The avian influenza virus (subtype H5N1) is currently becoming the world's largest pandemic threat due to the high lethality, in birds and increasingly humans , and virulence of its endemic presence, its increasingly large host reservoir, and its significant ongoing mutations. The two surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA) of influenza A virus, play an important role in the interactions with cellular receptors containing terminal N-acetyleneuraminic acid (Neu5Ac, or NANA) moieties, aka, sialic acids (http://en.wikipedia.org/wiki/Sialic_acid). The approved anti-influenza drugs oseltamivir and zanamivir inhibit H5N1 activity by targeting the NA active site. However, research has shown that antigenic drift may result in viral resistance to the abundant presence of existing NA inhibitors through the retention of NeuAc

moieties by complex glycan near HA receptor binding site; and antigenic shift could give rise to new virulent subtypes of the flu virus. Thus, it is crucial to design novel HA- and NA-targeted inhibitors, which can be used in combination for optimal prophylaxis and treatment. Work has been ongoing to apply the Relaxed Complex (RC) scheme and Molecular Dynamics (MD) simulations on the two target proteins in the hope of capturing key protein dynamics information and accounting for receptor flexibility. Research is under way to take advantage of novel loop flexibilities and changing cavity shapeadjacent to NA active siteto discover novel NA inhibitors that may work in a way similar to the HIV integrase inhibitor, raltegravir, inspired by the RC/MD simulation procedures. Further investigation involves statistical cluster analysis for rational selection of representative HA/NA protein structure snapshots, which will be used in the virtual screening with diverse ligand libraries. Finally, the binding energies of the high scoring compounds will be re-evaluated and refined by Molecular Mechanics-Poisson Bolzmann Surface Area (MM-PBSA) approach for lead optimization. By leveraging the PRAGMA grid and high performance computing (HPC) resources, the implementation of many state-of-the-art computational techniques would be expected to greatly facilitate the drug discovery process and improve the accuracy in the search for novel avian influenza inhibitors, subsequently generate drug leads with potentials for further validation and development in biological assays and experiments.