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.