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KNApSAcK 家族数据库:用于多方面植物研究的综合代谢物-植物物种数据库。

KNApSAcK family databases: integrated metabolite-plant species databases for multifaceted plant research.

机构信息

Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma-shi, Nara, 630-0192 Japan.

出版信息

Plant Cell Physiol. 2012 Feb;53(2):e1. doi: 10.1093/pcp/pcr165. Epub 2011 Nov 28.

Abstract

A database (DB) describing the relationships between species and their metabolites would be useful for metabolomics research, because it targets systematic analysis of enormous numbers of organic compounds with known or unknown structures in metabolomics. We constructed an extensive species-metabolite DB for plants, the KNApSAcK Core DB, which contains 101,500 species-metabolite relationships encompassing 20,741 species and 50,048 metabolites. We also developed a search engine within the KNApSAcK Core DB for use in metabolomics research, making it possible to search for metabolites based on an accurate mass, molecular formula, metabolite name or mass spectra in several ionization modes. We also have developed databases for retrieving metabolites related to plants used for a range of purposes. In our multifaceted plant usage DB, medicinal/edible plants are related to the geographic zones (GZs) where the plants are used, their biological activities, and formulae of Japanese and Indonesian traditional medicines (Kampo and Jamu, respectively). These data are connected to the species-metabolites relationship DB within the KNApSAcK Core DB, keyed via the species names. All databases can be accessed via the website http://kanaya.naist.jp/KNApSAcK_Family/. KNApSAcK WorldMap DB comprises 41,548 GZ-plant pair entries, including 222 GZs and 15,240 medicinal/edible plants. The KAMPO DB consists of 336 formulae encompassing 278 medicinal plants; the JAMU DB consists of 5,310 formulae encompassing 550 medicinal plants. The Biological Activity DB consists of 2,418 biological activities and 33,706 pairwise relationships between medicinal plants and their biological activities. Current statistics of the binary relationships between individual databases were characterized by the degree distribution analysis, leading to a prediction of at least 1,060,000 metabolites within all plants. In the future, the study of metabolomics will need to take this huge number of metabolites into consideration.

摘要

一个描述物种与其代谢物之间关系的数据库对于代谢组学研究将非常有用,因为它针对的是对代谢组学中具有已知或未知结构的大量有机化合物进行系统分析。我们构建了一个广泛的植物物种-代谢物数据库,即 KNApSAcK 核心数据库,其中包含 101500 个物种-代谢物关系,涵盖了 20741 个物种和 50048 种代谢物。我们还开发了 KNApSAcK 核心数据库中的搜索引擎,用于代谢组学研究,可以根据精确质量、分子式、代谢物名称或几种电离模式下的质谱进行代谢物搜索。我们还开发了用于检索与多种用途相关的植物代谢物的数据库。在我们的多方面植物用途数据库中,药用/食用植物与植物使用的地理区域(GZ)、生物活性以及日本和印度尼西亚传统药物(Kampo 和 Jamu)的配方有关。这些数据通过物种名称与 KNApSAcK 核心数据库中的物种-代谢物关系数据库相连。所有数据库都可以通过网站 http://kanaya.naist.jp/KNApSAcK_Family/ 访问。KNApSAcK WorldMap DB 包含 41548 个 GZ-植物对条目,包括 222 个 GZ 和 15240 种药用/食用植物。KAMPO DB 包含 336 个配方,涵盖 278 种药用植物;JAMU DB 包含 5310 个配方,涵盖 550 种药用植物。生物活性数据库包含 2418 种生物活性和 33706 种药用植物与其生物活性之间的两两关系。个体数据库之间二元关系的当前统计数据特征是度分布分析,这导致预测所有植物中至少有 106 万种代谢物。在未来,代谢组学的研究将需要考虑到这大量的代谢物。

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