An integrated computational approach towards novel drugs discovery against polyketide synthase 13 thioesterase domain of Mycobacterium tuberculosis

Abstract

Abstract The acquired drug resistance by Mycobacterium tuberculosis (M. tuberculosis) to antibiotics urges the need for developing novel anti-M. tuberculosis drugs that possess novel mechanism of action. Since traditional drug discovery is a labor-intensive and costly process, computer aided drug design is highly appreciated tool as it speeds up and lower the cost of drug development process. Herein, Asinex antibacterial compounds were virtually screened against thioesterase domain of Polyketide synthase 13, a unique enzyme that forms α-alkyl β-ketoesters as a direct precursor of mycolic acids which are essential components of the lipid-rich cell wall of M. tuberculosis. The study identified three drug-like compounds as the most promising leads; BBB_26582140, BBD_30878599 and BBC_29956160 with binding energy value of − 11.25 kcal/mol, − 9.87 kcal/mol and − 9.33 kcal/mol, respectively. The control molecule binding energy score is -9.25 kcal/mol. Also, the docked complexes were dynamically stable with maximum root mean square deviation (RMSD) value of 3 Å. Similarly, the MM-GB\PBSA method revealed highly stable complexes with mean energy values < − 75 kcal/mol for all three systems. The net binding energy scores are validated by WaterSwap and entropy energy analysis. Furthermore, The in silico druglike and pharmacokinetic investigation revealed that the compounds could be suitable candidates for additional experimentations. In summary, the study findings are significant, and the compounds may be used in experimental validation pipeline to develop potential drugs against drug-resistant tuberculosis.