This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research Article
Claudia Cava
Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate-Milan, Milan, Italy
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5540-4104
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Severe acute respiratory syndrome coronavirus (SARS-CoV-2), an emerging Betacoronavirus, is the causative agent of COVID-19. Angiotensin converting enzyme 2 (ACE2), being the main cell receptor of SARS-CoV-2, plays a role in the entry of the virus into the cell. Currently, there are no specific antiviral drugs for the treatment and neither preventive drugs such as vaccines.
Results: We proposed a bioinformatics analysis in order to test in silico existing drugs as a fast way to identify an efficient therapy. We found differentially expressed genes in COVID-19 patients correlated with ACE-2 and we explored their direct relations with a network approach.
Conclusions: In this network we integrated drug-gene interactions and we proposed several drugs with antiviral activity that, alone or in combination with other treatment options, could be considered as therapeutic approaches against COVID-19.
Keywords
COVID-19, SARS-CoV-2, drug, network, in-silico
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research Article
Claudia Cava
Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090 Segrate-Milan, Milan, Italy
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5540-4104
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 10 Jun, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Severe acute respiratory syndrome coronavirus (SARS-CoV-2), an emerging Betacoronavirus, is the causative agent of COVID-19. Angiotensin converting enzyme 2 (ACE2), being the main cell receptor of SARS-CoV-2, plays a role in the entry of the virus into the cell. Currently, there are no specific antiviral drugs for the treatment and neither preventive drugs such as vaccines.
Results: We proposed a bioinformatics analysis in order to test in silico existing drugs as a fast way to identify an efficient therapy. We found differentially expressed genes in COVID-19 patients correlated with ACE-2 and we explored their direct relations with a network approach.
Conclusions: In this network we integrated drug-gene interactions and we proposed several drugs with antiviral activity that, alone or in combination with other treatment options, could be considered as therapeutic approaches against COVID-19.
Figure 1
Figure 2
Figure 3
Figure 4
This is a list of supplementary files associated with this preprint. Click to download.
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