COVID-19 Coronavirus Vaccine Design Using Reverse Vaccinology and Machine Learning

Abstract

To ultimately combat the emerging COVID-19 pandemic, it is desired to develop an effective and safe vaccine against this highly contagious disease caused by the SARS-CoV-2 coronavirus. Our literature and clinical trial survey showed that the whole virus, as well as the spike (S) protein, nucleocapsid (N) protein, and membrane (M) protein, have been tested for vaccine development against SARS and MERS. However, these vaccine candidates might lack the induction of complete protection and have safety concerns. We then applied the Vaxign and the newly developed machine learning-based Vaxign-ML reverse vaccinology tools to predict COVID-19 vaccine candidates. Our Vaxign analysis found that the SARS-CoV-2 N protein sequence is conserved with SARS-CoV and MERS-CoV but not from the other four human coronaviruses causing mild symptoms. By investigating the entire proteome of SARS-CoV-2, six proteins, including the S protein and five non-structural proteins (nsp3, 3CL-pro, and nsp8-10), were predicted to be adhesins, which are crucial to the viral adhering and host invasion. The S, nsp3, and nsp8 proteins were also predicted by Vaxign-ML to induce high protective antigenicity. Besides the commonly used S protein, the nsp3 protein has not been tested in any coronavirus vaccine studies and was selected for further investigation. The nsp3 was found to be more conserved among SARS-CoV-2, SARS-CoV, and MERS-CoV than among 15 coronaviruses infecting human and other animals. The protein was also predicted to contain promiscuous MHC-I and MHC-II T-cell epitopes, and the predicted linear B-cell epitopes were found to be localized on the surface of the protein. Our predicted vaccine targets have the potential for effective and safe COVID-19 vaccine development. We also propose that an "Sp/Nsp cocktail vaccine" containing a structural protein(s) (Sp) and a non-structural protein(s) (Nsp) would stimulate effective complementary immune responses.

Genome-wide analysis of Indian SARS-CoV-2 genomes to identify T-cell and B-cell epitopes from conserved regions based on immunogenicity and antigenicity

“…Also, as targets for prophylactic or therapeutic vaccines, the non-structural proteins of HIV-1 were shown to be quite important [53] . Moreover, Ong et al [25] have predicted NSP3 in SARS-CoV-2 to produce high protective antigenicity. Thus, we can hypothesize that apart from structural proteins non-structural proteins of SARS-CoV-2 can be possible targets as well for vaccine design which may induce cell-mediated or humoral immunity that is necessary to prevent viral invasion and/or replication.…”

“…Moreover, for the ease of the readers, all the details related to the 125 CCnRs, 92 MHC-I and MHC-II restricted T-cell epitopes and 61 B-cell epitopes are provided in the supplementary as an excel file , the link of which is given in Table S6. Additionally, a list of MHC-I and MHC-II restricted T-cell and B-cell epitopes for SARS-CoV-2 as collected from different sources in the literature like [26] , [27] , [17] , [28] , [16] , [15] , [20] , [24] , [23] , [29] , [30] , [31] , [32] , [33] , [25] are reported in Table 5 . For space constraint, 3 of each MHC-I and MHC-II restricted T-cell and B-cell epitopes from each paper are mentioned in this table while the list of all the MHC-I and MHC-II restricted T-cell and B-cell epitopes are given in the supplementary as an excel file as given in Table S6 .…”

“…On the other hand, Crooke et al [24] have used available algorithms and webtools to identify 41 T-cell epitopes (5 HLA class I, 36 HLA class II) and 6 B-cell epitopes as probable targets for epitope-based vaccine design. Ong et al [25] have used Vaxign and the recently developed Vaxign-ML reverse vaccinology tools to predict potential vaccine candidates for COVID-19. Apart from Spike, they have identified epitopes derived from NSP3, 3CL-pro, NSP8, NSP9 and NSP10 proteins to be highly likely candidates for vaccine design.…”

Systems Biology Approaches for Therapeutics Development Against COVID-19

“…The B-cell and Tcell epitopes of novel SARS-CoV-2 were analyzed by Ahmed et al by approaching IEDB and other computational tools (Grifoni et al, 2020). Ong et al (2020) reported the reverse vaccinology and machine learning approach were used to identify the potential vaccine candidate against COVID-19 infection (Ong et al, 2020). As reported by Chen and Wu (2020), ABCpred and BepiPred and IEDB are the epitope prediction tools used for the identification of epitopes in the novel SARS-CoV-2.…”

COVID-19 Pandemic Data Visualization with Moment about Midpoint: Exploratory and Expository Analyses

“…Some studies and interviews with some medical practitioners recently, have shown that the combination of hydroxychloroquine, azithromycin, Zinc sulphate and vitamin C have been proved effective both as preventive and curative measures for COVID-19 [36,37]. Also see [38,39,40] on conclusions on hydroxychloroquine and other drugs therapies in treating COVID-19.…”