Strategies for vaccine design for corona virus using Immunoinformatics techniques

Anamika Basu; Anasua Sarkar; Ujjwal Maulik

Various physico-chemical properties e.g. hydrophilicity, flexibility, accessibility, turns, exposed surface, polarity and antigenic propensity of peptides chains have been estimated to identify the locations of linear epitopes of an antigenic protein [11] . Thus, different tools from IEDB (www.iedb.org), including the classical propensity scale methods such as Kolaskar and Tongaonkar antigenicity scale [12] , E mini surface accessibility prediction [13] , Parker hydrophilicity prediction [14] , Karplus and Schulz flexibilty prediction [15] , Bepipred linear epitope prediction [16] and Chou and Fashman beta turn prediction tool [17] are used to predict linear or continous B cell epitopes of nonstructural protein NS4 protein in coronavirus. With the help of graphical findings and prediction scores the most probable B cell epitope of that antigenic protein has been identified. BepiPred prediction method is a combination of Hidden Markov model and propensity scale method to predict score and identification of B cell epitopes of antigenic protein [16] .