Evolutionary-docking targeting bacterial FtsZ

To accurately predict binding of inhibitors to the FtsZ cell division protein of the antibiotic-resistance Staphilococcus aureus pathogen, evolutionary library docking, ligand-efficiency predictions and rank consensus docking strategies have been sequentially applied. Starting from the crystallographic FtsZ bound model of the PC190723 reference ligand, fragments were derived to generate children molecules fitting low docking-scores with low molecular sizes and hydrophobicities using the DataWarrior Build Evolutionary Library. PC190723 fragment children molecules combined with toxicity filters, and consensus ranks with ligand efficiencies and AutoDockVina docking, identified new benzamide and non-benzamide chemotypes with nanomolar docking-scores and improved specificities to continue with anti-FtsZ ligand investigations