A One Health Computational Framework for Identifying PA Endonuclease Inhibitors Against Contemporary H5N1 Avian...

Area of Science:

• Virology
• Computational Biology
• Drug Discovery

Background:

• Highly pathogenic avian influenza (HPAI) H5N1 clade 2.3.4.4b poses a global threat across multiple hosts.
• The influenza A polymerase acidic (PA) endonuclease is a conserved target for antiviral development.

Purpose of the Study:

• To develop a computational framework for identifying PA endonuclease inhibitors for H5N1.
• To evaluate candidate inhibitors within a One Health context, considering cross-host applicability.

Main Methods:

• Homology modeling of H5N1 PA sequences.
• Cross-host molecular docking against a ligand library.
• Molecular dynamics simulations and physicochemical filtering.

Main Results:

• Baloxavir and entecavir were identified as potential inhibitors.
• Entecavir showed favorable binding in poultry models, with stable dynamics (170 ns) and binding free energy (ΔG ≈ -85 kJ/mol).
• Physicochemical properties of entecavir were assessed for translational potential.

Conclusions:

• A computational framework integrating cross-host analysis and translational considerations was established.
• Entecavir is a candidate for further biochemical and virological evaluation against H5N1.
• This approach supports One Health strategies for H5N1 control.