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Comprehensive survey of target prediction web servers for Traditional Chinese Medicine
Traditional Chinese medicine (TCM) is characterized by multi-components, multiple targets, and complex mechanisms of action and therefore has significant advantages in treating diseases. However, the clinical application of TCM prescriptions is limited due to the difficulty in elucidating the effect...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10468387/ https://www.ncbi.nlm.nih.gov/pubmed/37664753 http://dx.doi.org/10.1016/j.heliyon.2023.e19151 |
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author | Ren, Xia Yan, Chun-Xiao Zhai, Run-Xiang Xu, Kuo Li, Hui Fu, Xian-Jun |
author_facet | Ren, Xia Yan, Chun-Xiao Zhai, Run-Xiang Xu, Kuo Li, Hui Fu, Xian-Jun |
author_sort | Ren, Xia |
collection | PubMed |
description | Traditional Chinese medicine (TCM) is characterized by multi-components, multiple targets, and complex mechanisms of action and therefore has significant advantages in treating diseases. However, the clinical application of TCM prescriptions is limited due to the difficulty in elucidating the effective substances and the lack of current scientific evidence on the mechanisms of action. In recent years, the development of network pharmacology based on drug systems research has provided a new approach for understanding the complex systems represented by TCM. The determination of drug targets is the core of TCM network pharmacology research. Over the past years, many web tools for drug targets with various features have been developed to facilitate target prediction, significantly promoting drug discovery. Therefore, this review introduces the widely used web tools for compound-target interaction prediction databases and web resources in TCM pharmacology research, and it compares and analyzes each web tool based on their basic properties, including the underlying theory, algorithms, datasets, and search results. Finally, we present the remaining challenges for the promising future of compound-target interaction prediction in TCM pharmacology research. This work may guide researchers in choosing web tools for target prediction and may also help develop more TCM tools based on these existing resources. |
format | Online Article Text |
id | pubmed-10468387 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-104683872023-09-01 Comprehensive survey of target prediction web servers for Traditional Chinese Medicine Ren, Xia Yan, Chun-Xiao Zhai, Run-Xiang Xu, Kuo Li, Hui Fu, Xian-Jun Heliyon Review Article Traditional Chinese medicine (TCM) is characterized by multi-components, multiple targets, and complex mechanisms of action and therefore has significant advantages in treating diseases. However, the clinical application of TCM prescriptions is limited due to the difficulty in elucidating the effective substances and the lack of current scientific evidence on the mechanisms of action. In recent years, the development of network pharmacology based on drug systems research has provided a new approach for understanding the complex systems represented by TCM. The determination of drug targets is the core of TCM network pharmacology research. Over the past years, many web tools for drug targets with various features have been developed to facilitate target prediction, significantly promoting drug discovery. Therefore, this review introduces the widely used web tools for compound-target interaction prediction databases and web resources in TCM pharmacology research, and it compares and analyzes each web tool based on their basic properties, including the underlying theory, algorithms, datasets, and search results. Finally, we present the remaining challenges for the promising future of compound-target interaction prediction in TCM pharmacology research. This work may guide researchers in choosing web tools for target prediction and may also help develop more TCM tools based on these existing resources. Elsevier 2023-08-15 /pmc/articles/PMC10468387/ /pubmed/37664753 http://dx.doi.org/10.1016/j.heliyon.2023.e19151 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Article Ren, Xia Yan, Chun-Xiao Zhai, Run-Xiang Xu, Kuo Li, Hui Fu, Xian-Jun Comprehensive survey of target prediction web servers for Traditional Chinese Medicine |
title | Comprehensive survey of target prediction web servers for Traditional Chinese Medicine |
title_full | Comprehensive survey of target prediction web servers for Traditional Chinese Medicine |
title_fullStr | Comprehensive survey of target prediction web servers for Traditional Chinese Medicine |
title_full_unstemmed | Comprehensive survey of target prediction web servers for Traditional Chinese Medicine |
title_short | Comprehensive survey of target prediction web servers for Traditional Chinese Medicine |
title_sort | comprehensive survey of target prediction web servers for traditional chinese medicine |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10468387/ https://www.ncbi.nlm.nih.gov/pubmed/37664753 http://dx.doi.org/10.1016/j.heliyon.2023.e19151 |
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