To date, influenza A virus cause a serious impact in human health. It has emerged as a worldwide pandemic threat in the 21st century where large human populations were affected annually. At present, Oseltamivir (Tamiflu) and Zanamivir (Relenza) have become important treatments for influenza infectious disease. Unfortunately, the resistance of influenza viruses to these drugs has been reported recently. So, it is important to discover new anti-influenza inhibitors to overcome the on-going and potential influenza outbreak. This project is about the discovery of the potential inhibitor for influenza infectious disease via ensemble-based virtual screening. As a receptor destroying enzyme, neuraminidase has been widely used as a drug target for drug discovery. Thus, this study was focused on Neuraminidase subtype-1. Variation of neuraminidase conformations from Protein Data Bank (PDB) and molecular dynamics (MD) simulation structures were used in this study. With the aid of computational resource, ensemble-based virtual screening was performed. Neuraminidase was screened against the National Cancer Institute (NCI) Database and the Natural Product Discovery System (NADI) Database to discover the potential compounds as the neuraminidase inhibitors. From docking results, 20 compounds from NCI Database were selected. For NADI Database, there were 40 compounds have been selected and they were clustered into 7 plants. All these compounds (NCI and NADI) were able to bind to all 13 ensemble structures. This has exhibited the probable anti-neuraminidase activity. These compounds were then subjected to inhibitory activity evaluation via MUNANA assay