Pharmacoinformatics-based identification of anti-bacterial catalase-peroxidase enzyme inhibitors

Abstract

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb). In the present age, due to the rapid increase in antibiotic resistance worldwide, TB has become a major threat to human life. Regardless of significant efforts have been inclined to improve the healthcare systems for improving diagnosis, treatment, and anticipatory measures controlling TB is challenging. To date, there are no such therapeutic chemical agents available to fight or control the bacterial drug-resistance. The catalase-peroxidase enzyme (katG) which encoded by the katG gene of Mtb is most frequently getting mutated and hence promotes Isoniazid resistance by diminishing the normal activity of katG enzyme. In the current study, an effort has been intended to find novel and therapeutically active antibacterial chemical compounds through pharmacoinformatics methodologies. Initially, the five mutant katG were generated by making mutation of Ser315 by Thr, Ile, Arg, Asn, and Gly followed by structural optimizations. About eight thousand small molecules were collected from the Asinex antibacterial library. All molecules were docked to active site of five mutant katG and wild type katG. To narrow down the chemical space several criteria were imposed including, screening for highest binding affinity towards katG proteins, compounds satisfying various criterion of drug-likeliness properties like Lipinski's rule of five (RO5), Veber's rule, absorption, distribution, metabolism, and excretion (ADME) profile, and synthetic accessibility. Finally, five molecules were found to be important antibacterial katG inhibitors. All the analyzed parameters suggested that selected molecules are promising in nature. Binding interactions analysis revealed that proposed molecules are efficient enough to form a number of strong binding interactions with katG proteins. Dynamic behavior of the proposed molecules with katG protein was evaluated through 100 ns molecular dynamics (MD) simulation study. Parameters calculated from the MD simulation trajectories adjudged that all molecules can form stable complexes with katG. High binding free energy of all proposed molecules definitely suggested strong affection towards the katG. Hence, it can be concluded that proposed molecules might be used as antibacterial chemical component subjected to experimental validation.

Keywords: Binding energy; Catalase-peroxidase enzyme; Molecular docking; Molecular dynamics; Pharmacoinformatics; Virtual screening.