Abstract
Natural medicines (i.e., herbal medicines, traditional formulas) are useful for treatment of multifactorial and chronic diseases. Here, we present KampoDB (http://wakanmoview.inm.u-toyama.ac.jp/kampo/), a novel platform for the analysis of natural medicines, which provides various useful scientific resources on Japanese traditional formulas Kampo medicines, constituent herbal drugs, constituent compounds, and target proteins of these constituent compounds. Potential target proteins of these constituent compounds were predicted by docking simulations and machine learning methods based on large-scale omics data (e.g., genome, proteome, metabolome, interactome). The current version of KampoDB contains 42 Kampo medicines, 54 crude drugs, 1230 constituent compounds, 460 known target proteins, and 1369 potential target proteins, and has functional annotations for biological pathways and molecular functions. KampoDB is useful for mode-of-action analysis of natural medicines and prediction of new indications for a wide range of diseases.
Highlights
Traditional medicines are used clinically in many areas of the world, including in Japan (Kampo), China, Korea, India (Ayurveda) and Perso-Arabic countries (Yunani)
We collected the relationships between Kampo drugs and crude drugs from the Traditional Medical & Pharmaceutical Database of the Institute of Natural Medicine, University of Toyama
KampoDB is compatible with other molecular biology databases (e.g., KEGG12, ChEMBL6, UniProt[13], KNApSAcK14) by using the same identifiers
Summary
Traditional medicines are used clinically in many areas of the world, including in Japan (Kampo), China, Korea, India (Ayurveda) and Perso-Arabic countries (Yunani). It is, 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. 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. These “big data” are useful resources for mode-of-action analysis of Kampo medicines; there is a strong need to develop databases and associated tools for Kampo medicines. 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
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
