The emergence of antibiotic resistance is one of the major global threats in healthcare. Metallo-β-Lactamases (MBL) are a class of enzymes in bacteria that cleave β-lactam antibiotics and confer resistance. MBLs are further divided into subclasses B1, B2 and B3. Of these, subclasses B1-MBLs (including NDM-1, VIM-2 and IMP-1) constitute the clinically prevalent lactamases conferring resistance. To date, no effective drugs are available clinically against MBLs. In this work, we aim to identify potent inhibitors for the B1 subclass of MBL from available marine metabolites in Comprehensive Marine Natural Product database through integrated in silico approaches. We have used two methods, namely, the high-throughput strategy and the pharmacophore-based strategy to identify potential inhibitors from marine metabolites. High-throughput virtual screening identified N-methyl mycosporine-Ser, which had the highest binding affinity to NDM-1. The pharmacophore-based approach based on co-crystallized ligands identified makaluvic acid and didymellamide with higher binding affinity across B1-MBLs. Taking into account of the advantage of a pharmacophore model-based approach with higher binding affinity, we conclude that both makaluvic acid and didymellamide show potential broad-spectrum effects by binding to all three B1-MBL receptors. The study also indicates the need to take multiple in silico approaches to screen and identify novel inhibitors. Together, our study reveals promising inhibitors that can be identified from marine systems.Communicated by Ramaswamy H. Sarma.
Keywords: high throughput virtual screening; inhibitors; marine metabolites; natural products; pharmacophore-based screening; β-lactamases.