Discontinuous epitopes on the modelled structure of the Indian case 1 SARS-CoV-2 spike protein were predicted using the online servers, Ellipro (http://tools.iedb.org/ellipro/) and DiscoTope 2.0 (http://tools.iedb.org/discotope/), integrated in the Immune Epitope Database. Ellipro predicts epitopes based on the protusion index (PI), wherein the protein shape is approximated as an ellipsoid (Ref for Ellipro and DiscoTope). An ellipsoid with the PI value of 0.8 indicates that 80 per cent of the residues are within the ellipsoid and 20 per cent are outside. All residues that are outside the 80 per cent ellipsoid will have a score of 0.8. Residues with larger scores are associated with greater solvent accessibility. The PI value was set to a score of 0.8. DiscoTope predicts epitopes using 3D structure and half-sphere exposure as a surface measure in a novel spatial neighbourhood definition method. Default values were set for sensitivity (0.47) and specificity (0.75) for selecting the amino acids forming discontinuous epitopes. A sensitivity of 0.47 means that 47 per cent of the epitope residues are predicted as part of the epitopes, while a specificity of 0.75 means that 25 per cent of the non-epitope residues are predicted as part of the epitopes. Outputs from both the methods were combined, and the final regions were mapped on the modelled 3D-structure as the most probable conformational epitopes. In addition, we also predicted N-linked glycosylation sites in the S protein using NetNGlyc 1.0 Server (http://www.cbs.dtu.dk/services/NetNGlyc/). The spike proteins were also screened for the presence of potential epitopes presented by major histocompatibility complex (MHC) class I molecules to cytotoxic T lymphocytes (CTLs). The online NetCTL1.2 server (http://www.cbs.dtu.dk/services/NetCTL/) based on machine learning techniques such as artificial neural network (ANN) and support vector machine (SVM) was used to predict the T-cell epitopes. The prediction was made for all the human leucocyte antigen (HLA) supertypes and the available human alleles. The C terminal cleavage, weight of transport-associated protein (TAP) efficiency and threshold for identification were kept as default. VaxiJen v2.0 tool was used to predict the antigenicity of the predicted epitopes (http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html). The sequences were further screened to be potential epitopes using the CTLPred online server (http://crdd.osdd.net/raghava/ctlpred/).