ArticleFrontiers in pharmacology2018
Systems-Mapping of Herbal Effects on Complex Diseases Using the Network-Perturbation Signatures.
Article in Frontiers in pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Licochalcone A: a review of its pharmacology activities and molecular mechanisms.Frontiers in pharmacology · 2024Review
- Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review.Frontiers in pharmacology · 2023Review
- Elucidating direct kinase targets of compound Danshen dropping pills employing archived data and prediction models.Scientific reports · 2021Article
- The Advantages of Connectivity Map Applied in Traditional Chinese Medicine.Frontiers in pharmacology · 2021Review
- Modular Characteristics and Mechanism of Action of Herbs for Endometriosis Treatment in Chinese Medicine: A Data Mining and Network Pharmacology-Based Identification.Frontiers in pharmacology · 2020Article
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Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The herbs have proven to hold great potential to improve people's health and wellness during clinical practice over the past millennia. However, herbal medicine for the personalized treatment of disease is still under investigation owing to the complex multi-component interactions in herbs. To reveal the valuable insights for herbal synergistic therapy, we have chosen Traditional Chinese Medicine (TCM) as a case to illustrate the art and science behind the complicated multi-molecular, multi-genes interaction systems, and how the good practices of herbal combination therapy are applicable to personalized treatment. Here, we design system-wide interaction map strategy to provide a generic solution to establish the links between diseases and herbs based on comprehensive testing of molecular signatures in herb-disease pairs. Firstly, we integrated gene expression profiles from 189 diseases to characterize the disease-pathological feature. Then, we generated the perturbation signatures from the huge chemical informatics data and pharmacological data for each herb, which were represented the targets affected by the ingredients in the herb. So that we could assess the effects of herbs on the individual. Finally, we integrated the data of 189 diseases and 502 herbs, yielding the optimal herbal combinations for the diseases based on the strategy, and verifying the reliability of the strategy through the permutation testing and literature verification. Furthermore, we propose a novel formula as a candidate therapeutic drugs of rheumatoid arthritis and demonstrate its therapeutic mechanism through the systematic analysis of the influencing targets and biological processes. Overall, this computational method provides a systematic approach, which blended herbal medicine and omics data sets, allowing for the development of novel drug combinations for complex human diseases.
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