Author: Sukrit Srivastava; Sonia Verma; Mohit Kamthania; Rupinder Kaur; Ruchi Kiran Badyal; Ajay Kumar Saxena; Ho-Joon Shin; Kailash Pandey; Michael Kolbe
Title: Structural basis to design multi-epitope vaccines against Novel Coronavirus 19 (COVID19) infection, the ongoing pandemic emergency: an in silico approach Document date: 2020_4_3
ID: 80m78jh2_6
Snippet: Tools" of IEDB server (http://tools.iedb.org/bcell/) was utilized. In this screening, 321 the parameters such as hydrophilicity, flexibility, accessibility, turns, exposed 322 surface, polarity and the antigenic propensity of the polypeptides is correlated 323 with its location in the protein. This allows the search for continuous epitopes 324 prediction from protein sequence. The prediction is base on the propensity scales 325 for each of the 20.....
Document: Tools" of IEDB server (http://tools.iedb.org/bcell/) was utilized. In this screening, 321 the parameters such as hydrophilicity, flexibility, accessibility, turns, exposed 322 surface, polarity and the antigenic propensity of the polypeptides is correlated 323 with its location in the protein. This allows the search for continuous epitopes 324 prediction from protein sequence. The prediction is base on the propensity scales 325 for each of the 20 amino acids. For a window size n, the i -(n-1)/2 neighboring 326 residues on each side of residue i are used to compute the score for the residue 327 i. The method "Bepipred Linear Epitope Prediction" utilized here is based on the 328 propensity scale method as well as the physiochemical properties of the given 329 antigenic sequence to screen potential epitopes (Larsen et al., 2006) . 330 331
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