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| Title |
COVID-19 Coronavirus Vaccine Design Using Reverse Vaccinology and Machine Learning
|
|---|---|
| Published in |
Frontiers in immunology, July 2020
|
| DOI | 10.3389/fimmu.2020.01581 |
| Pubmed ID | |
| Authors |
Edison Ong, Mei U Wong, Anthony Huffman, Yongqun He |
| 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. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 6% |
| Japan | 2 | 6% |
| India | 1 | 3% |
| South Africa | 1 | 3% |
| Portugal | 1 | 3% |
| Unknown | 24 | 77% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 28 | 90% |
| Scientists | 1 | 3% |
| Practitioners (doctors, other healthcare professionals) | 1 | 3% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 760 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 760 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 98 | 13% |
| Researcher | 86 | 11% |
| Student > Master | 74 | 10% |
| Student > Ph. D. Student | 60 | 8% |
| Other | 36 | 5% |
| Other | 127 | 17% |
| Unknown | 279 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 87 | 11% |
| Medicine and Dentistry | 74 | 10% |
| Computer Science | 55 | 7% |
| Immunology and Microbiology | 33 | 4% |
| Agricultural and Biological Sciences | 31 | 4% |
| Other | 179 | 24% |
| Unknown | 301 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 June 2023.
All research outputs
#2,077,036
of 26,409,992 outputs
Outputs from Frontiers in immunology
#2,037
of 33,162 outputs
Outputs of similar age
#55,823
of 435,469 outputs
Outputs of similar age from Frontiers in immunology
#77
of 763 outputs
Altmetric has tracked 26,409,992 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 33,162 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 435,469 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 763 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.