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Letters in Drug Design & Discovery

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ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

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Research Article

Exploring the Biochemical Mechanisms of Fluoroquinolone Compounds against Tuberculosis by Utilizing Molecular Docking and Quantitative Structure-amino Acid Relationship

Author(s): Muneer Alam, Zeeshan Fatima* and Sisir Nandi*

Volume 21, Issue 9, 2024

Published on: 24 August, 2023

Page: [1521 - 1531] Pages: 11

DOI: 10.2174/1570180820666230619094409

Price: $65

Abstract

Background: Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb). It is one of the leading causes of death of 1.5 million people each year. TB can be treated by directly observed treatment short course (DOTS), but due to multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis, consequences can be devastating if the single DOTS dose is missed by the patient. MDR and XDR-TB require much more attention and time to control the infection. The longer period of tuberculosis treatment has side effects and it is expensive.

Objectives: This alarming condition demands the development of novel processes to diagnose the disease in its early stage as well as to produce more promising antimicrobial chemotherapeutics. The current study aimed to explore molecular mechanisms involving docking simulation-based quantitative structureamino acid relationship (QSAAR) in order to have a better understanding of the interactions between the fluoroquinolones and Mtb DNA gyrase.

Methods: In this study, 24 fluoroquinolone (FQ) compounds present in the literature were selected and docked against the Mtb DNA gyrase. Further, the relationship between the minimum inhibitory concentration of the compounds and interacting amino acids was assessed using QSAAR.

Results: The study has established a novel method of formulating a quantitative structure-amino acid relationship. A significant correlation (R-value=0.829) between biological activity and the docked amino acid residues responsible for producing anti-tubercular activities has been obtained.

Conclusion: The predicted residues captured in the developed model have been explored to report the Mtb virulence.

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