| Tertiary Structure prediction, and Molecular dynamic simulation studies on NSP6 of SARS-CoV-2 |
| Paper ID : 1075-ISCH |
| Authors |
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Mohammed Salama *1, MEDHAT WAHBA SHAFAA2, MOHAMED EL-SAYED EL-NAGDY2, MOHAMED EL-SAYED HASAN3 1Physics department, Faculty of Science, Helwan University. 2helwan university, cairo 3University of Sadat City, Genetic Engineering and Biotechnology Research Institute, Bioinformatics Department, Sadat City 32897, Egypt. Borg Al Arab Technological University (BATU), Faculty of Applied Health Science, Department of Health Information Technology, Borg Al Arab, Egypt. |
| Abstract |
| The Non-structural protein 6 (NSP6) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is one of the most interesting proteins to study in targeting SARS-CoV-2. As there is no verified tertiary structure of NSP6, this study aims to use bioinformatical tools in predicting a high quality and highly assessed tertiary structure of NSP6. LOMETS, SWISS-MODEL, C-Quark, I-Tasser, Galaxyweb, Phyre2, Robetta, and AlphaFold servers were used to generate the predicted models. Then these models were subjected to ModRefiner, GalaxyRefine, 3D-refine, DeepRefiner, GalaxyRefine2, and ReFOLD3 servers to refine the models to increase their quality, producing more than 40 high quality models. After that the quality of these models was inspected using quality assurance servers. Finally molecular dynamics simulation was applied on the highest quality model. The AlphaFold model displayed the highest overall quality percentage (99.6%) according to the ERRAT server. The structural classification and functional annotations of the NSP6 protein of SARS-CoV-2 were characterized using the CATH, InterPro, SCOP and SUPERFAMILY databases, which included only one matching protein. A 100 ns molecular dynamic simulation study was conducted on the verified model using RMSD, RMSF, Rg, and SASA results and proved the stability of the model. The integration between the construction, refinement, and assessment of the models and MDS study has shown that the AlphaFold server generated the best-predicted model and MD simulation study was applied to guarantee the stability of the protein for more advanced studies including suitable drug and vaccine design. |
| Keywords |
| SARS-CoV-2; NSP6; in silico; Phylogenetic tree; Ab-initio; Protein structure prediction; Tertiary structure; MDS |
| Status: Abstract Accepted (Poster Presentation) |