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Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments

The coronavirus disease 2019 (COVID-19) pandemic has caused a dramatic loss of human life and devastated the worldwide economy. Numerous efforts have been made to mitigate COVID-19 symptoms and reduce the death rate. We conducted literature mining of more than 250 thousand published works and curate...

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Autores principales: Dai, Yulin, Yu, Hui, Yan, Qiheng, Li, Bingrui, Liu, Andi, Liu, Wendao, Jiang, Xiaoqian, Kim, Yejin, Guo, Yan, Zhao, Zhongming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9316565/
https://www.ncbi.nlm.nih.gov/pubmed/35885993
http://dx.doi.org/10.3390/genes13071210
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author Dai, Yulin
Yu, Hui
Yan, Qiheng
Li, Bingrui
Liu, Andi
Liu, Wendao
Jiang, Xiaoqian
Kim, Yejin
Guo, Yan
Zhao, Zhongming
author_facet Dai, Yulin
Yu, Hui
Yan, Qiheng
Li, Bingrui
Liu, Andi
Liu, Wendao
Jiang, Xiaoqian
Kim, Yejin
Guo, Yan
Zhao, Zhongming
author_sort Dai, Yulin
collection PubMed
description The coronavirus disease 2019 (COVID-19) pandemic has caused a dramatic loss of human life and devastated the worldwide economy. Numerous efforts have been made to mitigate COVID-19 symptoms and reduce the death rate. We conducted literature mining of more than 250 thousand published works and curated the 174 most widely used COVID-19 medications. Overlaid with the human protein–protein interaction (PPI) network, we used Steiner tree analysis to extract a core subnetwork that grew from the pharmacological targets of ten credible drugs ascertained by the CTD database. The resultant core subnetwork consisted of 34 interconnected genes, which were associated with 36 drugs. Immune cell membrane receptors, the downstream cellular signaling cascade, and severe COVID-19 symptom risk were significantly enriched for the core subnetwork genes. The lung mast cell was most enriched for the target genes among 1355 human tissue-cell types. Human bronchoalveolar lavage fluid COVID-19 single-cell RNA-Seq data highlighted the fact that T cells and macrophages have the most overlapping genes from the core subnetwork. Overall, we constructed an actionable human target-protein module that mainly involved anti-inflammatory/antiviral entry functions and highly overlapped with COVID-19-severity-related genes. Our findings could serve as a knowledge base for guiding drug discovery or drug repurposing to confront the fast-evolving SARS-CoV-2 virus and other severe infectious diseases.
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spelling pubmed-93165652022-07-27 Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments Dai, Yulin Yu, Hui Yan, Qiheng Li, Bingrui Liu, Andi Liu, Wendao Jiang, Xiaoqian Kim, Yejin Guo, Yan Zhao, Zhongming Genes (Basel) Article The coronavirus disease 2019 (COVID-19) pandemic has caused a dramatic loss of human life and devastated the worldwide economy. Numerous efforts have been made to mitigate COVID-19 symptoms and reduce the death rate. We conducted literature mining of more than 250 thousand published works and curated the 174 most widely used COVID-19 medications. Overlaid with the human protein–protein interaction (PPI) network, we used Steiner tree analysis to extract a core subnetwork that grew from the pharmacological targets of ten credible drugs ascertained by the CTD database. The resultant core subnetwork consisted of 34 interconnected genes, which were associated with 36 drugs. Immune cell membrane receptors, the downstream cellular signaling cascade, and severe COVID-19 symptom risk were significantly enriched for the core subnetwork genes. The lung mast cell was most enriched for the target genes among 1355 human tissue-cell types. Human bronchoalveolar lavage fluid COVID-19 single-cell RNA-Seq data highlighted the fact that T cells and macrophages have the most overlapping genes from the core subnetwork. Overall, we constructed an actionable human target-protein module that mainly involved anti-inflammatory/antiviral entry functions and highly overlapped with COVID-19-severity-related genes. Our findings could serve as a knowledge base for guiding drug discovery or drug repurposing to confront the fast-evolving SARS-CoV-2 virus and other severe infectious diseases. MDPI 2022-07-06 /pmc/articles/PMC9316565/ /pubmed/35885993 http://dx.doi.org/10.3390/genes13071210 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Dai, Yulin
Yu, Hui
Yan, Qiheng
Li, Bingrui
Liu, Andi
Liu, Wendao
Jiang, Xiaoqian
Kim, Yejin
Guo, Yan
Zhao, Zhongming
Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments
title Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments
title_full Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments
title_fullStr Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments
title_full_unstemmed Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments
title_short Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments
title_sort drug-target network study reveals the core target-protein interactions of various covid-19 treatments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9316565/
https://www.ncbi.nlm.nih.gov/pubmed/35885993
http://dx.doi.org/10.3390/genes13071210
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