Analysis of a Compound-Target Network of Oryeong-san (오령산 구성성분-타겟 네트워크 분석)

Kim Sang-Kyun (김상균)

doi:10.34163/jkits.2018.13.5.011

Analysis of a Compound-Target Network of Oryeong-san

Journal of Knowledge Information Technology and Systems
Abbr : JKITS
2018, 13(5), pp.607-614
DOI : 10.34163/jkits.2018.13.5.011
Publisher : Korea Knowledge Information Technology Society
Research Area : Interdisciplinary Studies > Interdisciplinary Research
Published : October 31, 2018

Kim Sang-Kyun ¹

¹한국한의학연구원

Accredited

ABSTRACT

Oryeong-san is a prescription widely used for diseases where water is stagnant because it has the effect of circulating the water in the body and releasing it into the urine. In order to investigate the mechanisms of oryeong-san, we in this paper construct and analysis the compound-target network of medicinal materials constituting oryeong-san based on a systems pharmacology approach. First, the targets related to the 475 chemical compounds of oryeong-san were searched in the STITCH database, and the search results for the interactions between compounds and targets were downloaded as XML files. The compound-target network of oryeong-san is visualized and explored using Gephi 0.8.2, which is an open-source software for graphs and networks. In the network, nodes are compounds and targets, and edges are interactions between the nodes. The edge is weighted according to the reliability of the interaction. In order to analysis the compound-target network, it is clustered using MCL algorithm, which is able to cluster the weighted network. A total of 130 clusters were created, and the number of nodes in the cluster with the largest number of nodes was 32. In the clustered network, it was revealed that the active compounds of medicinal materials were associated with the targets for regulating the blood pressure in the kidney. In the future, we will clarify the mechanisms of oryeong-san by linking the information on disease databases and the network of this research.

KEYWORDS

Oryeong-san, Compound-Target network, Clustering, TM-MC, MCL algorithm, Korean medicine

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* References for papers published after 2023 are currently being built.

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This paper was written with support from the National Research Foundation of Korea.

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Journal of Knowledge Information Technology and Systems 2023 KCI Impact Factor : 0.89

Analysis of a Compound-Target Network of Oryeong-san

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Citation status

* References for papers published after 2023 are currently being built.

Journal of Knowledge Information Technology and Systems 2023 KCI Impact Factor : 0.89

Analysis of a Compound-Target Network of Oryeong-san

ABSTRACT

KEYWORDS

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