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Abstract

Tuberculosis (TB) is caused by a bacterium called Mycobacterium tuberculosis, identified as a global health emergency by the world health organization. The development of drug-resistance stains due to spontaneous gene mutation has been a major boost to research in the pathogenicity and biochemistry of Mtb. To combat drug resistance to tuberculosis, new drugs and methodologies are emerging. Since, starting itself mycobacterium complex cell wall has been a choice for widely selected targets for anti-TB drugs. Peptidoglycan, arabinogalactan, and mycolic acid are the basic layers supporting cell growth. The current work investigates virtual screening for optimal small molecule inhibitors targeted against selected mycolic acid targets (β-keto acyl ACP synthase, enoyl acyl ACPreductase and Polyketide synthase 13). A small library of 485 compounds was designed and docked into a selected target core to identify the potential inhibitor. The designed compounds were subjected to docking studies using Glide (Schrodinger). InhA was the most suitable mycolic acid inhibitor target for the designed compounds. Further, the effectiveness of the study was evaluated by comparing the docking score of known molecules against selected targets with the designed library.