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      A Systems Biology-Based Investigation into the Pharmacological Mechanisms of Wu Tou Tang Acting on Rheumatoid Arthritis by Integrating Network Analysis

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          Abstract

          Aim. To investigate pharmacological mechanisms of Wu Tou Tang acting on rheumatoid arthritis (RA) by integrating network analysis at a system level. Methods and Results. Drug similarity search tool in Therapeutic Targets Database was used to screen 153 drugs with similar structures to compositive compounds of each ingredient in Wu Tou Tang and to identify 56 known targets of these similar drugs as predicted molecules which Wu Tou Tang affects. The recall, precision, accuracy, and F1-score, which were calculated to evaluate the performance of this method, were, respectively, 0.98, 0.61, 59.67%, and 0.76. Then, the predicted effector molecules of Wu Tou Tang were significantly enriched in neuroactive ligand-receptor interaction and calcium signaling pathway. Next, the importance of these predicted effector molecules was evaluated by analyzing their network topological features, such as degree, betweenness, and k-coreness. We further elucidated the biological significance of nine major candidate effector molecules of Wu Tou Tang for RA therapy and validated their associations with compositive compounds in Wu Tou Tang by the molecular docking simulation. Conclusion. Our data suggest the potential pharmacological mechanisms of Wu Tou Tang acting on RA by combining the strategies of systems biology and network pharmacology.

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          Most cited references72

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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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            The IntAct molecular interaction database in 2010

            IntAct is an open-source, open data molecular interaction database and toolkit. Data is abstracted from the literature or from direct data depositions by expert curators following a deep annotation model providing a high level of detail. As of September 2009, IntAct contains over 200.000 curated binary interaction evidences. In response to the growing data volume and user requests, IntAct now provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows ‘zooming in’ on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available at http://www.ebi.ac.uk/intact.
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              Online predicted human interaction database.

              High-throughput experiments are being performed at an ever-increasing rate to systematically elucidate protein-protein interaction (PPI) networks for model organisms, while the complexities of higher eukaryotes have prevented these experiments for humans. The Online Predicted Human Interaction Database (OPHID) is a web-based database of predicted interactions between human proteins. It combines the literature-derived human PPI from BIND, HPRD and MINT, with predictions made from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Mus musculus. The 23,889 predicted interactions currently listed in OPHID are evaluated using protein domains, gene co-expression and Gene Ontology terms. OPHID can be queried using single or multiple IDs and results can be visualized using our custom graph visualization program. Freely available to academic users at http://ophid.utoronto.ca, both in tab-delimited and PSI-MI formats. Commercial users, please contact I.J. juris@ai.utoronto.ca http://ophid.utoronto.ca/supplInfo.pdf.
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                Author and article information

                Journal
                Evid Based Complement Alternat Med
                Evid Based Complement Alternat Med
                ECAM
                Evidence-based Complementary and Alternative Medicine : eCAM
                Hindawi Publishing Corporation
                1741-427X
                1741-4288
                2013
                28 March 2013
                28 March 2013
                : 2013
                : 548498
                Affiliations
                Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, No. 16, Nanxiaojie, Dongzhimennei, Beijing 100700, China
                Author notes

                Academic Editor: Aiping Lu

                Author information
                https://orcid.org/0000-0002-9202-5939
                https://orcid.org/0000-0002-6781-5330
                https://orcid.org/0000-0002-6180-864X
                https://orcid.org/0000-0002-4487-5517
                Article
                10.1155/2013/548498
                3625555
                23690848
                219e6162-3a16-43ed-9a16-258b80b6e938
                Copyright © 2013 Yanqiong Zhang et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 January 2013
                : 20 February 2013
                Categories
                Research Article

                Complementary & Alternative medicine
                Complementary & Alternative medicine

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