Virtual screening, molecular docking, and molecular dynamics simulation reveal new insights into RNA polymerase inhibition for anti-tuberculosis drug discovery.

Purpose: This study aims to identify potential RNA polymerase (RNAP) inhibitors using a comprehensive computational approach, addressing the challenges in drug discovery related to stability, affinity, and accurate binding predictions.

Patients and methods: The research workflow involved virtual screening to narrow down candidate compounds, molecular docking to predict optimal binding poses, molecular dynamics (MD) simulations to evaluate interaction stability over time, and MM-PBSA analysis to calculate binding energies. These steps ensured that only compounds with strong and stable binding profiles were selected for further evaluation.

Results: The selected compounds, ZINC001286671821, ZINC000253654686, and ZINC000252693842, demonstrated varying degrees of stability and affinity. MM-PBSA analysis revealed that ZINC000252693842 had the most favourable binding energy at -106.097 ± 24.664 kJ/mol, followed by ZINC001286671821 at -89.201 ± 22.647 kJ/mol, and ZINC000253654686 at -43.832 ± 23.748 kJ/mol. Van der Waals forces were the main contributors to stability, with values of -221.032 ± 27.721 kJ/mol, -187.136 ± 23.796 kJ/mol, and -157.232 ± 19.676 kJ/mol, respectively. These findings confirm the strong binding potential of ZINC000252693842 as an RNAP inhibitor.

Conclusion: This study highlights the effectiveness of combining virtual screening, molecular docking, MD simulations, and MM-PBSA analysis in identifying promising RNAP inhibitors. The results establish a strong foundation for further experimental validation, advancing the development of effective therapeutic agents targeting RNA polymerase.