
Chen
Beining
B
McLay
Iain M
IM
Ormsby
Daniel L
DL
Lindvall
Mika K
MK
D015105:3',5'-Cyclic-AMP Phosphodiesterases / Q000037:antagonists & inhibitors* / Q000378:metabolism*; D000465:Algorithms; D054703:Cyclic Nucleotide Phosphodiesterases, Type 4; D005544:Forecasting; D008024:Ligands; D008958:Models, Molecular; D010726:Phosphodiesterase Inhibitors / Q000494:pharmacology*; D011485:Protein Binding; D012106:Research / Q000706:statistics & numerical data; D012107:Research Design
D008024:Ligands; D010726:Phosphodiesterase Inhibitors; D015105:3',5'-Cyclic-AMP Phosphodiesterases; D054703:Cyclic Nucleotide Phosphodiesterases, Type 4