Computational design and evaluation of hydrantoin derivatives as potential anti-tubercular agents: Insight from ADMET, molecular docking, DFT, and molecular dynamic simulations

Background The global burden of tuberculosis and the rise of drug-resistant Mycobacterium tuberculosis strains continue to challenge effective disease control, underscoring the need for novel therapeutic agents with improved efficacy and safety profiles. Objective This study aimed to design and computationally evaluate hydantoin-based derivatives as potential InhA inhibitors for anti-tubercular drug development. Methods A series of sixty-three compounds were subjected to molecular docking–based virtual screening to identify promising InhA inhibitors. Molecular dynamics simulations were performed to characterize ligand-protein interactions and stability. The candidates were assessed for drug-likeness and pharmacokinetic properties, while density functional theory (DFT) calculations were conducted to examine their electronic reactivity. Results Six compounds (3, 23, 25, 28, 45, and 53) exhibited higher binding affinities, with MolDock scores from −137.26 to −151.66 kcal/mol and re-rank scores between −99.26 and −112.32 kcal/mol, outperforming isoniazid (-48.59 and −45.69 kcal/mol). Compound 53 showed stable binding over a 300 ns simulation and served as a template for new derivative design. This yielded six analogues with improved affinities (MolDock: −156.53 to −170.37 kcal/mol; re-rank: −120.18 to −134.43 kcal/mol). Pharmacological profiling confirmed favourable drug-likeness and ADMET properties with minimal Lipinski violations. DFT analysis revealed strong electronic reactivity, particularly for compounds 23 and 53b. Conclusion These results highlight compounds 23 and 53b as promising scaffolds for InhA inhibition and suggest their potential as lead structures for future anti-tubercular drug discovery.