The combined study based on the computational and experimental techniques helped in identifying novel inhibitors that bind to SAM binding site.21, 22 and 23 The present work is to identify the inhibitor lead molecules for Flavivirus NS5 MTase using computational approach. The

dengue MTase has separate binding sites for RTP and SAM. E-pharmacophore studies were performed using both the sites for studying the substrate and inhibitor binding in the active site of MTase. Finally, these pharmacophores were used as queries for virtual screening using compounds from the Asinex database and induced fit docking (IFD) was carried out for the short-listed compounds. The identification of pharmacophore features

was carried out by aligning all the compounds together in a 3D Cartesian space. The earlier studies focused on the structure-based ZD1839 ic50 virtual screening and ligand-based pharmacophore models, keeping the active site of the protein rigid.18, 19 and 20 BKM120 order The structure-based pharmacophore was used to derive pharmacophore features from the inhibitors or substrates that bind at different sites, separately. The X-ray crystal structures of the dengue MTase complex, MTase–SAM complex (PDB id: 3P97), MTase–SAH complex (PDB id: 1R6A), MTase–RTP complex (PDB id: 1R6A) specific to the Flavivirus were retrieved from Protein Data Bank. 25 During protein preparation, water molecules were removed, hydrogen atoms were added, bond orders were assigned and orientation of hydroxyl groups were optimized. Energy minimization was carried out using OPLS2005 force field to converge RMSD of 0.30Å. The receptor grid was generated around the centroid of the ligand contained by enzyme file and the ligands with cut off size of 10 Å were allowed to dock. The ligands were docked with the active site using the ‘Extra Precision’ Glide algorithm. 26 and 27 Glide includes ligand–protein interaction energies, hydrophobic interactions,

hydrogen bonds, internal energy, π–π stacking interactions and root mean square deviation (RMSD) and desolvation. Finally, best pose of the particular ligand was selected based on the Glide Mannose-binding protein-associated serine protease score. Energy-optimized pharmacophores (e-pharmacophores)28 were evaluated through mapping the energetic terms from the Glide XP scoring function onto atom center. Pharmacophore sites were automatically generated from the protein–ligand docked complex with Phase (Phase, v.3.0, Schrodinger, LLC) using the default set of six chemical features, hydrogen bond acceptor (A), hydrogen bond donor (D), hydrophobic (H), negative ionizable (N), positive ionizable (P), and aromatic ring (R). Glide XP descriptors include terms for hydrophobic enclosure, hydrophobically packed correlated hydrogen bonds, electrostatic rewards, π–π stacking, π cation and other interactions.