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      TCM Database@Taiwan: The World's Largest Traditional Chinese Medicine Database for Drug Screening In Silico

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      PLoS ONE
      Public Library of Science

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          Abstract

          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@ 123456Taiwan ( http://tcm.cmu.edu.tw/) based on information collected from Chinese medical texts and scientific publications. TCM Database@ 123456Taiwan 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@ 123456Taiwan will be a milestone on the path towards modernizing traditional Chinese medicine.

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          Most cited references10

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          Database resources of the National Center for Biotechnology Information

          In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, Reference Sequence, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Entrez Probe, GENSAT, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Peptidome, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.
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            TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining

            Background Traditional Chinese Medicine (TCM), a complementary and alternative medical system in Western countries, has been used to treat various diseases over thousands of years in East Asian countries. In recent years, many herbal medicines were found to exhibit a variety of effects through regulating a wide range of gene expressions or protein activities. As available TCM data continue to accumulate rapidly, an urgent need for exploring these resources systematically is imperative, so as to effectively utilize the large volume of literature. Methods TCM, gene, disease, biological pathway and protein-protein interaction information were collected from public databases. For association discovery, the TCM names, gene names, disease names, TCM ingredients and effects were used to annotate the literature corpus obtained from PubMed. The concept to mine entity associations was based on hypothesis testing and collocation analysis. The annotated corpus was processed with natural language processing tools and rule-based approaches were applied to the sentences for extracting the relations between TCM effecters and effects. Results We developed a database, TCMGeneDIT, to provide association information about TCMs, genes, diseases, TCM effects and TCM ingredients mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information are also available for exploring the regulations of genes associated with TCM curative effects. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in understanding the possible therapeutic mechanisms of TCMs via gene regulations and deducing synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. The database is now available at . Conclusion TCMGeneDIT is a unique database that offers diverse association information on TCMs. This database integrates TCMs with biomedical studies that would facilitate clinical research and elucidate the possible therapeutic mechanisms of TCMs and gene regulations.
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              Functionality Pattern Matching as an Efficient Complementary Structure/Reaction Search Tool: an Open-Source Approach

              An open-source software package for creating and operating web-based structure and/or reaction databases is presented. Besides standard search capabilities (text, structure/substructure/similarity), the system offers a fast additional search option, entirely based on binary pattern matching, which uses automatically assigned functional group descriptors.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                6 January 2011
                : 6
                : 1
                : e15939
                Affiliations
                [1 ]School of Chinese Medicine, China Medical University, Taichung, Taiwan
                [2 ]Department of Bioinformatics, Asia University, Taichung, Taiwan
                [3 ]Department of Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
                Griffith University, Australia
                Author notes

                Conceived and designed the experiments: CYCC. Performed the experiments: CYCC. Analyzed the data: CYCC. Contributed reagents/materials/analysis tools: CYCC. Wrote the paper: CYCC.

                Article
                PONE-D-10-03893
                10.1371/journal.pone.0015939
                3017089
                21253603
                afe05b8d-5ea5-41dc-a276-64be25a0d23b
                Calvin Yu-Chian Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 25 October 2010
                : 30 November 2010
                Page count
                Pages: 5
                Categories
                Research Article
                Biology
                Biochemistry
                Biomacromolecule-Ligand Interactions
                Drug Discovery
                Small Molecules
                Biophysics
                Biomacromolecule-Ligand Interactions
                Biophysics Simulations
                Biotechnology
                Drug Discovery
                Computational Biology
                Biophysic Al Simulations
                Computer Science
                Information Technology
                Databases

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                Uncategorized

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