Virtual Screening of Novel Benzothiozinone Derivatives to Predict Potential Inhibitors of Mycobacterium Tuberculosis Kinases 2D-QSAR, Molecular Docking, MM-PBSA Dynamics Simulations, and ADMET Properties.

ABSTRACT: Mycobacterium tuberculosis, the infectious agent behind tuberculosis (TB), underscores the significance of targeting enzymes such as arabinosyltransferases in drug development efforts. Benzothiozinone derivatives, which have been assessed for their effectiveness against TB, present a promising avenue for treatment. Utilizing a high virtual screening quantitative structure-activity relationship (QSAR-VS), a set of forty Benzothiozinone (C1-C40) compounds were investigated to build a robust model with satisfactory performance metrics (R² = 0.82, R²_adj = 0.78, N_test = 10, R²_test = 0.70). This model enabled the creation of databases containing new derivatives for screening drug-like prop

SUBMITTER: Guendouzi A 

PROVIDER: S-EPMC12155315 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature