Development of a suitable recombinant peptide vaccine against pathogens requires designing of effective immunogenic polypeptide taking various aspects and complexity of immune-response into consideration. Implementing SARS-CoV-2 spike glycoprotein (S-protein) and RNA-dependent RNA polymerase (RdRp) as model targets, in this study, we outline and assess a strategy for in silico recombinant vaccine designing. After mapping the linear B-cell epitopes and MHC1-binding T-cell epitopes six epitopes were sorted from each of the proteins on the basis of extent of residue-conservancy among three types of coronaviruses namely SARS-CoV-2, SARS-CoV and MERS-CoV. Each of the selected epitopes were profiled for their pro-inflammatory potential through molecular docking analysis with surface bound Toll-like receptors, namely TLR2, TLR4 and TLR5. Based on a custom scoring function, the epitopes were ranked for highest and least pro-inflammatory potential. Segments of Spike and RdRp harboring such epitopes were combined using linkers to design immunogenic recombinant polypeptide. Antigenicity and allergenicity of each of the combination was scored; and the best fitting one was docked against TLR2, TLR4 and TLR5 for assessing pro-inflammatory potential. Codon optimization and in silico cloning in expression vector indicated that the designed peptide can be satisfactorily expressed in bacteria, reinforcing the viability of the strategy in identification and designing of potential immunogens.