VIRTUAL SCREENING OF MEDICINAL PLANT COMPOUNDS AGAINST DevR (A0R2V2) OF Mycobacterium tuberculosis USING MOLECULAR DOCKING STUDIES

Abstract

The DevR response regulator in Mycobacterium tuberculosis is believed to play a key role in bacterial dormancy adaptation during hypoxia and also shares a homologous genetic system with Mycobacterium smegmatis. Thus DevR is proposed to be an attractive target for the development of inhibitors against tuberculosis. Currently available first line anti-tuberculosis drugs have been caused several side effects in the body as well as resistance development by mycobacterium against these drugs, necessitates the considerable need for finding new drugs. Therefore, we propose a structure based computational method to find a new potential inhibitor for DevR protein. Natural sources pro- vide numerous examples of interesting secondary metabolites with antimycobacterial activity, indicating that natural products could be a re- warding field for the discovery of new anti-TB leads. The present study is to deduce the structure of the DevR (UniprotID: A0R2V2) protein using prime module (Schrodinger) and to validate the same with Ramachandran plot. The proposed model structure is further explored for insilico docking studies with natural inhibitors obtained from published literatures which describe the effectiveness of natural anti-tuberculosis compounds. 143natural compounds were computationally analyzed using glide module for their bioactivity against DevR protein using virtual screening approach. The best ligand that exhibited high docking score with DevR was finally reported. Further, structure optimization and in vitro validation of above inhibitors will prove its efficacy as a better candidate in the drug designing pipeline. Keywords-