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.
Highlights
Common complex diseases are caused by a combination of heritable and environmental factors that affect the gene expression of individual (Kalf et al, 2014)
To explore the synergistic mechanism of herbal medicine and the personalized treatment strategy for diseases, the establishment of standard basic data is the key factor for the algorithm
With the establishment of disease and herbal data, we perform a system-wide interaction mapping strategy to predict the most therapeutic potential herb for the disease based on the perturbation signatures, termed HDmap-S (Single Herb-Disease Mapping)
Summary
Common complex diseases are caused by a combination of heritable and environmental factors that affect the gene expression of individual (Kalf et al, 2014). Enormous efforts have been made to obtain potent and specific drugs, the side effects caused by these drugs and the emergence of resistance to complex diseases are still not negligible (Lounkine et al, 2012; Holohan et al, 2013). It becomes more and more evident that, for complex diseases like rheumatoid arthritis, an interference from multiple molecules and multiple targets is superior to classical “one-targetone-disease” approach regarding drug efficiency, side-effects and drug resistance (Sheng and Sun, 2011; Koeberle and Werz, 2014). The traditional herbal formulas have achieved tremendous achievements in clinical practice based on TCM clinical practice guidelines (e.g., “Jun-Chen-Zuo-Shi,” 君-臣-佐-使), which are the clinical summary of Chinese herbalists over the past millennia (He et al, 2015; Zhao et al, 2015). The fundamental challenge that arises throughout TCM is the need to establish the relationship between diseases and the action of herb therapeutics
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