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A multilayer screening approach toward the discovery of novel Pf-DHFR inhibitors
Affiliation:1. Laboratoire de Chimie des Matériaux, Faculté des Sciences de Bizerte, 7021 Zarzouna, Tunisia;2. Laboratoire CRM2 (Cristallographie, Résonance Magnétique et Modélisations), BP 70239, 54506 Vandoeuvre lès Nancy Cedex, France;3. Laboratoire de Chimie Organométallique de Surface (LCOMS), Ecole Supérieure de Chimie Physique Electronique, 69622 Villeurbanne Cedex, France;1. New Technologies – Research Center, University of West Bohemia, Univerzitni 8, 306 14 Pilsen, Czech Republic;2. Center of Excellence Geopolymer and Green Technology, School of Material Engineering, University Malaysia Perlis, 01007 Kangar, Perlis, Malaysia
Abstract:A small yet diverse xanthone library was build and computationally docked against wild type Pf-DHFR by Molegro Virtual Docker (MolDock). For analysis of results an integrated approach based on re-ranking, scaling (based on heavy atom counts), pose clustering and visual inspection was implemented. Standard methods such as self-docking (for docking), EF analysis, average rank determinations (for size normalization), and cluster quality indices (for pose clustering) were used for validation of results. Three compounds X5, X113A and X164B displayed contact footprints similar to the known inhibitors with good scores. Finally, 16 compounds were extracted from ZINC data base by similarity based screening, docking score and drug/lead likeness. Out of these 16 compounds, 11 displayed very close contact footprints to experimentally known inhibitors, indicating there potential utility in further drug discovery efforts.
Keywords:Contact footprint  Docking  Size normalization  Re-ranking  MolDock
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