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      TCMID 2.0: a comprehensive resource for TCM

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          Abstract

          As a traditional medical intervention in Asia and a complementary and alternative medicine in western countries, Traditional Chinese Medicine (TCM) is capturing worldwide attention in life science field. Traditional Chinese Medicine Integrated Database (TCMID), which was originally launched in 2013, was a comprehensive database aiming at TCM’s modernization and standardization. It has been highly recognized among pharmacologists and scholars in TCM researches. The latest release, TCMID 2.0 ( http://www.megabionet.org/tcmid/), replenished the preceding database with 18 203 herbal ingredients, 15 prescriptions, 82 related targets, 1356 drugs, 842 diseases and numerous new connections between them. Considering that chemical changes might take place in decocting process of prescriptions, which may result in new ingredients, new data containing the prescription ingredients was collected in current version. In addition, 778 herbal mass spectrometry (MS) spectra related to 170 herbs were appended to show the variation of herbal quality in different origin and distinguish genuine medicinal materials from common ones while 3895 MS spectra of 729 ingredients were added as the supplementary materials of component identification. With the significant increase of data, TCMID 2.0 will further facilitate TCM’s modernization and enhance the exploration of underlying biological processes that are response to the diverse pharmacologic actions of TCM.

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          Most cited references13

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          ChEBI in 2016: Improved services and an expanding collection of metabolites

          ChEBI is a database and ontology containing information about chemical entities of biological interest. It currently includes over 46 000 entries, each of which is classified within the ontology and assigned multiple annotations including (where relevant) a chemical structure, database cross-references, synonyms and literature citations. All content is freely available and can be accessed online at http://www.ebi.ac.uk/chebi. In this update paper, we describe recent improvements and additions to the ChEBI offering. We have substantially extended our collection of endogenous metabolites for several organisms including human, mouse, Escherichia coli and yeast. Our front-end has also been reworked and updated, improving the user experience, removing our dependency on Java applets in favour of embedded JavaScript components and moving from a monthly release update to a ‘live’ website. Programmatic access has been improved by the introduction of a library, libChEBI, in Java, Python and Matlab. Furthermore, we have added two new tools, namely an analysis tool, BiNChE, and a query tool for the ontology, OntoQuery.
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            TCM Database@Taiwan: The World's Largest Traditional Chinese Medicine Database for Drug Screening In Silico

            Rapid advancing computational technologies have greatly speeded up the development of computer-aided drug design (CADD). Recently, pharmaceutical companies have increasingly shifted their attentions toward traditional Chinese medicine (TCM) for novel lead compounds. Despite the growing number of studies on TCM, there is no free 3D small molecular structure database of TCM available for virtual screening or molecular simulation. To address this shortcoming, we have constructed TCM Database@Taiwan (http://tcm.cmu.edu.tw/) based on information collected from Chinese medical texts and scientific publications. TCM Database@Taiwan is currently the world's largest non-commercial TCM database. This web-based database contains more than 20,000 pure compounds isolated from 453 TCM ingredients. Both cdx (2D) and Tripos mol2 (3D) formats of each pure compound in the database are available for download and virtual screening. The TCM database includes both simple and advanced web-based query options that can specify search clauses, such as molecular properties, substructures, TCM ingredients, and TCM classification, based on intended drug actions. The TCM database can be easily accessed by all researchers conducting CADD. Over the last eight years, numerous volunteers have devoted their time to analyze TCM ingredients from Chinese medical texts as well as to construct structure files for each isolated compound. We believe that TCM Database@Taiwan will be a milestone on the path towards modernizing traditional Chinese medicine.
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              HIT: linking herbal active ingredients to targets

              The information of protein targets and small molecule has been highly valued by biomedical and pharmaceutical research. Several protein target databases are available online for FDA-approved drugs as well as the promising precursors that have largely facilitated the mechanistic study and subsequent research for drug discovery. However, those related resources regarding to herbal active ingredients, although being unusually valued as a precious resource for new drug development, is rarely found. In this article, a comprehensive and fully curated database for Herb Ingredients’ Targets (HIT, http://lifecenter.sgst.cn/hit/) has been constructed to complement above resources. Those herbal ingredients with protein target information were carefully curated. The molecular target information involves those proteins being directly/indirectly activated/inhibited, protein binders and enzymes whose substrates or products are those compounds. Those up/down regulated genes are also included under the treatment of individual ingredients. In addition, the experimental condition, observed bioactivity and various references are provided as well for user's reference. Derived from more than 3250 literatures, it currently contains 5208 entries about 1301 known protein targets (221 of them are described as direct targets) affected by 586 herbal compounds from more than 1300 reputable Chinese herbs, overlapping with 280 therapeutic targets from Therapeutic Targets Database (TTD), and 445 protein targets from DrugBank corresponding to 1488 drug agents. The database can be queried via keyword search or similarity search. Crosslinks have been made to TTD, DrugBank, KEGG, PDB, Uniprot, Pfam, NCBI, TCM-ID and other databases.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                04 January 2018
                02 November 2017
                02 November 2017
                : 46
                : Database issue , Database issue
                : D1117-D1120
                Affiliations
                TCM Clinical Basis Institute, Zhejiang Chinese Medicine University, Zhejiang 310000, China
                The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai 200241, China
                Author notes
                To whom correspondence should be addressed. Tel: +86 571 86613644; Fax: +86 571 86613644; Email: wengcp@ 123456163.com . Correspondence may also be addressed to Tieliu Shi. Tel: +86 21 54345020; Fax: +86 21 54344922; Email: tieliushi@ 123456bio.ecnu.edu.cn

                These authors contributed equally to this work as first authors.

                Article
                gkx1028
                10.1093/nar/gkx1028
                5753259
                29106634
                234bc943-8533-428e-9a51-65d002688ff1
                © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 18 October 2017
                : 14 October 2017
                : 13 September 2016
                Page count
                Pages: 4
                Categories
                Database Issue

                Genetics
                Genetics

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