In-silico design and evaluation of quinoline-dione derivatives as Mycobacterium tuberculosis DprE1 inhibitors

Background Because of increase in drug resistance and a scarcity of effective treatment options, tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a significant global health threat. In the realm of TB drug discovery, the enzyme decaprenylphosphoryl-β-D-ribose oxidase (DprE1) serves as a validated and essential therapeutic target. This research primarily focusses on the in-silico development of novel 3-Methyl-3 H-naphtho[1,2,3-de]quinoline-2,7-dione derivatives as potential DprE1 inhibitors. Methodology A structure-based drug design strategy was employed to identify robust candidates, incorporating pharmacokinetic analyses, molecular docking, and molecular dynamics (MD) simulations. The molecular docking study revealed strong binding interactions of the proposed derivatives within the DprE1 active site, highlighting essential hydrogen bonds and hydrophobic interactions that facilitate target inhibition. Results MD simulations (250 ns) were performed to assess the stability, flexibility, and conformational dynamics of protein-ligand complexes, thereby validating docking results. Stable binding was indicated by critical metrics such as root mean square deviation (RMSD) and root mean square fluctuation (RMSF). Binding free energy calculations (MM/PBSA) quantified the favourable thermodynamics of ligand binding. Additionally, the drug-like properties of the top candidates were confirmed through ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) predictions, ensuring favourable pharmacokinetic and safety profiles. Several optimised compounds of 3-Methyl-3 H-naphtho[1,2,3-de]quinoline-2,7-dione with significant potential as tuberculosis inhibitors were identified through these in silico methodologies. Conclusion These compounds have been predicted to bind strongly to DprE1, demonstrating excellent specificity and antitubercular action. and offer a foundation for subsequent experimental validation.