Discovery of Potent LasR Inhibitor Using Pharmacophore Informatics Strategy

Abstract

Pseudomonas aeruginosa is a Gram-negative microorganism which is present commonly in soil and water. P. aeruginosa has potential to survive in harsh conditions and it is an opportunistic pathogen that cause fatal infections in patients which are immunocompromised. Due to the presence of drug-strain resistance in P. aeruginosa there is a high mortality rate among infected patients which is now a critical and lethal issue by causing 51,000 infections in the USA every year with mortality rate ranging from 18% to 61% worldwide. Multi-drug resistance (MDR) has inflated dramatically in past years and is now conceded as a major threat globally, so there is an eternal need to develop new strategies to overcome drug-strain resistance by P. aeruginosa. It causes nosocomial respiratory tract infections, urinary tract infections, dermatitis, chronic wounds, soft tissue infections and several systemic infections. Drug resistance is due to the formation of biofilms by LasR which regulates quorum sensing in P. aeruginosa and has been reported as a new therapeutic target for the designing of antibacterial agents. In this study we have done virtual screening and molecular docking is performed against LasR-LBD with pharmacophore hypothesis for the screening of 2373 FDA approved compounds attained from the DrugBank database to get the top screened hit results. Six inhibitors out of 2373 compounds were found to have binding affinities close to the reference inhibitors. The binding modes of these compounds to the binding site in LasR-LBD were predicted and used to identify the key interactions that contribute to the inhibition of LasR activity. 50 ns simulation of top hit compound has been done to determine the stability of their bonds with targeted LasR-LBD. From this study we have concluded that sulfamerazine had the highest binding affinity value and exhibited good binding interactions during MD simulation.