| Abstract
| - A two-step, fully automatic virtual screening procedure consisting of flexible docking followedby activity prediction by COMparative BINding Energy (COMBINE) analysis is presented.This novel approach has been successfully applied, as an example with medicinal chemistryinterest, to a recently reported series of 133 factor Xa (fXa) inhibitors whose activitiesencompass 4 orders of magnitude. The docking algorithm is linked to the COMBINE analysisprogram and used to derive independent regression models of the 133 inhibitors docked withinthree different fXa structures (PDB entries 1fjs, 1f0r, and 1xka), so as to explore the effect ofreceptor conformation on the overall results. Reliable docking conformations and predictiveregression models requiring eight latent variables could be derived for two of the fXa structures,with the best model achieving a Q of 0.63 and a standard deviation of errors of prediction(SDEP) of 0.51 (leave-one-out). The two-step procedure was then employed to screen a designedvirtual library of 112 ligands, containing both active and inactive compounds. While dockingenergies alone could show a good performance for selecting hits, including structurally diverseones, inclusion of COMBINE analysis regression models provided improved rankings for theidentification of structurally related molecules in external sets. In our best case, a recognitionrate of ∼80% of known binders at ∼15% false positives rate was achieved, corresponding to anenrichment factor of ∼450% over random.
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