PharmDB-K: Integrated bio-pharmacological network database for traditional Korean medicine

Ji Hyun Lee, Kyoung Mii Park, Dong Jin Han, Nam Young Bang, Do Hee Kim, Hyeongjin Na, Semi Lim, Tae Bum Kim, Dae Gyu Kim, Hyun Jung Kim, Yeonseok Chung, Sang Hyun Sung, Young Joon Surh, Sunghoon Kim, Byung Woo Han

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

Despite the growing attention given to Traditional Medicine (TM) worldwide, there is no wellknown, publicly available, integrated bio-pharmacological Traditional Korean Medicine (TKM) database for researchers in drug discovery. In this study, we have constructed PharmDB-K, which offers comprehensive information relating to TKM-Associated drugs (compound), disease indication, and protein relationships. To explore the underlying molecular interaction of TKM, we integrated fourteen different databases, six Pharmacopoeias, and literature, and established a massive bio-pharmacological network for TKM and experimentally validated some cases predicted from the PharmDB-K analyses. Currently, PharmDB-K contains information about 262 TKMs, 7,815 drugs, 3,721 diseases, 32,373 proteins, and 1,887 side effects. One of the unique sets of information in PharmDB-K includes 400 indicator compounds used for standardization of herbal medicine. Furthermore, we are operating PharmDB-K via phExplorer (a network visualization software) and BioMart (a data federation framework) for convenient search and analysis of the TKM network.

Original languageEnglish
Article numbere0142624
JournalPloS one
Volume10
Issue number11
DOIs
Publication statusPublished - 2015 Nov 10

Bibliographical note

Funding Information:
This research was supported by the Basic Science Research Program funded by the Ministry of Education [JL] and Global Frontier Project funded by the Ministry of Science, ICT and Future Planning through the National Research Foundation of Korea [BH] (NRF-2013R1A1A2058353 and NRF-2013M3A6A4043695).

Publisher Copyright:
© 2015 Lee et al. 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.

All Science Journal Classification (ASJC) codes

  • General

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