COVID 19 coronavirus vaccine design using reverse vaccinology and machine learning
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 protein, have been tested for vaccine development against SARS and MERS. We further used the Vaxign reverse vaccinology tool and the newly developed Vaxign ML machine learning tool to predict COVID 19 vaccine candidates. The N protein was found to be conserved in the more pathogenic strains (SARS/MERS/COVID 19) but not in the other human coronaviruses that mostly cause 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 linear B cell epitopes localized in specific locations and functional domains of the protein. Our predicted vaccine targets provide new strategies for effective and safe COVID 19 vaccine development.
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