scholarly journals Structural Basis for Designing Multiepitope Vaccines Against COVID-19 Infection: In Silico Vaccine Design and Validation

10.2196/19371 ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. e19371 ◽  
Author(s):  
Sukrit Srivastava ◽  
Sonia Verma ◽  
Mohit Kamthania ◽  
Rupinder Kaur ◽  
Ruchi Kiran Badyal ◽  
...  
Keyword(s):  
B Cell ◽  
Cell Line ◽  
T Lymphocyte ◽  
Molecular Interactions ◽  
In Silico ◽  
Antigen Processing ◽  
Vaccine Design ◽  
Structural Basis ◽  
Toll Like Receptor ◽  
Vaccine Candidates

Background The novel coronavirus disease (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the ongoing 2019-2020 pandemic. SARS-CoV-2 is a positive-sense single-stranded RNA coronavirus. Effective countermeasures against SARS-CoV-2 infection require the design and development of specific and effective vaccine candidates. Objective To address the urgent need for a SARS-CoV-2 vaccine, in the present study, we designed and validated one cytotoxic T lymphocyte (CTL) and one helper T lymphocyte (HTL) multi-epitope vaccine (MEV) against SARS-CoV-2 using various in silico methods. Methods Both designed MEVs are composed of CTL and HTL epitopes screened from 11 structural and nonstructural proteins of the SARS-CoV-2 proteome. Both MEVs also carry potential B-cell linear and discontinuous epitopes as well as interferon gamma–inducing epitopes. To enhance the immune response of our vaccine design, truncated (residues 10-153) Onchocerca volvulus activation-associated secreted protein-1 was used as an adjuvant at the N termini of both MEVs. The tertiary models for both the designed MEVs were generated, refined, and further analyzed for stable molecular interaction with toll-like receptor 3. Codon-biased complementary DNA (cDNA) was generated for both MEVs and analyzed in silico for high level expression in a mammalian (human) host cell line. Results In the present study, we screened and shortlisted 38 CTL, 33 HTL, and 12 B cell epitopes from the 11 protein sequences of the SARS-CoV-2 proteome. Moreover, the molecular interactions of the screened epitopes with their respective human leukocyte antigen allele binders and the transporter associated with antigen processing (TAP) complex were positively validated. The shortlisted screened epitopes were utilized to design two novel MEVs against SARS-CoV-2. Further molecular models of both MEVs were prepared, and their stable molecular interactions with toll-like receptor 3 were positively validated. The codon-optimized cDNAs of both MEVs were also positively analyzed for high levels of overexpression in a human cell line. Conclusions The present study is highly significant in terms of the molecular design of prospective CTL and HTL vaccines against SARS-CoV-2 infection with potential to elicit cellular and humoral immune responses. The epitopes of the designed MEVs are predicted to cover the large human population worldwide (96.10%). Hence, both designed MEVs could be tried in vivo as potential vaccine candidates against SARS-CoV-2.

scholarly journals Structural Basis for Designing Multiepitope Vaccines Against COVID-19 Infection: In Silico Vaccine Design and Validation (Preprint)

2020 ◽  
Author(s):  
Sukrit Srivastava ◽  
Sonia Verma ◽  
Mohit Kamthania ◽  
Rupinder Kaur ◽  
Ruchi Kiran Badyal ◽  
...  
Keyword(s):  
B Cell ◽  
Cell Line ◽  
T Lymphocyte ◽  
Molecular Interactions ◽  
In Silico ◽  
Vaccine Design ◽  
Structural Basis ◽  
Toll Like Receptor ◽  
Vaccine Candidates ◽  
Line P

BACKGROUND The novel coronavirus disease (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the ongoing 2019-2020 pandemic. SARS-CoV-2 is a positive-sense single-stranded RNA coronavirus. Effective countermeasures against SARS-CoV-2 infection require the design and development of specific and effective vaccine candidates. OBJECTIVE To address the urgent need for a SARS-CoV-2 vaccine, in the present study, we designed and validated one cytotoxic T lymphocyte (CTL) and one helper T lymphocyte (HTL) multi-epitope vaccine (MEV) against SARS-CoV-2 using various in silico methods. METHODS Both designed MEVs are composed of CTL and HTL epitopes screened from 11 structural and nonstructural proteins of the SARS-CoV-2 proteome. Both MEVs also carry potential B-cell linear and discontinuous epitopes as well as interferon gamma–inducing epitopes. To enhance the immune response of our vaccine design, truncated (residues 10-153) <i>Onchocerca volvulus</i> activation-associated secreted protein-1 was used as an adjuvant at the N termini of both MEVs. The tertiary models for both the designed MEVs were generated, refined, and further analyzed for stable molecular interaction with toll-like receptor 3. Codon-biased complementary DNA (cDNA) was generated for both MEVs and analyzed in silico for high level expression in a mammalian (human) host cell line. RESULTS In the present study, we screened and shortlisted 38 CTL, 33 HTL, and 12 B cell epitopes from the 11 protein sequences of the SARS-CoV-2 proteome. Moreover, the molecular interactions of the screened epitopes with their respective human leukocyte antigen allele binders and the transporter associated with antigen processing (TAP) complex were positively validated. The shortlisted screened epitopes were utilized to design two novel MEVs against SARS-CoV-2. Further molecular models of both MEVs were prepared, and their stable molecular interactions with toll-like receptor 3 were positively validated. The codon-optimized cDNAs of both MEVs were also positively analyzed for high levels of overexpression in a human cell line. CONCLUSIONS The present study is highly significant in terms of the molecular design of prospective CTL and HTL vaccines against SARS-CoV-2 infection with potential to elicit cellular and humoral immune responses. The epitopes of the designed MEVs are predicted to cover the large human population worldwide (96.10%). Hence, both designed MEVs could be tried in vivo as potential vaccine candidates against SARS-CoV-2.

scholarly journals Exploring the structural basis to develop efficient multi-epitope vaccines displaying interaction with HLA and TAP and TLR3 molecules to prevent NIPAH infection, a global threat to human health

2021 ◽  
Author(s):  
Sukrit Srivastava ◽  
Ajay Kumar Saxena ◽  
Michael Kolbe
Keyword(s):  
Immune Response ◽  
B Cell ◽  
T Lymphocyte ◽  
Antigen Processing ◽  
Dynamics Simulation ◽  
Structural Basis ◽  
Effective Vaccine ◽  
Mammalian Host ◽  
Ctl Epitopes ◽  
Epitope Vaccines

Nipah virus (NiV) is an emerging zoonotic virus responsible to cause several serious outbreaks in South Asian region with high mortality rate of 40 to 90% since 2001. NiV infection causes lethal encephalitis and respiratory disease with the symptom of endothelial cell-cell fusion. No specific vaccine has yet been reported against NiV infection. Recently, some Multi-Epitope Vaccines (MEV) has been proposed but they involve limited number of epitopes which further limits the potential of vaccine. To address the urgent need for a specific and effective vaccine against NiV infection, in the present study, we have design two multi-epitope vaccines (MEVs) composed of 33 Cytotoxic T lymphocyte (CTL) epitopes and 38 Helper T lymphocyte (HTL) epitopes. Both the MEVs carry potential B cell linear epitope overlapping regions, B cell discontinuous epitopes as well as IFN-γ inducing epitopes. Hence the designed MEVs carry potential to elicit cell-mediated as well as humoral immune response. Selected CTL and HTL epitopes were validated for their stable molecular interactions with HLA class I and II alleles as well as in case of CTL epitopes, with human transporter associated with antigen processing (TAP). Human β-defensin 2 and β-defensin 3 were used as adjuvants to enhance the immune response of both the MEVs. The molecular dynamics simulation study of MEVs-TLR3(ECD) (Toll-Like Receptor 3 Ectodomain) complex indicated stable molecular interaction. Further, the codon optimized cDNA of both the MEVs has shown high expression potential in the mammalian host cell line (Human). Hence for further studies, both the design of CTL and HTL MEVs could be cloned, expressed and tried for in-vivo validations (animal trails) as potential vaccine candidates against NiV infection.

scholarly journals In silico prediction of B cell epitopes of the hemolysis-associated protein 1 for vaccine design against leptospirosis

2020 ◽  
Vol 1 (1) ◽  
pp. 32-37
Author(s):  
Sakineh Poorhosein Fookolaee ◽  
Somayyeh Talebishelimaki ◽  
Mohammad Taha Saadati Rad ◽  
Mostafa Akbarian Rokni
Keyword(s):  
B Cell ◽  
In Silico ◽  
Vaccine Design ◽  
In Silico Prediction ◽  
B Cell Epitopes

scholarly journals Epitope order Matters in multi-epitope-based peptide (MEBP) vaccine design: An in silico study

2021 ◽  
Author(s):  
Muthu Raj Salaikumaran ◽  
Prasanna Sudharson Kasamuthu ◽  
V L S Prasad Burra
Keyword(s):  
In Silico ◽  
Experimental Validation ◽  
Vaccine Development ◽  
Experimental Testing ◽  
Peptide Vaccine ◽  
Vaccine Design ◽  
Vaccine Candidates ◽  
Vaccine Potency ◽  
Experimental Protocols ◽  
The Many

With different countries facing multiple waves, with some SARS-CoV-2 variants more deadly and virulent, the COVID-19 pandemic is becoming more dangerous by the day and the world is facing an even more dreadful extended pandemic with exponential positive cases and increasing death rates. There is an urgent need for more efficient and faster methods of vaccine development against SARS-CoV-2. Compared to experimental protocols, the opportunities to innovate are very high in immunoinformatics/in silico approaches especially with the recent adoption of structural bioinformatics in peptide vaccine design. In recent times, multi-epitope-based peptide vaccine candidates (MEBPVCs) have shown extraordinarily high humoral and cellular responses to immunization. Most of the publications claim that respective reported MEBPVC(s) assembled using a set of in silico predicted epitopes, to be the computationally validated potent vaccine candidate(s) ready for experimental validation. However, in this article, for a given set of predicted epitopes, it is shown that the published MEBPVC is one among the many possible variants and there is high likelihood of finding more potent MEBPVCs than the published candidate. To test the same, a methodology is developed where novel MEBP variants are derived by changing the epitope order of the published MEBPVC. Further, to overcome the limitations of current qualitative methods of assessment of MEBPVC, to enable quantitative comparison, ranking, and the discovery of more potent MEBPVCs, novel predictors, Percent Epitope Accessibility (PEA), Receptor specific MEBP vaccine potency(RMVP), MEBP vaccine potency(MVP) are introduced. The MEBP variants indeed showed varied MVP scores indicating varied immunogenicity. When the MEBP variants were ranked in descending order of their MVP scores, the published MEBPVC had the least MVP score. Further, the MEBP variants with IDs, SPVC_387 and SPVC_206, had the highest MVP scores indicating these variants to be more potent MEBPVCs than the published MEBPVC and hence should be prioritized for experimental testing and validation. Through this method, more vaccine candidates will be available for experimental validation and testing. This study also opens the opportunity to develop new software tools for designing more potent MEBPVCs in less time. The computationally validated top-ranked MEBPVCs must be experimentally tested, validated, and verified. The differences and deviations between experimental results and computational predictions provide an opportunity for improving and developing more efficient algorithms and reliable scoring schemes and software.

scholarly journals Structural basis to design multi-epitope vaccines against Novel Coronavirus 19 (COVID19) infection, the ongoing pandemic emergency: an in silico approach

2020 ◽  
Author(s):  
Sukrit Srivastava ◽  
Sonia Verma ◽  
Mohit Kamthania ◽  
Rupinder Kaur ◽  
Ruchi Kiran Badyal ◽  
...  
Keyword(s):  
Immune Response ◽  
Molecular Docking ◽  
T Lymphocyte ◽  
Antigen Processing ◽  
Onchocerca Volvulus ◽  
Secreted Protein ◽  
Toll Like Receptor ◽  
B Cell Epitopes ◽  
Novel Coronavirus ◽  
Epitope Vaccines

AbstractThe 2019 novel coronavirus (COVID19 / Wuhan coronavirus), officially named as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a positive-sense single-stranded RNA coronavirus. SARS-CoV-2 causes the contagious COVID19 disease also known as 2019-nCoV acute respiratory disease and has led to the ongoing 2019–20 pandemic COVID19 outbreak. The effective counter measures against SARS-CoV-2 infection require the design and development of specific and effective vaccine candidate. In the present study, we have screened and shortlisted 38 CTL, 33 HTL and 12 B cell epitopes from the eleven Protein sequences of SARS-CoV-2 by utilizing different in silico tools. The screened epitopes were further validated for their binding with their respective HLA allele binders and TAP (Transporter associated with antigen processing) molecule by molecular docking. The shortlisted screened epitopes were further utilized to design novel two multi-epitope vaccines (MEVs) composed of CTL, HTL and B cell epitopes overlaps with potential to elicit humoral as well as cellular immune response against SARS-CoV-2. To enhance the immune response for our vaccine design, truncated (residues 10-153) Onchocerca volvulus activation-associated secreted protein-1 (Ov-ASP-1) has been utilized as an adjuvant at N terminal of both the MEVs. Further molecular models for both the MEVs were prepared and validated for their stable molecular interactions with Toll-Like Receptor 3 (TLR 3). The codon-optimized cDNA of both the MEVs were further analyzed for their potential of high level of expression in a human cell line. The present study is very significant in terms of molecular designing of prospective CTL and HTL vaccine against SARS-CoV-2 infection with the potential to elicit cellular as well as humoral immune response. (SARS-CoV-2), Coronavirus, Human Transporter associated with antigen processing (TAP), Toll-Like Receptor (TLR), Epitope, Immunoinformatics, Molecular Docking, Molecular dynamics simulation, Multi-epitope VaccineGraphical abstractThe designed CTL (Cytotoxic T lymphocyte) and HTL (Helper T lymphocyte) multi-epitope vaccines (MEV) against COVID19 infection. Both the CTL and HTL MEV models show a very stable and well fit conformational complex formation tendency with the Toll like receptor 3. CTL and HTL MEVs: ribbon; Toll like receptor 3: gray cartoon; Adjuvant [truncated (residues 10-153) Onchocerca volvulus activation-associated secreted protein-1]: orange ribbon regions; Epitopes: cyan ribbons regions; 6xHis Tag: magenta ribbon regions.

scholarly journals Immunoinformatics Approach for Epitope-Based Peptide Vaccine Design and Active Site Prediction against Polyprotein of Emerging Oropouche Virus

2018 ◽  
Vol 2018 ◽  
pp. 1-22 ◽  
Author(s):  
Utpal Kumar Adhikari ◽  
Mourad Tayebi ◽  
M. Mizanur Rahman
Keyword(s):  
T Cell ◽  
Ligand Binding ◽  
B Cell ◽  
Peptide Vaccine ◽  
Vaccine Design ◽  
Binding Interaction ◽  
B Cell Epitopes ◽  
Vaccine Candidates ◽  
Binding Pockets ◽  
Potential Vaccine

Oropouche virus (OROV) is an emerging pathogen which causes Oropouche fever and meningitis in humans. Several outbreaks of OROV in South America, especially in Brazil, have changed its status as an emerging disease, but no vaccine or specific drug target is available yet. Our approach was to identify the epitope-based vaccine candidates as well as the ligand-binding pockets through the use of immunoinformatics. In this report, we identified both T-cell and B-cell epitopes of the most antigenic OROV polyprotein with the potential to induce both humoral and cell-mediated immunity. Eighteen highly antigenic and immunogenic CD8+ T-cell epitopes were identified, including three 100% conserved epitopes (TSSWGCEEY, CSMCGLIHY, and LAIDTGCLY) as the potential vaccine candidates. The selected epitopes showed 95.77% coverage for the mixed Brazilian population. The docking simulation ensured the binding interaction with high affinity. A total of five highly conserved and nontoxic linear B-cell epitopes “NQKIDLSQL,” “HPLSTSQIGDRC,” “SHCNLEFTAITADKIMSL,” “PEKIPAKEGWLTFSKEHTSSW,” and “HHYKPTKNLPHVVPRYH” were selected as potential vaccine candidates. The predicted eight conformational B-cell epitopes represent the accessibility for the entered virus. In the posttherapeutic strategy, ten ligand-binding pockets were identified for effective inhibitor design against emerging OROV infection. Collectively, this research provides novel candidates for epitope-based peptide vaccine design against OROV.

scholarly journals In Silico screening of T-cell and B-cell Epitopes of Rotavirus VP7 and VP4 proteins for Effective Vaccine Design

2019 ◽  
Vol 35 (1) ◽  
pp. 45-55
Author(s):  
Md Sadikur Rahman Shuvo ◽  
Sanjoy Kumar Mukharjee ◽  
Firoz Ahmed
Keyword(s):  
Developing Countries ◽  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Child Death ◽  
Vaccine Design ◽  
Effective Vaccine ◽  
World Population ◽  
Promising Alternative ◽  
B Cell Epitopes

Rotavirus is one of the deadliest causative agents of childhood diarrhea which causes half a million child death across the globe, mostly in developing countries. However, effective vaccine strategies against rotavirus are yet to be established to prevent these unwanted premature deaths. In this regard, in silico vaccine design for rotavirus could be a promising alternative for developing countries due to its efficiency in shortening valuable time and cost. The present study described an epitope-based peptide vaccine design against rotavirus, using a combination of T-cell and B-cell epitope predictions and molecular docking approach. To perform this, sequences of rotavirus VP7 and VP4 proteins were retrieved from the NCBI database and subjected to different bioinformatics tools to predict most immunogenic T-cell and B-cell epitopes. From the identified epitopes, the sequence VMSKRSRSL of VP7 and TQFTDFVSL of VP4 was identified as the most potential epitopes based on their antigenicity, conservancy and interaction with major histocompatability complex I (MHC-I) alleles. Moreover, the peptide VMSKRSRSL interacted with human leukocyte antigen, HLA-B*08:01 and TQFTDFVSL interacted with HLA-A*02:06 with considerable binding energy and affinity score. Combined population coverage for our identified epitopes was found 70.53% and 45.64% for world population and South Asian population respectively. All these results suggest that, the epitopes identified in this study could be a very good vaccine candidate for the strains of rotavirus circulating in Bangladesh. However, as this study is completely dependent on computational prediction algorithms, further in vivo screening is required to come up in a precise conclusion about these epitopes for effective rotavirus vaccination. Bangladesh J Microbiol, Volume 35 Number 1 June 2018, pp 45-55

scholarly journals In Silico Prediction of a Multitope Vaccine against Moraxella catarrhalis: Reverse Vaccinology and Immunoinformatics

Vaccines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 669
Author(s):  
Mohamed A. Soltan ◽  
Nada Elbassiouny ◽  
Helmy Gamal ◽  
Eslam B. Elkaeed ◽  
Refaat A. Eid ◽  
...  
Keyword(s):  
Immune Response ◽  
Outer Membrane ◽  
T Lymphocyte ◽  
In Silico ◽  
Moraxella Catarrhalis ◽  
In Silico Analysis ◽  
Reverse Vaccinology ◽  
Effective Vaccine ◽  
Vaccine Candidates ◽  
Tract Infections

Moraxella catarrhalis (M. catarrhalis) is a Gram-negative bacterium that can cause serious respiratory tract infections and middle ear infections in children and adults. M. catarrhalis has demonstrated an increasing rate of antibiotic resistance in the last few years, thus development of an effective vaccine is a major health priority. We report here a novel designed multitope vaccine based on the mapped epitopes of the vaccine candidates filtered out of the whole proteome of M. catarrhalis. After analysis of 1615 proteins using a reverse vaccinology approach, only two proteins (outer membrane protein assembly factor BamA and LPS assembly protein LptD) were nominated as potential vaccine candidates. These proteins were found to be essential, outer membrane, virulent and non-human homologs with appropriate molecular weight and high antigenicity score. For each protein, cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B cell lymphocyte (BCL) epitopes were predicted and confirmed to be highly antigenic and cover conserved regions of the proteins. The mapped epitopes constituted the base of the designed multitope vaccine where suitable linkers were added to conjugate them. Additionally, beta defensin adjuvant and pan-HLA DR-binding epitope (PADRE) peptide were also incorporated into the construct to improve the stimulated immune response. The constructed multitope vaccine was analyzed for its physicochemical, structural and immunological characteristics and it was found to be antigenic, soluble, stable, non-allergenic and have a high affinity to its target receptor. Although the in silico analysis of the current study revealed that the designed multitope vaccine has the ability to trigger a specific immune response against M. catarrhalis, additional translational research is required to confirm the effectiveness of the designed vaccine.

scholarly journals In Vitro Anti-Tubulin Activity on MCF10A Cell Line and In Silico Rigid/Semiflexible-Residues Docking, of Two Lignans from Bursera Fagaroides var. Fagaroides

Molecules ◽  
2021 ◽  
Vol 26 (20) ◽  
pp. 6155
Author(s):  
Verónica Rodríguez-López ◽  
César Millán-Pacheco ◽  
Judith González-Christen ◽  
Maricruz Anaya-Ruíz ◽  
Omar Aristeo Peña-Morán
Keyword(s):  
Cell Line ◽  
In Silico ◽  
Topoisomerase Ii ◽  
In Silico Analysis ◽  
Stem Bark ◽  
Structural Basis ◽  
Mcf10a Cell ◽  
Binding Modes ◽  
In Silico Docking

Podophyllotoxins are natural lignans with known cytotoxic activity on several cell lines. The structural basis for their actions is mainly by the aryltetralin-lignan skeleton. Authors have proposed a cytotoxic mechanism of podophyllotoxins through the topoisomerase-II inhibition activity; however, several studies have also suggested that podophyllotoxins can inhibit the microtubules polymerization. In this work, the two possible mechanisms of action of two previously isolated compounds from the stem bark of Bursera fagaroides var. fagaroides: acetylpodophyllotoxin (1) and 5’-desmethoxydeoxypodophyllotoxin (2), was analyzed. An in vitro anti-tubulin epifluorescence on the MCF10A cell line and enzymatic topoisomerase II assays were performed. The binding affinities of compounds 1 and 2 in the colchicine binding site of tubulin by using rigid- and semiflexible-residues were calculated and compared using in silico docking methods. The two lignans were active by the in vitro anti-tubulin assay but could not inhibit TOP2 activity. In the in silico analysis, the binding modes of compounds into both rigid- and semiflexible-residues of tubulin were predicted, and only for the semiflexible docking method, a linear correlation between the dissociation constant and IC50 previously reported was found. Our results suggest that a simple semiflexible-residues modification in docking methods could provide an in vitro correlation when analyzing very structurally similar compounds.

scholarly journals An In-silico Deep Learning Approach to Multi-epitope Vaccine Design: A SARS-CoV-2 Case Study

2020 ◽  
Author(s):  
Zikun Yang ◽  
Paul Bogdan ◽  
Shahin Nazarian
Keyword(s):  
Deep Learning ◽  
T Lymphocytes ◽  
B Cell ◽  
In Silico ◽  
Vaccine Design ◽  
Learning Approach ◽  
Epitope Vaccine ◽  
B Cell Epitopes ◽  
Ctl Epitopes ◽  
The World

Abstract The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has led to over 6.5 million cases and more than 380,000 deaths, and devastated the social, financial and political entities around the world. Without an existing effective medical therapy, vaccines are urgently needed to avoid the spread of this disease. In this study, we propose an in-silico deep learning approach for prediction and design of a multi-epitope vaccine (Deep-Vac-Pred). By combining the in-silico immunotherapeutic and deep neural network strategies, the DeepVacPred computational framework directly predicts 26 potential vaccine subunits from the available SARS-CoV- 2 spike protein sequence. We further use in-silico methods to investigate the linear B-cell epitopes, Cytotoxic T Lymphocytes (CTL) epitopes, Helper T Lymphocytes (HTL) epitopes in the 26 subunit candidates and identify the best 11 of them to construct a multi-epitope vaccine for SARS-CoV-2 virus. The human population coverage, antigenicity, allergenicity, toxicity, physicochemical properties and secondary structure of the designed vaccine are evaluated via state-of-the-art bioinformatic approaches, showing good quality of the designed vaccine. The 3D structure of the designed vaccine is predicted, refined and validated by in-silico tools. Finally, we optimize and insert the codon sequence into a plasmid to ensure the cloning and expression efficiency. In conclusion, this proposed artificial intelligence vaccine discovery framework accelerates the vaccine design process and constructs a 694aa multi- epitope vaccine containing 16 B-cell epitopes, 82 CTL epitopes and 89 HTL epitopes, which is promising to fight the SARS-CoV-2 viral infection and can be further evaluated in clinical studies. Moreover, we trace the RNA mutations of the CoV and make sure our designed vaccine can tackle the recent RNA mutations of the virus.

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