Understanding the stability and dynamics of influenza a H5N1 polymerase PB2 CAP-Binding domain in complex with natural compounds for antiviral drug discovery.

Arch Biochem Biophys

Molecular Biology Research Lab, Department of Zoology, Deshbandhu College, University of Delhi, Delhi, 110019, India; Delhi School of Public Health, Institute of Eminence, University of Delhi, Delhi, 110007, India.

Published: November 2024

Influenza A virus, particularly the H5N1 strain, poses a significant threat to public health due to its ability to cause severe respiratory illness and its high mortality rate. Traditional antiviral drugs targeting influenza A virus have faced challenges such as drug resistance and limited efficacy. Therefore, new antiviral compounds are needed to be discovered and developed. This study concentrated on examining the stability and behavior of the H5N1 polymerase PB2 CAP-binding domain when interacting with natural compounds, aiming to identify potential candidates for antiviral drug discovery. Through the virtual screening process, four lead compounds, ZINC000096095464, ZINC000044404209, ZINC000001562130, and ZINC000059779788, were selected, and these compounds showed binding energies -9.6, -9.4, -9.3, and -9.2 kcal/mol, respectively. When complexed with PB2, the ligand showed acceptable binding stability due to significant bond formation. However, during the 200ns MD simulation analysis, three (ZINC000096095464, ZINC000044404209, and ZINC000059779788) showed significant stability, which was proven by the trajectory analysis. The Rg-RMSD-based FEL plot showed significant structural stability due to stable conformers. The free-binding energy calculation also validates the stability of these complexes. This study offers valuable insights into the stability and dynamics of the H5N1 polymerase PB2 CAP-binding domain in complexes with natural compounds. These findings highlight the potential of these natural compounds as antiviral agents against the H5N1 influenza virus. Furthermore, this research contributes to the broader field of influenza virus treatment by demonstrating the effectiveness of computational methods in predicting and evaluating the stability and dynamics of potential drug candidates.

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http://dx.doi.org/10.1016/j.abb.2024.110148DOI Listing

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