Targeting KasA: isosakuranetin derivatives as promising scaffolds for novel anti-tuberculosis agents against drug-resistant Mycobacterium tuberculosis

Introduction: , a medicinal plant with reported antimicrobial and antituberculosis activity, is a rich source of bioactive flavonoids, including Isosakuranetin, which shows moderate anti-tuberculosis activity. Modifications in pharmacophores-such as functional groups, structural features, bond angles, and bond distances-can enhance the activity of these phytochemicals and improve their potential as drug leads. Methodology: A structure-based computational workflow was employed, including molecular docking, MM-GBSA binding energy calculations, ADMET evaluation, and 250 ns molecular dynamics simulations to investigate the binding affinity, stability, and pharmacokinetic profiles of Isosakuranetin and its derivatives against KasA. Results: The analysis revealed differential binding affinities and dynamic stabilities of Isosakuranetin derivatives. Isn_96 exhibited the strongest binding affinity (-7.921 kcal/mol), with favorable electrostatic and hydrophobic interactions involving residues HIS311, HIS345, and ASP273. Post-MDS MM-GBSA analysis confirmed its enhanced stability, displaying the highest binding free energy (-56.20 ± 6.90 kcal/mol). Pharmacokinetic predictions also indicated acceptable absorption and safety profiles. Discussion: These findings suggest that Isosakuranetin derivatives, particularly Isn_96, are promising scaffolds for the design of novel KasA inhibitors. Their strong binding affinity, dynamic stability, and favorable ADMET properties highlight potential efficacy against drug-resistant M. tuberculosis. The results emphasize the potential of plant-derived flavonoids as lead compounds and underscore the value of structure-based computational approaches in guiding anti-tuberculosis drug development.

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Publication Details

Journal
Frontiers in Bioinformatics
Published
2026-03-31
DOI
https://doi.org/10.3389/fbinf.2026.1777858
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Targeting KasA: isosakuranetin derivatives as promising scaffolds for novel anti-tuberculosis agents against drug-resistant Mycobacterium tuberculosis

Radul R Dev, J. Abhithaj, C. V. Umesh, T. Amritha et al.
Frontiers in Bioinformatics
Computational Drug Discovery Methods
article

Targeting KasA: isosakuranetin derivatives as promising scaffolds for novel anti-tuberculosis agents against drug-resistant Mycobacterium tuberculosis

Radul R Dev, J. Abhithaj, C. V. Umesh, T. Amritha, Rajesh Raju, B. Angitha
article en

Abstract

Introduction: , a medicinal plant with reported antimicrobial and antituberculosis activity, is a rich source of bioactive flavonoids, including Isosakuranetin, which shows moderate anti-tuberculosis activity. Modifications in pharmacophores-such as functional groups, structural features, bond angles, and bond distances-can enhance the activity of these phytochemicals and improve their potential as drug leads. Methodology: A structure-based computational workflow was employed, including molecular docking, MM-GBSA binding energy calculations, ADMET evaluation, and 250 ns molecular dynamics simulations to investigate the binding affinity, stability, and pharmacokinetic profiles of Isosakuranetin and its derivatives against KasA. Results: The analysis revealed differential binding affinities and dynamic stabilities of Isosakuranetin derivatives. Isn_96 exhibited the strongest binding affinity (-7.921 kcal/mol), with favorable electrostatic and hydrophobic interactions involving residues HIS311, HIS345, and ASP273. Post-MDS MM-GBSA analysis confirmed its enhanced stability, displaying the highest binding free energy (-56.20 ± 6.90 kcal/mol). Pharmacokinetic predictions also indicated acceptable absorption and safety profiles. Discussion: These findings suggest that Isosakuranetin derivatives, particularly Isn_96, are promising scaffolds for the design of novel KasA inhibitors. Their strong binding affinity, dynamic stability, and favorable ADMET properties highlight potential efficacy against drug-resistant M. tuberculosis. The results emphasize the potential of plant-derived flavonoids as lead compounds and underscore the value of structure-based computational approaches in guiding anti-tuberculosis drug development.

Frontiers in BioinformaticsVol. 6
Yenepoya University (IN), Chi Mei Medical Center (TW)
Good health and well-being
Openalex Percentile: Top 27%
Computational Drug Discovery Methods
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