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Alkamid database: Chemistry, occurrence and functionality of plant N-alkylamides

期刊

JOURNAL OF ETHNOPHARMACOLOGY
卷 142, 期 3, 页码 563-590

出版社

ELSEVIER IRELAND LTD
DOI: 10.1016/j.jep.2012.05.038

关键词

N-alkylamides (NAAs); Plant taxonomy; Bioactivity; Alkamid database; Chemical structure classification

资金

  1. Institute for the Promotion of Innovation through Science and Technology in Flanders (IWT-Vlaanderen) [91257]

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Ethnopharmacological relevance: N-Alkylamides (NAAs) are a promising group of bioactive compounds, which are anticipated to act as important lead compounds for plant protection and biocidal products, functional food, cosmeceuticals and drugs in the next decennia. These molecules, currently found in more than 25 plant families and with a wide structural diversity, exert a variety of biological-pharmacological effects and are of high ethnopharmacological importance. However, information is scattered in literature, with different, often unstandardized, pharmacological methodologies being used. Therefore, a comprehensive NAA database (acronym: Alkamid) was constructed to collect the available structural and functional NAA data, linked to their occurrence in plants (family, tribe, species, genus). Materials and methods: For loading information in the database, literature data was gathered over the period 1950-2010, by using several search engines. In order to represent the collected information about NAAs, the plants in which they occur and the functionalities for which they have been examined, a relational database is constructed and implemented on a MySQL back-end. Results: The database is supported by describing the NAA plant-, functional- and chemical-space. The chemical space includes a NAA classification, according to their fatty acid and amine structures. Conclusions: The Alkamid database (publicly available on the website http://alkamid.ugent.be/) is not only a central information point, but can also function as a useful tool to prioritize the NAA choice in the evaluation of their functionality, to perform data mining leading to quantitative structure-property relationships (QSPRs), functionality comparisons, clustering, plant biochemistry and taxonomic evaluations. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

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