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Comput Biol Chem . Identification of novel influenza virus H3N2 nucleoprotein inhibitors using most promising epicatechin derivatives

tetano

Editor, Senior Moderator
Comput Biol Chem


. 2024 Nov 27:115:108293.
doi: 10.1016/j.compbiolchem.2024.108293. Online ahead of print. Identification of novel influenza virus H3N2 nucleoprotein inhibitors using most promising epicatechin derivatives

Tajul Islam Mamun[SUP] 1 [/SUP], Sharifa Sultana[SUP] 2 [/SUP], Farjana Islam Aovi[SUP] 2 [/SUP], Neeraj Kumar[SUP] 3 [/SUP], Dharmarpu Vijay[SUP] 4 [/SUP], Umberto Laino Fulco[SUP] 5 [/SUP], Al-Anood M Al-Dies[SUP] 6 [/SUP], Hesham M Hassan[SUP] 7 [/SUP], Ahmed Al-Emam[SUP] 8 [/SUP], Jonas Ivan Nobre Oliveira[SUP] 9 [/SUP]



Affiliations
Abstract

Influenza A virus is a leading cause of acute respiratory tract infections, posing a significant global health threat. Current treatment options are limited and increasingly ineffective due to viral mutations. This study aimed to identify potential drug candidates targeting the nucleoprotein of the H3N2 subtype of Influenza A virus. We focused on epicatechin derivatives and employed a series of computational approaches, including ADMET profiling, drug-likeness evaluation, PASS predictions, molecular docking, molecular dynamics simulations, Principal Component Analysis (PCA), dynamic cross-correlation matrix (DCCM) analyses, and free energy landscape assessments. Molecular docking and dynamics simulations revealed strong and stable binding interactions between the derivatives and the target protein, with complexes 01 and 81 exhibiting the highest binding affinities. Additionally, ADMET profiling indicated favorable pharmacokinetic properties for these compounds, supporting their potential as effective antiviral agents. Compound 81 demonstrated exceptional quantum chemical descriptors, including a small HOMO-LUMO energy gap, high electronegativity, and significant softness, suggesting high chemical reactivity and strong electron-accepting capabilities. These properties enhance Compound 81's potential to interact effectively with the H3N2 nucleoprotein. Experimental validation is strongly recommended to advance these compounds toward the development of novel antiviral therapies to address the global threat of influenza.

Keywords: ADMET profiling; Epicatechin derivatives; H3N2; Influenza A virus; Molecular docking; Molecular dynamics simulation; PASS predictions.

 
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