The docked structures were visualized through PyMol (http://www.pymol.org) to analyse the interactions between vaccine and TLRs. complex also showed low deformation and increased rigidity in motion of residues during dynamics. Furthermore, cloning of the multi-epitope vaccine was carried out to generate the plasmid construct for expression in a bacterial system. Altogether, our study suggests that the designed vaccine candidate containing RBD region could provide the specific humoral and cell-mediated immune responses against SARS-CoV-2. YM-90709 Communicated by Ramaswamy H. Sarma cloning. 2.2. Cytotoxic T lymphocyte (CTL) epitope prediction The CTL epitopes of SARS-CoV-2 RBD were determined using the server, NetCTL v1.2 (http://www.cbs.dtu.dk/services/NetCTL/) for all the MHC-I supertypes (A1, A2, A3, A24, A26, B7, B8, B27, B39, B44, B58, B62) with 0.75 threshold value having 0.80 sensitivity and 0.97 specificity, while TAP transport efficiency and weight YM-90709 on C-terminal cleavage were kept as default parameters. Subsequently, the antigenicity and immunogenicity of these epitopes were evaluated with VaxiJen v2.0 server and IEDB MHC-I immunogenicity tool (http://tools.iedb.org/immunogenicity/), respectively. Simultaneously, AllergenFP v1.0 server and ToxinPred server (http://crdd.osdd.net/raghava/toxinpred/) were used to analyse the allergic and toxic properties, respectively. Further, MHC-I binding alleles for the selected 9-mer CTL epitopes with antigenic, immunogenic, non-allergenic and non-toxic properties were predicted by a Consensus method of IEDB MHC-I binding tool (http://tools.iedb.org/mhci/) with human as a MHC-I source species and percentile rank 2. 2.3. Helper T lymphocyte (HTL) epitope prediction Fifteen amino acids long HTL epitopes for RBD domain were predicted using Immune Epitopes and Analysis Resource (IEDB) server (http://tools.iedb.org/mhcii/). The NN_Align method was applied to calculate IC50 value and percentile rank for peptide interacting with the MHC-II molecules. Human was considered as a source species, while loci, HLA-DP, HLA- DQ and HLA-DR were used for analysis. The IC50 value 20?nM and percentile rank 2 were considered for prediction as these values correspond to higher binding affinity. Finally, Predicted HTL epitopes were screened according to their antigenicity, allergenicity and toxicity. 2.4. Interferon- (IFN-) inducing epitope prediction Helper T-cells produce cytokines like IFN- (interferon-gamma) that leads to the activation of many Cxcr3 immune cells including cytotoxic T-cells, making cytokine-stimulating HTL epitopes a critical factor for vaccine development. IFNepitope server (http://crdd.osdd.net/raghava/ifnepitope/) was applied to identify the HTL epitopes that can produce IFN- with SVM and Motif based hybrid method and IFN- versus Non-IFN- model. 2.5. Linear B lymphocyte (LBL) epitope prediction Detection of B-cell epitopes is an essential part to develop epitope-based vaccine as they generate antibodies that elicit humoral immune response. ABCpred YM-90709 server (http://crdd.osdd.net/raghava/abcpred/) was employed to predict the epitopes followed by further evaluation using BepiPred server of IEDB (http://tools.iedb.org/bcell/help/#Bepipred). The epitopes that are common for both of the tools were selected for further analysis. As the B-cell epitope is present on the cell surface, exomembrane topology is considered as one of the essential parameter. The allergenicity, antigenicity, toxicity and transmembrane topology of the epitopes were evaluated by AllergenFP v1.0, VaxiJen v2.0, ToxinPred and TMHMM v2.0 server, respectively. B-cell epitopes were also characterized by its surface accessibility, hydrophilicity, flexibility, and beta-turn by using Emini surface accessibility prediction tool, Parker hydrophilicity scale, Karplus & Schulz flexibility scale and Chou & Fasman beta-turn prediction, respectively (http://tools.iedb.org/bcell/). 2.6. Analysis of cross-reactivity and population coverage To avoid the cross-reactivity, the predicted epitopes were employed to search against the database of human proteome from UniProt using Multiple Peptide Match YM-90709 tool of Protein Information Resource (https://research.bioinformatics.udel.edu/peptidematch/batchpeptidematch.jsp). Simultaneously, the Population Coverage tool of IEDB (http://tools.iedb.org/population/) was used to analyse the potential CTL and HTL epitopes as expression and distribution of its HLA alleles diverge within the ethnicities, regions and countries worldwide that affect the development of epitope-based vaccines. This tool utilizes the dissemination of human MHC binding alleles and provides.