Discovering Influenza Virus Neuraminidase Inhibitors via Computational and Experimental Studies

Influenza A and B viruses spread out worldwide, causing
several
global concerns. Discovering neuraminidase inhibitors to prevent influenza
A and B viruses is thus of great interest. In this work, a machine
learning model was trained and tested to evaluate the ligand-binding
affinity to neuraminidase. The model was then used to predict the
binding affinity of compounds from the CHEMBL database, which is a
manually curated database of bioactive molecules with drug-like properties.
The physical insights into the binding process of ligands to neuraminidase
were clarified via molecular docking and molecular dynamics simulations.
Experimental investigation on enzymatic activity validated our computational
results and suggested that 2 compounds were potential inhibitors of
neuraminidase of the influenza A and B viruses.