An In-Silico Investigation of Phytochemicals as Antiviral Agents Against Dengue Fever

Powers, Chelsea N.; Setzer, William N.

Protein-ligand docking studies were carried out based on the crystal structures (PDB 3U1J [22] , 4M9K, 4M9M, and 4M9T [23] ) and the NMR structures (PDB 2M9P and 2M9Q [24] ) of dengue virus NS3 protease; crystal structures of dengue virus NS3 helicase (PDB 2BHR, 2BMF [25] , 2JLQ, 2JLR, 2JLS, 2JLU, 2JLV, 2JLX [26] , and 2WHX [27] ); crystal structures of dengue virus NS5 RNA methyltransferase (PDB 3P8Z [28] , 4CTJ, 4CTK, and 4R8S [21] ); crystal structures of dengue virus NS5 RNAdependent RNA polymerase (2J7U, 2J7W [29] , 3VWS, and 4HHJ [30] ); and crystal structures of dengue virus envelope protein (PDB 1OAN and 1OKE [31] ). In order to examine selectivity for DEVN MTase, human RNA methyltransferase proteins (PDB 3BGV [32] , 3EPP [33] , and 4N49 [34] ) were also used for docking. Similarly, in order to examine selectivity for DENV protease over mammalian serine proteases, we have carried out docking of the phytochemical ligands with crystal structures of rat trypsin (PDB 1BRB [35] ), bovine trypsin (PDB 2ZDK [36] and 4MTB [37] ), and porcine elastase (PDB 7EST [38] ). Prior to docking, all solvent molecules and the co-crystallized ligands were removed from the structures. Molecular docking calculations for all compounds with each of the proteins were undertaken using Molegro Virtual Docker (version 6.0, Molegro ApS, Aarhus, Denmark) [39] , with a sphere (15 Ã… radius) large enough to accommodate the cavity centered on the binding sites of each protein structure in order to allow each ligand to search. If a co-crystallized inhibitor or substrate was present in the structure, then that site was chosen as the binding site. If no co-crystallized ligand was present, then suitably sized (> 50 Ã… 3 ) cavities were used as potential binding sites. Standard protonation states of the proteins based on neutral pH were used in the docking studies. Each protein was used as a rigid model structure; no relaxation of the protein was performed. Assignments of charges on each protein were based on standard templates as part of the Molegro Virtual Docker program; no other charges were necessary to be set. Overall, 2194 plant-derived secondary metabolites have been docked. This molecule set was comprised of 290 alkaloids (68 indole alkaloids, 153 isoquinoline alkaloids, 5 quinoline alkaloids, 13 piperidine alkaloids, 14 steroidal alkaloids, and 37 miscellaneous alkaloids), 678 terpenoids (47 monoterpenoids, 169 sesquiterpenoids, 265 diterpenoids, 81 steroids, and 96 triterpenoids), 20 aurones, 81 chalcones, 349 flavonoids, 120 isoflavonoids, 74 lignans, 58 stilbenoids, 169 miscellaneous polyphenolic compounds, 100 coumarins, 28 xanthones, 67 quinones, and 160 miscellaneous phytochemicals. While this list does not include all phytochemicals, it does represent a practical selection of phytochemical classes and structural types. Each ligand structure was built using Spartan '14 for Windows (version 1.1.8, Wavefunction Inc., Irvine, California). For each ligand, a conformational search and geometry optimization was carried out using the MMFF force field [40] . Flexible ligand models were used in the docking and subsequent optimization scheme. Variable orientations of each of the ligands were searched and ranked based on their re-rank score. For each docking simulation the maximum number of iterations for the docking algorithm was set to 1500, with a maximum population size of 50, and 100 runs per ligand. The RMSD threshold for multiple poses was set to 1.00 Ã…. T