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Epitope identification of SARS-CoV-2 structural proteins using in silico approaches to obtain a conserved rational immunogenic peptide.

ABSTRACT: The short time between the first cases of COVID-19 and the declaration of a pandemic initiated the search for ways to stop the spread of SARS-CoV-2. There are great expectations regarding the development of effective vaccines that protect against all variants, and in the search for it, we hypothesized the obtention of a predicted rational immunogenic peptide from structural components of SARS-CoV-2 might help the vaccine research direction. In the search for a candidate of an immunogenic peptide of the SARS-CoV-2 envelope (E), membrane (M), nucleocapsid (N), or spike (S) proteins, we access the predicted sequences of each protein after the genome sequenced worldwide. We obtained the consensus amino acid sequences of about 14,441 sequences of each protein of each continent and the worldwide consensus sequence. For epitope identification and characterization from each consensus structural protein related to MHC-I or MHC-II interaction and B-cell receptor recognition, we used the IEDB reaching 68 epitopes to E, 174 to M, 245 to N, and 833 to S proteins. To select an epitope with the highest probability of binding to the MHC or BCR, all epitopes of each consensus sequence were aligned. The curation indicated 1, 4, 8, and 21 selected epitopes for E, M, N, and S proteins, respectively. Those epitopes were tested in silico for antigenicity obtaining 16 antigenic epitopes. Physicochemical properties and allergenicity evaluation of the obtained epitopes were done. Ranking the results, we obtained one epitope of each protein except for the S protein that presented two epitopes after the selection. To check the 3D position of each selected epitope in the protein structure, we used molecular homology modeling. Afterward, each selected epitope was evaluated by molecular docking to reference MHC-I or MHC-II allelic protein sequences. Taken together, the results obtained in this study showed a rational search for a putative immunogenic peptide of SARS-CoV-2 structural proteins that can improve vaccine development using in silico approaches. The epitopes selected represent the most conserved sequence of new coronavirus and may be used in a variety of vaccine development strategies since they are also presented in the described variants of SARS-CoV-2.

SUBMITTER: Araujo LP

PROVIDER: S-EPMC9188263 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:COVID-19 caused by SARS-CoV-2 was declared a global pandemic by WHO (World Health Organization) in March, 2020. Within 6 months, nearly 750,000 deaths are claimed by COVID-19 across the globe. This called for immediate social, scientific, technological, public and community interventions. Considering the severity of infection and the associated mortalities, global efforts are underway to develop preventive measures against SARS-CoV-2. Among the SARS-CoV-2 target proteins, Spike (S) glycoprotein (a.k.a S Protein) is the most studied target known to trigger strong host immune response. A detailed analysis of S protein-based epitopes enabled us to design a novel B-cell-derived T-cell Multi-epitope-based peptide (MEBP) vaccine candidate. This involved a systematic and comprehensive computational protocol consisting of prediction of dual-purpose epitopes and designing an MEBP vaccine construct. This was followed by 3D structure validation, MEBP complex interaction studies, in silico cloning and vaccine dose-based immune response simulation to evaluate the immunogenic potency of the vaccine construct. The dual-purpose epitope prediction protocol was designed such that the same epitope elicits both humoral and cellular immune response unlike the earlier designs. Further, the epitopes predicted were screened against stringent criteria to ensure selection of a potent candidate with maximum antigen coverage and best immune response. The vaccine dose-based immune response simulation studies revealed a rapid antigen clearance through antibody generation and elevated levels of cell-mediated immunity during repeated exposure of the vaccine. The favourable results of the analysis strongly indicate that the vaccine construct is indeed a potent vaccine candidate and ready to proceed to the next steps of experimental validation and efficacy studies.Supplementary informationThe online version contains supplementary material available at 10.1007/s13205-020-02574-x.

Project description: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.

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Epitope identification of SARS-CoV-2 structural proteins using in silico approaches to obtain a conserved rational immunogenic peptide.

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