Key result
In silico modeling, including 2D- and 3D-QSAR, pharmacophore mapping, and molecular dynamics, identified key structural requirements for aryl benzoyl hydrazide derivatives to inhibit the RdRp enzyme of the H5N1 influenza virus.
Why the study?
RNA-dependent RNA polymerase is a potential therapeutic target for influenza, but its inhibitors require further investigation to design novel antiviral agents.
In silico modeling identifies structural requirements for aryl benzoyl hydrazide derivatives to inhibit the RdRp enzyme of H5N1 influenza virus, providing guidelines for future antiviral drug design.
May inform RdRp inhibitor design for influenza; leaves open clinical translation pending validation studies.
RNA-dependent RNA polymerase (RdRp) is a potential therapeutic target for the discovery of novel antiviral agents for the treatment of life-threatening infections caused by newly emerged strains of the influenza virus. Being one of the most conserved enzymes among RNA viruses, RdRp and its inhibitors require further investigations to design novel antiviral agents. In this work, we systematically investigated the structural requirements for antiviral properties of some recently reported aryl benzoyl hydrazide derivatives through a range of in silico tools such as 2D-quantitative structure-activity relationship (2D-QSAR), 3D-QSAR, structure-based pharmacophore modeling, molecular docking and molecular dynamics simulations. The 2D-QSAR models developed in the current work achieved high statistical reliability and simultaneously afforded in-depth mechanistic interpretability towards structural requirements. The structure-based pharmacophore model developed with the docked conformation of one of the most potent compounds with the RdRp protein of H5N1 influenza strain was utilized for developing a 3D-QSAR model with satisfactory statistical quality validating both the docking and the pharmacophore modeling methodologies performed in this work. However, it is the atom-based alignment of the compounds that afforded the most statistically reliable 3D-QSAR model, the results of which provided mechanistic interpretations consistent with the 2D-QSAR results. Additionally, molecular dynamics simulations performed with the apoprotein as well as the docked complex of RdRp revealed the dynamic stability of the ligand at the proposed binding site of the receptor. At the same time, it also supported the mechanistic interpretations drawn from 2D-, 3D-QSAR and pharmacophore modeling. The present study, performed mostly with open-source tools and webservers, returns important guidelines for research aimed at the future design and development of novel anti-viral agents against various RNA viruses like influenza virus, human immunodeficiency virus-1, hepatitis C virus, corona virus, and so forth.
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Ghosh et al. (2022) studied H5N1 influenza virus (n=30). Aryl benzoyl hydrazide derivatives was evaluated on In silico binding affinity and QSAR modeling (pEC50). In silico modeling, including 2D- and 3D-QSAR, pharmacophore mapping, and molecular dynamics, identified key structural requirements for aryl benzoyl hydrazide derivatives to inhibit the RdRp enzyme of the H5N1 influenza virus.
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