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Exploration of novel anti-TB agents targeting the serine/threonine kinase enzyme (PknE) in Mycobacterium tuberculosis: an in silico study

Sep 2026 · Scientific Reports · 0 citations

TL;DR

A structure-based in silico workflow comprising virtual screening of 2,202 FDA-approved compounds, molecular docking, molecular docking, 300 ns molecular dynamics simulation, and in silico toxicity profiling provide a strong computational basis for repurposing these agents as adjunct anti-TB therapies, pending experimental validation.

Abstract

Mycobacterium tuberculosis (MTB) remains a deadly infectious agent and a global health challenge, particularly due to the emergence of multidrug-resistant strains. Mycobacterial serine/threonine protein kinase E (PknE) is vital for mycobacterial survival under nitric oxide stress by altering Toll-like receptor expression, suppressing apoptosis, increasing inflammation, and modulating costimulatory molecules. This study employed a structure-based in silico workflow comprising virtual screening of 2,202 FDA-approved compounds, molecular docking, 300 ns molecular dynamics (MD) simulation molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) binding free energy calculations, principal component analysis (PCA), free energy landscape (FEL) analysis, and in silico toxicity profiling, to identify candidate PknE inhibitors. Molecular docking identified netilmicin, dirithromycin, acarbose, and ertapenem as top candidates, with docking scores of − 13.13 to − 15.86 kcal/mol. MD simulations confirmed complex stability with RMSD values near 1 nm, while MM/PBSA analysis revealed favourable binding free energies: netilmicin (− 1.47 ± 0.18), ertapenem (− 11.70 ± 1.22), dirithromycin (− 17.80 ± 0.13), and acarbose (− 18.90 ± 0.06 kcal/mol). PCA-based FEL analysis confirmed thermodynamic stability across all complexes, with DTM–PknE exhibiting the lowest minimum Gibbs free energy (15.7 kJ/mol). In silico toxicity profiling demonstrated acceptable safety profiles for all leads. These findings provide a strong computational basis for repurposing these agents as adjunct anti-TB therapies, pending experimental validation.

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