Vieira TF, Magalhaes RP and Sousa SF*
Department of Biomedicine, University of Porto, PortugalFulltext PDF
Docking and Virtual Screening (VS) are important tools for identifying novel drug candidates that possess antagonistic activity for several enzymes or protein receptors of medical or biological importance. Docking predicts and ranks the conformations of a ligand in a specific target and VS is used to explore large virtual databases containing millions of molecules. In this work, we report the optimization of a virtual screening protocol for the inhibition of β-lactamases. These are a class of enzymes that are associated with the development of resistance to β-lactam antibiotics. The results highlight the strengths and weaknesses of different scoring functions (AutoDock, Auto Dock Vina, GoldScore, ChemScore, CHEMPLP, and ASP) when dealing with this type of target. This allows us to perform large-scale VS campaigns in the search for novel inhibitors of β-lactamases. In general, the results have shown that the overall performance of the different scoring functions is comparable in discriminating between actives and decoys. However, the results can vary significantly with the type of target and ligand. ChemScore gives considerable better results, followed by Vina.
Vieira TF, Magalhaes RP, Sousa SF. Development of Consensus Scoring Functions for the Identification of Novel Beta-Lactamases Inhibitors by Virtual Screening. Ann Med Chem. 2019; 1(1): 1002.