Version 1
: Received: 26 March 2020 / Approved: 29 March 2020 / Online: 29 March 2020 (01:58:40 CET)
How to cite:
Liu, Y.; Chan, W.K.; Wang, Z.; Hur, J.; Xie, J.; Yu, H.; He, Y. Ontological and Bioinformatic Analysis of Anti-Coronavirus Drugs and Their Implication for Drug Repurposing against COVID-19. Preprints2020, 2020030413. https://doi.org/10.20944/preprints202003.0413.v1
Liu, Y.; Chan, W.K.; Wang, Z.; Hur, J.; Xie, J.; Yu, H.; He, Y. Ontological and Bioinformatic Analysis of Anti-Coronavirus Drugs and Their Implication for Drug Repurposing against COVID-19. Preprints 2020, 2020030413. https://doi.org/10.20944/preprints202003.0413.v1
Liu, Y.; Chan, W.K.; Wang, Z.; Hur, J.; Xie, J.; Yu, H.; He, Y. Ontological and Bioinformatic Analysis of Anti-Coronavirus Drugs and Their Implication for Drug Repurposing against COVID-19. Preprints2020, 2020030413. https://doi.org/10.20944/preprints202003.0413.v1
APA Style
Liu, Y., Chan, W.K., Wang, Z., Hur, J., Xie, J., Yu, H., & He, Y. (2020). Ontological and Bioinformatic Analysis of Anti-Coronavirus Drugs and Their Implication for Drug Repurposing against COVID-19. Preprints. https://doi.org/10.20944/preprints202003.0413.v1
Chicago/Turabian Style
Liu, Y., Hong Yu and Yongqun He. 2020 "Ontological and Bioinformatic Analysis of Anti-Coronavirus Drugs and Their Implication for Drug Repurposing against COVID-19" Preprints. https://doi.org/10.20944/preprints202003.0413.v1
Abstract
Coronavirus-infected diseases have posed great threats to human health. In past years, highly infectious coronavirus-induced diseases, including COVID-19, SARS, and MERS, have resulted in world-wide severe infections. Our literature annotations identified 110 chemical drugs and 26 antibodies effective against at least one human coronavirus infection in vitro or in vivo. Many of these drugs inhibit viral entry to cells and viral replication inside cells or modulate host immune responses. Many antimicrobial drugs, including antimalarial (e.g., chloroquine and mefloquine) and antifungal (e.g., terconazole and rapamycin) drugs as well as antibiotics (e.g., teicoplanin and azithromycin) were associated with anti-coronavirus activity. A few drugs, including remdesivir, chloroquine, favipiravir, and tocilizumab, have already been reported to be effective against SARS-CoV-2 infection in vitro or in vivo. After mapping our identified drugs to three ontologies ChEBI, NDF-RT, and DrON, many features such as roles and mechanisms of action (MoAs) of these drugs were identified and categorized. For example, out of 57 drugs with MoA annotations in NDF-RT, 47 have MoAs of different types of inhibitors and antagonists. A total of 29 anticoronaviral drugs are anticancer drugs with the antineoplastic role. Two clustering analyses, one based on ChEBI-based semantic similarity, the other based on drug chemical similarity, were performed to cluster 110 drugs to new categories. Moreover, differences in physicochemical properties among the drugs were found between those inhibiting viral entry and viral replication. A total of 163 host genes were identified as the known targets of 68 anti-coronavirus drugs, resulting in a network of 428 interactions among these drugs and targets. Chlorpromazine, dasatinib, and anisomycin are the hubs of the drug-target network with the highest number of connected target proteins. Many enriched pathways such as calcium signaling and neuroactive ligand-receptor interaction pathways were identified. These findings may be used to facilitate drug repurposing against COVID-19.
Medicine and Pharmacology, Pharmacology and Toxicology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter's Conflict of Interests:
I am the corresponding author of both the preprint paper and the journal article that I introduced.
Comment:
A Scientific Data journal article has been published on 13 January 2021 that extends this preprint work: https://www.nature.com/articles/s41597-021-00799-w
Title: Ontological modeling and analysis of experimentally or clinically verified drugs against coronavirus infection
Commenter:
Commenter's Conflict of Interests: I am the corresponding author of both the preprint paper and the journal article that I introduced.
https://www.nature.com/articles/s41597-021-00799-w
Title: Ontological modeling and analysis of experimentally or clinically verified drugs against coronavirus infection