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A protein interaction map identifies existing drugs targeting SARS-CoV-2.
BMC Pharmacol Toxicol. 2020 09 03; 21(1):65.BP

Abstract

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 neither specific antiviral drugs for the treatment or preventive drugs such as vaccines.

METHODS

We proposed a bioinformatics analysis to test in silico existing drugs as a fast way to identify an efficient therapy. We performed a differential expression analysis in order to identify differentially expressed genes in COVID-19 patients correlated with ACE-2 and we explored their direct relations with a network approach integrating also drug-gene interactions. The drugs with a central role in the network were also investigated with a molecular docking analysis.

RESULTS

We found 825 differentially expressed genes correlated with ACE2. The protein-protein interactions among differentially expressed genes identified a network of 474 genes and 1130 interactions.

CONCLUSIONS

The integration of drug-gene interactions in the network and molecular docking analysis allows us to obtain several drugs with antiviral activity that, alone or in combination with other treatment options, could be considered as therapeutic approaches against COVID-19.

Authors+Show Affiliations

Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, 20090 Segrate-Milan, Milan, Italy. claudia.cava@ibfm.cnr.it.Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, 20090 Segrate-Milan, Milan, Italy.Department of Physics "Giuseppe Occhialini", University of Milan-Bicocca Piazza dell'Ateneo Nuovo, 1 - 20126, Milan, Italy.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

32883368

Citation

Cava, Claudia, et al. "A Protein Interaction Map Identifies Existing Drugs Targeting SARS-CoV-2." BMC Pharmacology & Toxicology, vol. 21, no. 1, 2020, p. 65.
Cava C, Bertoli G, Castiglioni I. A protein interaction map identifies existing drugs targeting SARS-CoV-2. BMC Pharmacol Toxicol. 2020;21(1):65.
Cava, C., Bertoli, G., & Castiglioni, I. (2020). A protein interaction map identifies existing drugs targeting SARS-CoV-2. BMC Pharmacology & Toxicology, 21(1), 65. https://doi.org/10.1186/s40360-020-00444-z
Cava C, Bertoli G, Castiglioni I. A Protein Interaction Map Identifies Existing Drugs Targeting SARS-CoV-2. BMC Pharmacol Toxicol. 2020 09 3;21(1):65. PubMed PMID: 32883368.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - A protein interaction map identifies existing drugs targeting SARS-CoV-2. AU - Cava,Claudia, AU - Bertoli,Gloria, AU - Castiglioni,Isabella, Y1 - 2020/09/03/ PY - 2020/05/15/received PY - 2020/08/25/accepted PY - 2020/9/5/entrez PY - 2020/9/5/pubmed PY - 2020/9/20/medline KW - COVID-19 KW - Drug KW - In silico analysis KW - Molecular docking KW - Network KW - SARS-CoV-2 SP - 65 EP - 65 JF - BMC pharmacology & toxicology JO - BMC Pharmacol Toxicol VL - 21 IS - 1 N2 - 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 neither specific antiviral drugs for the treatment or preventive drugs such as vaccines. METHODS: We proposed a bioinformatics analysis to test in silico existing drugs as a fast way to identify an efficient therapy. We performed a differential expression analysis in order to identify differentially expressed genes in COVID-19 patients correlated with ACE-2 and we explored their direct relations with a network approach integrating also drug-gene interactions. The drugs with a central role in the network were also investigated with a molecular docking analysis. RESULTS: We found 825 differentially expressed genes correlated with ACE2. The protein-protein interactions among differentially expressed genes identified a network of 474 genes and 1130 interactions. CONCLUSIONS: The integration of drug-gene interactions in the network and molecular docking analysis allows us to obtain several drugs with antiviral activity that, alone or in combination with other treatment options, could be considered as therapeutic approaches against COVID-19. SN - 2050-6511 UR - https://www.unboundmedicine.com/medline/citation/32883368/A_protein_interaction_map_identifies_existing_drugs_targeting_SARS_CoV_2_ L2 - https://bmcpharmacoltoxicol.biomedcentral.com/articles/10.1186/s40360-020-00444-z DB - PRIME DP - Unbound Medicine ER -