Evaluation of Scoring Functions for Large Scale Application of Virtual Screening in the Identification of Novel Beta-Lactamase Inhibitors

Virtual Screening is a powerful methodology that can be used to explore large virtual databases containing millions of molecules to identify novel drug candidates with promising inhibitory activity against enzymes or receptors of medical, biological or industrial importance. Here, we report the optimization of a virtual screening protocol using atomic-level protein docking for the inhibition of Beta-lactamase, an enzyme highly associated with the development multi-drug resistance in bacteria. The results highlight the strengths and weaknesses of different virtual screening methods when dealing with this type of targets, opening the way to large-scale campaigns in the search for novel inhibitors of Beta-lactamases.