Pharmacophore insights and molecular docking of ciprofloxacin analogues against 2XE1: strategies for reduced antibiotic resistance

Sanjana Katlaria; Ashish Singh Chauhan; Krishna Kumar; Mohit Kumar; Bhumika Chauhan; Vikash Jakhmola

doi:10.69857/joapr.v12i6.660

Authors

Sanjana Katlaria Department of Pharmaceutics, Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun-248007, Uttarakhand, India
Ashish Singh Chauhan Department of Pharmaceutics, Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun-248007, Uttarakhand, India
Krishna Kumar Department of Pharmaceutical Chemistry, Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun-248007, Uttarakhand, India
Mohit Kumar Department of Pharmaceutical Chemistry, Sai Institute of Medical Sciences, Jaspur, U.S. Nagar-244712, Uttarakhand, India
Bhumika Chauhan ITS College of Pharmacy, Ghaziabad-201206, Uttar Pradesh, India
Vikash Jakhmola Department of Pharmaceutical Chemistry, Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun-248007, Uttarakhand, India

DOI:

https://doi.org/10.69857/joapr.v12i6.660

Keywords:

Antibiotic Resistance, Ciprofloxacin, Docking Simulations, Arguslab 4.0, Computational Antibiotic Discovery

Abstract

Background: Antibiotic resistance is a silent pandemic disease that is growing and causing a global threat. Existing antibiotics are less effective against infectious diseases, so we must discover more potent and effective drugs. The latest report from the World Health Organization (WHO) underscores the global nature of the situation, revealing that high levels of antibiotic resistance in bacteria worldwide lead to life-threatening bloodstream infections and resistance to treatment. Methods: This study focuses on the Molecular Docking and Pharmacophore Modeling of Ciprofloxacin and its analogs to explore ligand-protein interactions and identify potent drugs against AMR. Twenty ciprofloxacin analogs, designed using ChemDraw Pro12.0, were docked with the 2XE1 protein. Molecular docking assessed the binding affinity, with Arguslab 4.0 scoring the lowest docking scores to indicate strong interactions and biological activity. Pharmacophore modeling identified essential molecular features like HBA, HBD, and AI for optimal biological activity. Results: The computational screening identified several compounds with improved binding properties, showing greater affinity towards ALA129, TYR149, and PHE88 amino acids, essential for biological activity. Conclusion: The study identifies the best analog of ciprofloxacin, which can effectively combat antibiotic resistance. Compound 13 showed promising docking scores and relevant pharmacophoric features, outperforming the parent ciprofloxacin in binding affinity, suggesting it could be a potent drug candidate against AMR.

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