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.
Authors
- Radul R Dev
- J. Abhithaj
- C. V. Umesh
- T. Amritha
- Rajesh Raju
- B. Angitha
Institutions
- Yenepoya University (IN)
- Chi Mei Medical Center (TW)
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
- Field-Weighted Citation Impact
- 0.00