Novel Anti-Microbial Peptides Design and Screening Against the KatG Using Molecular Docking and MD Simulation.

Authors

Kanchan Mehta, Shama Mujawar, Gaurav Kumar, Ashish Vyas

Published in

Probiotics and antimicrobial proteins. Jun 19, 2026. Epub Jun 19, 2026.

Abstract

Tuberculosis (TB) continues to be a significant worldwide health issue, with the rise of drug-resistant forms presenting substantial obstacles to successful treatment. The Mycobacterium tuberculosis (Mtb) enzyme catalase-peroxidase G (KatG) is a crucial molecular determinant of resistance, as it is necessary for the activation of isoniazid and for safeguarding the bacteria against oxidative stress. Mutations in KatG are a key mechanism of isoniazid resistance, contributing to the development of multidrug-resistant tuberculosis, hence establishing KatG as a crucial protein target for novel therapeutic approaches. This study focused on KatG to identify novel antimicrobial peptides (AMP) which were designed using rational changes of the host-defence peptide LL-37 to improve their efficacy against M. tuberculosis. A library of 15 antimicrobial peptides was designed using LL-37 modifications and categorized into three classes: Class I, Class II, and Class III. Peptide structures were predicted and docked against KatG resulting in top antimicrobial peptides. Molecular docking identified three top peptides P3 (-235.28 binding score), A5ζ (-229.42), and A4η (-233.81), with strong binding affinity with KatG active site residues. Further, molecular dynamic (MD) simulation was performed for 100 ns on these top three protein-peptide complexes. MD simulation showed distinct stability profiles majorly with P3 showing exceptional conformational stability. Additionally, safety assessment verified no-toxic, non-allergenic, favorable physicochemical and ADME properties. The computationally designed antimicrobial peptides (P3, A5ζ, and A4η) demonstrated strong binding affinity toward KatG. These interactions suggest their potential to interfere with key mycobacterial enzymatic functions and may contribute to strategies aimed at addressing existing drug resistance mechanisms.

PMID:
42319666
Bibliographic data and abstract were imported from PubMed on 19 Jun 2026.

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