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Computer-aided identification of candidate molecules for tuberculosis drugs
https://doi.org/10.29235/1818-9857-2026-03-78-83
Abstract
Structure-based virtual screening of the library of bioactive compounds was used to identify novel small-molecule compounds that can inhibit the catalytic activity of Mycobacterium tuberculosis (Mtb) enoyl acyl carrier protein reductase (InhA), one of the key enzymes involved in the biosynthesis of mycolic acids of the Mtb cell wall. To do this, we employed an integrated computational approach to drug repurposing which included high-throughput docking of the InhA enzyme with small-molecule compounds from the library of bioactive molecules containing the FDA-approved drugs and investigational drug candidates, molecular dynamics simulations of the ligand/InhA-NAD+ complexes, binding free energy calculations, post-modeling analysis followed by selection of the most promising drug candidates and experimental determination of their minimum inhibitory concentration MIC90. As a result, a lead compound which showed the MIC90 value of 62.5 µM against the vaccine strain Mycobacterium bovis and Mtb was found, giving hope that this compound forms a promising scaffold for the development of novel antitubercular molecules of clinical significance with activity against an important target of Mtb.
About the Authors
A. Gonchar
Объединенный институт проблем информатики НАН Беларуси
Belarus
Belarus
Anna Gonchar
K. Furs
Объединенный институт проблем информатики НАН Беларуси
Belarus
Belarus
Konstantin Furs
A. Tuzikov
Объединенный институт проблем информатики НАН Беларуси
Belarus
Belarus
Alexander Tuzikov
A. Andrianov
Институт биоорганической химии НАН Беларуси
Belarus
Belarus
Alexander Andrianov
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Review
For citations:
Gonchar A., Furs K., Tuzikov A., Andrianov A. Computer-aided identification of candidate molecules for tuberculosis drugs. Science and Innovations. 2026;(3):78-83. (In Russ.) https://doi.org/10.29235/1818-9857-2026-03-78-83
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