Agent Clustering Strategy Based on Metabolic Flux Distribution and Transcriptome Expression for Novel Drug Development

The network module-based method has been used for drug repositioning. The traditional drug repositioning method only uses the gene characteristics of the drug but ignores the drug-triggered metabolic changes. The metabolic network systematically characterizes the connection between genes, proteins,...

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Autores principales:	Yao Ruan, Xiao-Hui Chen, Feng Jiang, Yan-Guang Liu, Xiao-Long Liang, Bo-Min Lv, Hong-Yu Zhang, Qing-Ye Zhang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	drug repositioning genome-scale metabolic models connectivity map MoA Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/ed57e0165d7141c3aeb66d734c476bdd
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spelling	oai:doaj.org-article:ed57e0165d7141c3aeb66d734c476bdd2021-11-25T16:49:59ZAgent Clustering Strategy Based on Metabolic Flux Distribution and Transcriptome Expression for Novel Drug Development10.3390/biomedicines91116402227-9059https://doaj.org/article/ed57e0165d7141c3aeb66d734c476bdd2021-11-01T00:00:00Zhttps://www.mdpi.com/2227-9059/9/11/1640https://doaj.org/toc/2227-9059The network module-based method has been used for drug repositioning. The traditional drug repositioning method only uses the gene characteristics of the drug but ignores the drug-triggered metabolic changes. The metabolic network systematically characterizes the connection between genes, proteins, and metabolic reactions. The differential metabolic flux distribution, as drug metabolism characteristics, was employed to cluster the agents with similar MoAs (mechanism of action). In this study, agents with the same pharmacology were clustered into one group, and a total of 1309 agents from the CMap database were clustered into 98 groups based on differential metabolic flux distribution. Transcription factor (TF) enrichment analysis revealed the agents in the same group (such as group 7 and group 26) were confirmed to have similar MoAs. Through this agent clustering strategy, the candidate drugs which can inhibit (Japanese encephalitis virus) JEV infection were identified. This study provides new insights into drug repositioning and their MoAs.Yao RuanXiao-Hui ChenFeng JiangYan-Guang LiuXiao-Long LiangBo-Min LvHong-Yu ZhangQing-Ye ZhangMDPI AGarticledrug repositioninggenome-scale metabolic modelsconnectivity mapMoABiology (General)QH301-705.5ENBiomedicines, Vol 9, Iss 1640, p 1640 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	drug repositioning genome-scale metabolic models connectivity map MoA Biology (General) QH301-705.5
spellingShingle	drug repositioning genome-scale metabolic models connectivity map MoA Biology (General) QH301-705.5 Yao Ruan Xiao-Hui Chen Feng Jiang Yan-Guang Liu Xiao-Long Liang Bo-Min Lv Hong-Yu Zhang Qing-Ye Zhang Agent Clustering Strategy Based on Metabolic Flux Distribution and Transcriptome Expression for Novel Drug Development
description	The network module-based method has been used for drug repositioning. The traditional drug repositioning method only uses the gene characteristics of the drug but ignores the drug-triggered metabolic changes. The metabolic network systematically characterizes the connection between genes, proteins, and metabolic reactions. The differential metabolic flux distribution, as drug metabolism characteristics, was employed to cluster the agents with similar MoAs (mechanism of action). In this study, agents with the same pharmacology were clustered into one group, and a total of 1309 agents from the CMap database were clustered into 98 groups based on differential metabolic flux distribution. Transcription factor (TF) enrichment analysis revealed the agents in the same group (such as group 7 and group 26) were confirmed to have similar MoAs. Through this agent clustering strategy, the candidate drugs which can inhibit (Japanese encephalitis virus) JEV infection were identified. This study provides new insights into drug repositioning and their MoAs.
format	article
author	Yao Ruan Xiao-Hui Chen Feng Jiang Yan-Guang Liu Xiao-Long Liang Bo-Min Lv Hong-Yu Zhang Qing-Ye Zhang
author_facet	Yao Ruan Xiao-Hui Chen Feng Jiang Yan-Guang Liu Xiao-Long Liang Bo-Min Lv Hong-Yu Zhang Qing-Ye Zhang
author_sort	Yao Ruan
title	Agent Clustering Strategy Based on Metabolic Flux Distribution and Transcriptome Expression for Novel Drug Development
title_short	Agent Clustering Strategy Based on Metabolic Flux Distribution and Transcriptome Expression for Novel Drug Development
title_full	Agent Clustering Strategy Based on Metabolic Flux Distribution and Transcriptome Expression for Novel Drug Development
title_fullStr	Agent Clustering Strategy Based on Metabolic Flux Distribution and Transcriptome Expression for Novel Drug Development
title_full_unstemmed	Agent Clustering Strategy Based on Metabolic Flux Distribution and Transcriptome Expression for Novel Drug Development
title_sort	agent clustering strategy based on metabolic flux distribution and transcriptome expression for novel drug development
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/ed57e0165d7141c3aeb66d734c476bdd
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_version_	1718412931042902016

Agent Clustering Strategy Based on Metabolic Flux Distribution and Transcriptome Expression for Novel Drug Development

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