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Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics
Since coronavirus disease 2019 (COVID-19) is a serious new worldwide public health crisis with significant morbidity and mortality, effective therapeutic treatments are urgently needed. Drug repurposing is an efficient and cost-effective strategy with minimum risk for identifying novel potential tre...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8069812/ https://www.ncbi.nlm.nih.gov/pubmed/33919660 http://dx.doi.org/10.3390/pharmaceutics13040545 |
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author | Liu, Dan-Yang Liu, Jia-Chen Liang, Shuang Meng, Xiang-He Greenbaum, Jonathan Xiao, Hong-Mei Tan, Li-Jun Deng, Hong-Wen |
author_facet | Liu, Dan-Yang Liu, Jia-Chen Liang, Shuang Meng, Xiang-He Greenbaum, Jonathan Xiao, Hong-Mei Tan, Li-Jun Deng, Hong-Wen |
author_sort | Liu, Dan-Yang |
collection | PubMed |
description | Since coronavirus disease 2019 (COVID-19) is a serious new worldwide public health crisis with significant morbidity and mortality, effective therapeutic treatments are urgently needed. Drug repurposing is an efficient and cost-effective strategy with minimum risk for identifying novel potential treatment options by repositioning therapies that were previously approved for other clinical outcomes. Here, we used an integrated network-based pharmacologic and transcriptomic approach to screen drug candidates novel for COVID-19 treatment. Network-based proximity scores were calculated to identify the drug–disease pharmacological effect between drug–target relationship modules and COVID-19 related genes. Gene set enrichment analysis (GSEA) was then performed to determine whether drug candidates influence the expression of COVID-19 related genes and examine the sensitivity of the repurposing drug treatment to peripheral immune cell types. Moreover, we used the complementary exposure model to recommend potential synergistic drug combinations. We identified 18 individual drug candidates including nicardipine, orantinib, tipifarnib and promethazine which have not previously been proposed as possible treatments for COVID-19. Additionally, 30 synergistic drug pairs were ultimately recommended including fostamatinib plus tretinoin and orantinib plus valproic acid. Differential expression genes of most repurposing drugs were enriched significantly in B cells. The findings may potentially accelerate the discovery and establishment of an effective therapeutic treatment plan for COVID-19 patients. |
format | Online Article Text |
id | pubmed-8069812 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80698122021-04-26 Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics Liu, Dan-Yang Liu, Jia-Chen Liang, Shuang Meng, Xiang-He Greenbaum, Jonathan Xiao, Hong-Mei Tan, Li-Jun Deng, Hong-Wen Pharmaceutics Article Since coronavirus disease 2019 (COVID-19) is a serious new worldwide public health crisis with significant morbidity and mortality, effective therapeutic treatments are urgently needed. Drug repurposing is an efficient and cost-effective strategy with minimum risk for identifying novel potential treatment options by repositioning therapies that were previously approved for other clinical outcomes. Here, we used an integrated network-based pharmacologic and transcriptomic approach to screen drug candidates novel for COVID-19 treatment. Network-based proximity scores were calculated to identify the drug–disease pharmacological effect between drug–target relationship modules and COVID-19 related genes. Gene set enrichment analysis (GSEA) was then performed to determine whether drug candidates influence the expression of COVID-19 related genes and examine the sensitivity of the repurposing drug treatment to peripheral immune cell types. Moreover, we used the complementary exposure model to recommend potential synergistic drug combinations. We identified 18 individual drug candidates including nicardipine, orantinib, tipifarnib and promethazine which have not previously been proposed as possible treatments for COVID-19. Additionally, 30 synergistic drug pairs were ultimately recommended including fostamatinib plus tretinoin and orantinib plus valproic acid. Differential expression genes of most repurposing drugs were enriched significantly in B cells. The findings may potentially accelerate the discovery and establishment of an effective therapeutic treatment plan for COVID-19 patients. MDPI 2021-04-14 /pmc/articles/PMC8069812/ /pubmed/33919660 http://dx.doi.org/10.3390/pharmaceutics13040545 Text en © 2021 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 Liu, Dan-Yang Liu, Jia-Chen Liang, Shuang Meng, Xiang-He Greenbaum, Jonathan Xiao, Hong-Mei Tan, Li-Jun Deng, Hong-Wen Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics |
title | Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics |
title_full | Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics |
title_fullStr | Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics |
title_full_unstemmed | Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics |
title_short | Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics |
title_sort | drug repurposing for covid-19 treatment by integrating network pharmacology and transcriptomics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8069812/ https://www.ncbi.nlm.nih.gov/pubmed/33919660 http://dx.doi.org/10.3390/pharmaceutics13040545 |
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