Elucidation of novel compounds and epitope-based peptide vaccine design against C30 endopeptidase regions of SARS-CoV-2 using immunoinformatics approaches.

There has been progressive improvement in immunoinformatics approaches for epitope-based peptide design. Computational-based immune-informatics approaches were applied to identify the epitopes of SARS-CoV-2 to develop vaccines. The accessibility of the SARS-CoV-2 protein surface was analyzed, and hexa-peptide sequences (KTPKYK) were observed having a maximum score of 8.254, located between amino acids 97 and 102, whereas the FSVLAC at amino acids 112 to 117 showed the lowest score of 0.114. The surface flexibility of the target protein ranged from 0.864 to 1.099 having amino acid ranges of 159 to 165 and 118 to 124, respectively, harboring the FCYMHHM and YNGSPSG hepta-peptide sequences. The surface flexibility was predicted, and a 0.864 score was observed from amino acids 159 to 165 with the hepta-peptide (FCYMHHM) sequence. Moreover, the highest score of 1.099 was observed between amino acids 118 and 124 against YNGSPSG. B-cell epitopes and cytotoxic T-lymphocyte (CTL) epitopes were also identified against SARS-CoV-2. In molecular docking analyses, -0.54 to -26.21 kcal/mol global energy was observed against the selected CTL epitopes, exhibiting binding solid energies of -3.33 to -26.36 kcal/mol. Based on optimization, eight epitopes (SEDMLNPNY, GSVGFNIDY, LLEDEFTPF, DYDCVSFCY, GTDLEGNFY, QTFSVLACY, TVNVLAWLY, and TANPKTPKY) showed reliable findings. The study calculated the associated HLA alleles with MHC-I and MHC-II and found that MHC-I epitopes had higher population coverage (0.9019% and 0.5639%) than MHC-II epitopes, which ranged from 58.49% to 34.71% in Italy and China, respectively. The CTL epitopes were docked with antigenic sites and analyzed with MHC-I HLA protein. In addition, virtual screening was conducted using the ZINC database library, which contained 3,447 compounds. The 10 top-ranked scrutinized molecules (ZINC222731806, ZINC077293241, ZINC014880001, ZINC003830427, ZINC030731133, ZINC003932831, ZINC003816514, ZINC004245650, ZINC000057255, and ZINC011592639) exhibited the least binding energy (-8.8 to -7.5 kcal/mol). The molecular dynamics (MD) and immune simulation data suggest that these epitopes could be used to design an effective SARS-CoV-2 vaccine in the form of a peptide-based vaccine. Our identified CTL epitopes have the potential to inhibit SARS-CoV-2 replication.

Epitope-based peptide vaccine design and elucidation of novel compounds against 3C like protein of SARS-CoV-2.

Coronaviruses (CoVs) are positive-stranded RNA viruses with short clubs on their edges. CoVs are pathogenic viruses that infect several animals and plant organisms, as well as humans (lethal respiratory dysfunctions). A noval strain of CoV has been reported and named as SARS-CoV-2. Numerous COVID-19 cases were being reported all over the World. COVID-19 and has a high mortality rate. In the present study, immunoinformatics techniques were utilized to predict the antigenic epitopes against 3C like protein. B-cell epitopes and Cytotoxic T-lymphocyte (CTL) were designed computationally against SARS-CoV-2. Multiple Sequence Alignment (MSA) of seven complete strains (HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1, SARS-CoV, MERS-CoV, and SARS-CoV-2) was performed to elucidate the binding domain and interacting residues. MHC-I binding epitopes were evaluated by analyzing the binding affinity of the top-ranked peptides having HLA molecule. By utilizing the docked complexes of CTL epitopes with antigenic sites, the binding relationship and affinity of top-ranked predicted peptides with the MHC-I HLA protein were investigated. The molecular docking analyses were conducted on the ZINC database library and twelve compounds having least binding energy were scrutinized. In conclusion, twelve CTL epitopes (GTDLEGNFY, TVNVLAWLY, GSVGFNIDY, SEDMLNPNY, LSQTGIAV, VLDMCASLK, LTQDHVDIL, TTLNDFNLV, CTSEDMLNP, TTITVNVLA, YNGSPSGVY, and SMQNCVLKL) were identified against SARS-CoV-2.