Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network
Network-based methods for the analysis of drug-target interactions have gained attention and rely on the paradigm that a single drug can act on multiple targets rather than a single target. In this study, we have presented a novel approach to analyze the interactions between the chemicals in the med...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Biomolecules |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2218-273X/11/4/546 |
| _version_ | 1797538370479456256 |
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| author | Namgil Lee Hojin Yoo Heejung Yang |
| author_facet | Namgil Lee Hojin Yoo Heejung Yang |
| author_sort | Namgil Lee |
| collection | DOAJ |
| description | Network-based methods for the analysis of drug-target interactions have gained attention and rely on the paradigm that a single drug can act on multiple targets rather than a single target. In this study, we have presented a novel approach to analyze the interactions between the chemicals in the medicinal plants and multiple targets based on the complex multipartite network of the medicinal plants, multi-chemicals, and multiple targets. The multipartite network was constructed via the conjunction of two relationships: chemicals in plants and the biological actions of those chemicals on the targets. In doing so, we introduced an index of the efficacy of chemicals in a plant on a protein target of interest, called target potency score (TPS). We showed that the analysis can identify specific chemical profiles from each group of plants, which can then be employed for discovering new alternative therapeutic agents. Furthermore, specific clusters of plants and chemicals acting on specific targets were retrieved using TPS that suggested potential drug candidates with high probability of clinical success. We expect that this approach may open a way to predict the biological functions of multi-chemicals and multi-plants on the targets of interest and enable repositioning of the plants and chemicals. |
| first_indexed | 2024-03-10T12:29:36Z |
| format | Article |
| id | doaj.art-11a6edf4a6894e6abb3346a689881947 |
| institution | Directory Open Access Journal |
| issn | 2218-273X |
| language | English |
| last_indexed | 2024-03-10T12:29:36Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomolecules |
| spelling | doaj.art-11a6edf4a6894e6abb3346a6898819472023-11-21T14:42:22ZengMDPI AGBiomolecules2218-273X2021-04-0111454610.3390/biom11040546Cluster Analysis of Medicinal Plants and Targets Based on Multipartite NetworkNamgil Lee0Hojin Yoo1Heejung Yang2Department of Information Statistics, Kangwon National University, Chuncheon 24341, KoreaBionsight, Incorporated, Chuncheon 24341, KoreaBionsight, Incorporated, Chuncheon 24341, KoreaNetwork-based methods for the analysis of drug-target interactions have gained attention and rely on the paradigm that a single drug can act on multiple targets rather than a single target. In this study, we have presented a novel approach to analyze the interactions between the chemicals in the medicinal plants and multiple targets based on the complex multipartite network of the medicinal plants, multi-chemicals, and multiple targets. The multipartite network was constructed via the conjunction of two relationships: chemicals in plants and the biological actions of those chemicals on the targets. In doing so, we introduced an index of the efficacy of chemicals in a plant on a protein target of interest, called target potency score (TPS). We showed that the analysis can identify specific chemical profiles from each group of plants, which can then be employed for discovering new alternative therapeutic agents. Furthermore, specific clusters of plants and chemicals acting on specific targets were retrieved using TPS that suggested potential drug candidates with high probability of clinical success. We expect that this approach may open a way to predict the biological functions of multi-chemicals and multi-plants on the targets of interest and enable repositioning of the plants and chemicals.https://www.mdpi.com/2218-273X/11/4/546medicinal plantsmulti-chemicalsmulti-targetsmultipartite networknetwork analysis |
| spellingShingle | Namgil Lee Hojin Yoo Heejung Yang Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network Biomolecules medicinal plants multi-chemicals multi-targets multipartite network network analysis |
| title | Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network |
| title_full | Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network |
| title_fullStr | Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network |
| title_full_unstemmed | Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network |
| title_short | Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network |
| title_sort | cluster analysis of medicinal plants and targets based on multipartite network |
| topic | medicinal plants multi-chemicals multi-targets multipartite network network analysis |
| url | https://www.mdpi.com/2218-273X/11/4/546 |
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