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Kampo medicine originated from ancient Chinese medicine but evolved independently over a long period of time more than years to become a style individual to Japan. Kampo formulas often differ from Chinese or Korean traditional formulas, although many of the same medicinal herbs are used for traditional medicines across eastern Asian countries. Kampo medicines are decoctions or dry powders that include pharmaceutical active ingredients extracted by boiling from a mixture of naturally derived medicinal herbs.
They are generally factory-produced by pharmaceutical companies in Japan and provided in a ready-to-use form.
The Ministry maintains oversight of Kampo medicines. Thus, Kampo medicines are established as a pivotal part of mainstream medicine in Japan and the cost of Kampo medicines is covered by the National Health Insurance.
In recent years, NIH support and the US Food and Drug Administration FDA guideline on investigating botanical drug products, including complex formulas containing many constituents, has fostered the development of botanical drugs in the United States 1 , 2. Presently, randomized, double-blind, placebo-controlled clinical trials of some Kampo medicines e.
However, the pharmacotherapy with Kampo medicines greatly depends on the empirical knowledge of medical doctors in practice, and there is insufficient scientific evidence explaining the underlying molecular mechanisms of Kampo medicines. The mechanisms of Kampo medicines are different from those of ordinary medicines. The efficacies of Kampo medicines stem from multiple compound—multiple target interactions. It is, therefore, indispensable to establish fundamental technologies to comprehensively analyze the underlying mechanisms of every pharmacological action of multicomponent Kampo medicines in the human body as a complex system.
Figure 1 An illustration of the difference of the mode-of-action between ordinary medicines and Kampo medicines. In ordinary medicines, the efficacies stem from one compound—one target interaction. On the other hand, in Kampo medicines, the efficacies stem from multiple compound—multiple target interactions. Full size image In recent biomedical science, clinical and molecular data for Kampo medicine-based pharmacotherapy have been accumulated, and a variety of omics data are becoming available in the genome, transcriptome, proteome, metabolome, phenome, and diseasome.
Many databases for Western medicines exist e. However, there is no integrated database of Kampo medicine-related chemical and biological data, and clinical research data and clinical findings. There is a wiki-system database of Kampo medicines and crude drugs 11 , but it is mainly Kampo medicine-related pharmacognostical and chemical database and thereby cannot help to understand the mode-of-actions and further clinical applications of Kampo medicines.
Therefore, KampoDB is useful for understanding the mode-of-action of natural medicines in terms of biological pathways and molecular functions of target proteins, which can lead to new indications for a wide range of diseases.
The present study aims to elucidate the underlying mechanisms of Kampo medicines, while predicting their target proteins and new indications, thereby repositioning Kampo medicines for their extensive application in clinical practice, with a view toward using them more effectively in clinical practice. Results Data collection The current version of KampoDB contains 42 Kampo medicines, 54 crude drugs, constituent compounds, known target proteins, and potential target proteins and has functional annotations for biological pathways and molecular functions.
The molecular information on natural medicines in KampoDB was collected and digitized from scientific literature, molecular databases, and clinical reports. As the information was provided in Japanese, we translated it to English. The correlation between Kampo drugs and crude drugs was not based on the computational predictions.
KampoDB is compatible with other molecular biology databases e. Inputs and outputs KampoDB consists of three components: 1 natural medicines list, 2 functional analysis, and 3 target prediction.
Figure 2 A diagrammatic representation of KampoDB that consists of three components: 1 natural medicines list, 2 functional analysis, and 3 target prediction. Kakkonto is one of the most frequently used Kampo medicines in Japan, because it is a highly effective and safe medicine against the common cold 15 , influenza 16 and allergic rhinitis 17 either as sole therapy or in combination with modern Western medicines.
The main bioactive compound in kakkonto is thought to be puerarin, which is an isoflavonoid derived from Puerariae Radix that exhibits many pharmacological properties, including such as anti-inflammation, vasodilation, neuroprotection, antioxidant and anticancer effects Supplementary Fig. Clicking on the search button, the user can obtain the corresponding information on Kampo medicines, crude drugs, constituent compounds and target proteins.
The user can see a global classification of Kampo medicines, crude drugs, constituent compounds, and target proteins in a hierarchical manner Kampo medicines on the 1st layer; crude drugs on the 2nd layer; constituent compounds on the 3rd layer; target proteins on the 4th layer. Note that each Kampo medicine consists of multiple crude drugs, each crude drug consists of multiple compounds, and each constituent compound is supposed to interact with its target proteins.
If the proteins are therapeutic targets of diseases, the corresponding diseases are shown. The output is the summary of the mode-of-action analysis of the corresponding natural medicines, which provides molecular function annotations of target proteins e. A visualization of the results at different layer levels enables the user to see the mode-of-action information in a hierarchical manner within a natural medicine classification.
The user can select a query compound by clicking on a compound name of interest in the list of the constituent compounds that are defined as standard compounds in the Japanese pharmacopoeia see the METHODS section for more details. The outputs are the list of predicted human proteins for the query compound and associated information. In the docking simulation method, docking was performed for the constituent compounds with each human protein 3D structure.
In the machine learning method, supervised classification with compound chemical structure similarity was performed for each human protein see the METHODS section for more details. The 2nd and 3rd layers show the crude drugs e. The 4th layer shows the target proteins e.
The output enables the user to investigate the hierarchical relationship between Kampo medicines, crude drugs, constituent compounds and target proteins. The 2nd layer shows the crude drugs e. The 3rd layer shows the constituent compounds e. In the case of pathway enrichment analysis, biological pathways with high enrichment ratios and low p-values can be thought of as candidates for the associated pathways.
The 1st column shows the pathway ID in KEGG, the 2nd column shows the pathway name, the 3rd column shows the enrichment ratio, and the 4th column shows the p-value for a hypergeometic test.
The left panel in Fig. The graphical picture enables the user to investigate the ligand binding sites on the protein 3D structure. The validity of the shikonin-FKBP interaction and its pharmacological effects were experimentally confirmed in a previous work Boiogito is prescribed as a Kampo remedy for arthritis, nephrosis, edema, hyperhidrosis and obesity.
Sinomenine, an ingredient extracted from the Sinomenium Stem, exerts anti-inflammatory effects through inhibiting lymphocyte proliferation 21 , and decreasing eicosanoid synthesis and nitric oxide production Furthermore, sinomenine ameliorates experimental arthritis in an animal model The list of target candidate proteins and the associated information e. This is how the method can be used for the mode-of-action analysis of Kampo medicines. Full size image A case study As a case study, we show here how KampoDB could be used with daikenchuto, one of the most frequently used Kampo medicines in Japan.
Daikenchuto is beneficial for postoperative complications such as ileus and abdominal bloating. Although the mechanisms of daikenchuto are not fully understood, it has been reported that daikenchuto ameliorates these intestinal motility disorders via the release of serotonin and suppress the inflammation via the inhibition of cyclooxygenase-2 activity 24 , This suggests that daikenchuto derives its anti-inflammatory activity via arachidonic acid metabolism 26 and several other pathways.
We previously showed that daikenchuto markedly alleviated dextran sulfate sodium DSS -induced experimental colitis in mice. Ulcerative colitis is a chronic inflammatory bowel disease IBD in which patients experience intermittent remission and relapse over decades. The long-term chronic inflammation elevates the risk of colitis-associated cancer CAC and can lead to CAC-related death.
However, not all medicines effective against experimental colitis are necessarily effective against CAC. Indeed, it has been reported that an agonist for a prostaglandin E2 receptor subtype suppresses DSS-induced colitis and also prevents the development of colorectal carcinogenesis in a murine CAC model, whereas sulfasalazine, a prodrug of 5-aminosalicylic acid with efficacy against DSS-induced colitis, did not prevent colorectal tumor formation in a murine CAC model In particular, the contribution of the Wnt signaling pathway to the colorectal carcinogenesis is established Additionally, Wnt signaling-initiated tumorigenesis has been reported in a murine CAC model Taking all together, these findings suggest that daikenchuto attenuates the development of chronic inflammation-associated cancer.
It has the potential to be a new therapeutic strategy while repositioning the use of Kampo medicine. While testing this hypothesis, we found that the daikenchuto treatment indeed significantly suppressed the development of chronic colitis-associated colon cancer in a murine experimental model, as shown in Fig.
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Start reading. Book Description Data is getting bigger and more complex by the day, and so are your choices in handling it. What You Need: Each chapter will list the downloads required for that database.
Advanced Queries, Code, and Rules Day 3: Full Text and Multidimensions Wrap-Up 3. Working with Big Data Day 3: Taking It to the Cloud Wrap-Up 4. MongoDB Hu mongo us Day 1: Indexing, Aggregating, Mapreduce Day 3: Creating and Querying Views Day 3: Distributed High Availability Wrap-Up 7. Day 2: Building a Streaming Data Pipeline Day 3: Advanced Usage, Distribution Day 3: