Selected article for: "alpha helix and structure analysis"

Author: Neha Jain; Uma Shankar; Prativa Majee; Amit Kumar
Title: Scrutinizing the SARS-CoV-2 protein information for the designing an effective vaccine encompassing both the T-cell and B-cell epitopes
  • Document date: 2020_4_1
  • ID: lmstdmyb_62
    Snippet: Secondary and tertiary structure helps in the functional annotation of the multi-epitope vaccines. It also helps in analyzing the interaction of this vaccine construct with the immunological receptors like TLRs. Secondary structure of the protein was analyzed by using SOPMA and PSIPRED server that revealed the presence of ~40 % alpha helix, ~20 % β-sheet, ~30 % coils and ~6 % β turns in the vaccine construct ( Figure 5 and Supplementary Figure .....
    Document: Secondary and tertiary structure helps in the functional annotation of the multi-epitope vaccines. It also helps in analyzing the interaction of this vaccine construct with the immunological receptors like TLRs. Secondary structure of the protein was analyzed by using SOPMA and PSIPRED server that revealed the presence of ~40 % alpha helix, ~20 % β-sheet, ~30 % coils and ~6 % β turns in the vaccine construct ( Figure 5 and Supplementary Figure S3 ). Tertiary structure of the vaccine was predicted by threading based homology modelling using Robetta server ( Figure 6A ). Ramachandran plot analysis of the modelled structure revealed the presence of 95.5 % residues in the most favoured regions and 4.5 % in the additionally allowed regions ( Figure 6B ). Quality factor was analyzed by using ERRAT2 server and was obtained to be 90.47 depicting a good modelled structure ( Figure 6C ). To further refine the modelled structure, 3D refine and GalaxyRefine were utilized that leads to 97.4 % residues in the most favoured region and 2.6 % residues in the additionally allowed region. The quality factor of the refined structure was observed to be 94.29% depicting the improvement of the modelled structure ( Figure 6D-F) . The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.26.009209 doi: bioRxiv preprint

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