Search of dengue protease inhibitors from natural product database using ensemble-based virtual screening / Nor Farrah Wahidah Ridzwan

• 主要作者: Nor Farrah Wahidah , Ridzwan
• 格式: Thesis
• 出版: 2018
• 主题: Q Science (General)

As the number of reported dengue cases appears to increase each year, it has become a great concern globally that there has yet to be any specific treatment for it. Nevertheless, previous studies have identified several of the dengue virus proteins as the potential target for the development of antiviral whereby, the viral protease has become the most favourable target. Virtual screening (VS) provides an alternative option from the conventional screening in drug discovery and has frequently been used by researchers worldwide mainly due to its cost-effectiveness. An extension of the standard VS called the ensemble-based incorporates the flexibility of receptor and ligand in the VS. Therefore, this approach that takes into account the existing multiple conformations of the target’s structure would ultimately enhance the obtained VS findings. In general, this study aimed at identifying natural-based compounds that can serve as dengue protease inhibitors via the ensemble-based approach and to further evaluate the generated protein-ligand interactions. The collections of natural-based ligands were retrieved from the Super Natural II database utilising adapted criteria of the Lipinski’s rule of five. Prior to the screening procedure, the three-dimensional structure of the protease was first obtained from the protein data bank (PDB), followed by model generation via MODELLER to address the missing residues and were further evaluated using PROCHECK. Next, molecular dynamic (MD) simulations of the protease were conducted and assessed via GROMACS. Several clustered structures of the protease were then generated and selected from the MD simulations’ trajectories representing as the macromolecule or receptor in the subsequent virtual screening or molecular docking via AutoDock. The molecular docking simulations were conducted twice with the initial simulation aimed to identify the ligands that showed a strong affinity towards the protease whereas the second simulation was done to verify and strengthening the initial results. Based on the findings, several ligands showed promising potential as the dengue protease inhibitors that bears strong binding energy and interaction with at least one of the catalytic triads of the dengue protease structure. Thus, the listed ligands would provide a good starting point for extending the utilisation and confirmation of this studies and may be used as lead-compounds in generating an antiviral for the dengue virus.