Multi-omics-based identification of SARS-CoV-2 infection biology and candidate drugs against COVID-19
Open accessAbstract
SARS-CoV-2 has ushered a global pandemic with no effective drug being available at present. Although several FDA-approved drugs are currently under clinical trials for drug repositioning, there is an on-going global effort for new drug identification. In this paper, using multi-omics (interactome, proteome, transcriptome, and bibliome) data and subsequent integrated analysis, we present the biological events associated with SARS-CoV-2 infection and identify several candidate drugs against this viral disease. We found that: (i) Interactome-based infection pathways differ from the other three omics-based profiles. (ii) Viral process, mRNA splicing, cytokine and interferon signaling, and ubiquitin mediated proteolysis are important pathways in SARS-CoV-2 infection. (iii) SARS-CoV-2 infection also shares pathways with Influenza A, Epstein-Barr virus, HTLV-I, Measles, and Hepatitis virus. (iv) Further, bacterial, parasitic, and protozoan infection pathways such as Tuberculosis, Malaria, and Leishmaniasis are also shared by this virus. (v) A total of 50 candidate drugs, including the prophylaxis agents and pathway specific inhibitors are identified against COVID-19. (vi) Betamethasone, Estrogen, Simvastatin, Hydrocortisone, Tositumomab, Cyclosporin A etc. are among the important drugs. (vii) Ozone, Nitric oxide, plasma components, and photosensitizer drugs are also identified as possible therapeutic candidates. (viii) Curcumin, Retinoic acids, Vitamin D, Arsenic, Copper, and Zinc may be the candidate prophylaxis agents. Nearly 70% of our identified agents are previously suggested to have anti-COVID-19 effects or under clinical trials. Among our identified drugs, the ones that are not yet tested, need validation with caution while an appropriate drug combination from these candidate drugs along with a SARS-CoV-2 specific antiviral agent is needed for effective COVID-19 management.
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Omics data have recently been integrated in COVID-19 research.
“Recently, these omics have also been integrated for COVID-19 studies (Barh et al., 2020;Overmyer et al., 2020;Zhou et al., 2020).”
From Using machine learning approaches for multi-omics data analysis: A review (2021) · cites this paper as Barh et al., 2020
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- Authors
- Barh, D., Tiwari, S., Weener, M. E., Azevedo, V., Góes-Neto, A., Gromiha, M. M., & Ghosh, P.
- Affiliations
- Universidade Federal de Minas Gerais (BR)
- Indian Institute of Technology Madras (IN)
- Virginia Commonwealth University (US)
- Corresponding author
- Barh, Debmalya
- ORCID
- Venue
- Computers in Biology and Medicine
- Publisher
- Elsevier BV
- Published
- 2020-11
- Volume
- 126
- Pages
- 104051
- ISSN
- 0010-4825 (ISSN-L)
- PMC
- PMC7547373
- OpenAlex
- W3091948906
- Cited by
- 90
- References
- 82
- Citations by year
- 2025: 9 · 2024: 8 · 2023: 11 · 2022: 28 · 2021: 29 · 2020: 5
- FWCI
- 2.39
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Computers in Biology and Medicine (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- SARS-CoV-2, COVID-19 pandemic, drug repurposing, drug candidates, protein-protein interaction network, proteome, transcriptome, mRNA splicing, ubiquitin-mediated proteolysis, curcumin, retinoic acid, trace elements, drug combination therapy
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Antiviral Agents, Humans, Models, Biological, Pneumonia, Viral, Coronavirus Infections, Databases, Genetic, Proteomics, Drug Discovery, Pandemics
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