The design for vaccines using in silico analysis of genomic data of different viruses has taken many different paths, but lack of any precise computational approach has constrained them to alignment methods and some alignment-free techniques. In this work, a precise computational approach has been established wherein two new mathematical parameters have been suggested to identify the highly conserved and surface-exposed regions which are spread over a large region of the surface protein of the virus so that one can determine possible peptide vaccine candidates from those regions. The first parameter, w, is the sum of the normalized values of the measure of surface accessibility and the normalized measure of conservativeness, and the second parameter is the area of a triangle formed by a mathematical model named 2D Polygon Representation. This method has been, therefore, used to determine possible vaccine targets against SARS-CoV-2 by considering its surfacesituated spike glycoprotein. The results of this model have been verified by a parallel analysis using the older approach of manually estimating the graphs describing the variation of conservativeness and surface-exposure across the protein sequence. Furthermore, the working of the method has been tested by applying it to find out peptide vaccine candidates for Zika and Hendra viruses respectively. A satisfactory consistency of the model results with pre-established results for both the test cases shows that this in silico alignment-free analysis proposed by the model is suitable not only to determine vaccine targets against SARS-CoV-2 but also ready to extend against other viruses.

The currently surging SARS-COV-2 (or CoVID-19) is challenging the public health authorities worldwide. As of now there is no approved vaccine or drug available for the control of the viral disease. Therefore, non-pharmaceutical interventions (NPIs) are being used around the world to manage the spread of CoVID-19. In this article we used a computer-assisted vaccine design (CAVD) approach to develop a set of most probable peptide vaccine candidates which can be tested for their efficacy by wet lab experiments.

No abstract

We consider a novel approach to mathematically define a graphing method to represent amino acid sequences of proteins in two-dimensional plane and characterize them numerically. The amino acids are represented by their relative magnitude of their hydrophobicity.