Literature DB >> 24285751

KNApSAcK Metabolite Activity Database for retrieving the relationships between metabolites and biological activities.

Yukiko Nakamura1, Farit Mochamad Afendi, Aziza Kawsar Parvin, Naoaki Ono, Ken Tanaka, Aki Hirai Morita, Tetsuo Sato, Tadao Sugiura, Md Altaf-Ul-Amin, Shigehiko Kanaya.   

Abstract

Databases (DBs) are required by various omics fields because the volume of molecular biology data is increasing rapidly. In this study, we provide instructions for users and describe the current status of our metabolite activity DB. To facilitate a comprehensive understanding of the interactions between the metabolites of organisms and the chemical-level contribution of metabolites to human health, we constructed a metabolite activity DB known as the KNApSAcK Metabolite Activity DB. It comprises 9,584 triplet relationships (metabolite-biological activity-target species), including 2,356 metabolites, 140 activity categories, 2,963 specific descriptions of biological activities and 778 target species. Approximately 46% of the activities described in the DB are related to chemical ecology, most of which are attributed to antimicrobial agents and plant growth regulators. The majority of the metabolites with antimicrobial activities are flavonoids and phenylpropanoids. The metabolites with plant growth regulatory effects include plant hormones. Over half of the DB contents are related to human health care and medicine. The five largest groups are toxins, anticancer agents, nervous system agents, cardiovascular agents and non-therapeutic agents, such as flavors and fragrances. The KNApSAcK Metabolite Activity DB is integrated within the KNApSAcK Family DBs to facilitate further systematized research in various omics fields, especially metabolomics, nutrigenomics and foodomics. The KNApSAcK Metabolite Activity DB could also be utilized for developing novel drugs and materials, as well as for identifying viable drug resources and other useful compounds.

Entities:  

Keywords:  Database; KNApSAcK family; Metabolite–activity relationship

Mesh:

Year:  2013        PMID: 24285751     DOI: 10.1093/pcp/pct176

Source DB:  PubMed          Journal:  Plant Cell Physiol        ISSN: 0032-0781            Impact factor:   4.927


  28 in total

1.  novoPathFinder: a webserver of designing novel-pathway with integrating GEM-model.

Authors:  Shaozhen Ding; Yu Tian; Pengli Cai; Dachuan Zhang; Xingxiang Cheng; Dandan Sun; Le Yuan; Junni Chen; Weizhong Tu; Dong-Qing Wei; Qian-Nan Hu
Journal:  Nucleic Acids Res       Date:  2020-07-02       Impact factor: 16.971

2.  Expansion of the composition library for chemodiversity of hardwood extractives at molecular level by ultrahigh-resolution mass spectrometry.

Authors:  Wenya Hu; Chang Samuel Hsu; Qiong Pan; Yinghao Wang; Dongze Li; Yanfen Zhang; Honggang Nie; Yehua Han
Journal:  Anal Bioanal Chem       Date:  2022-01-24       Impact factor: 4.142

3.  Antibacterial Activity Prediction of Plant Secondary Metabolites Based on a Combined Approach of Graph Clustering and Deep Neural Network.

Authors:  Mohammad Bozlul Karim; Shigehiko Kanaya; Md Altaf-Ul-Amin
Journal:  Mol Inform       Date:  2022-01-28       Impact factor: 4.050

4.  Computational approaches to natural product discovery.

Authors:  Marnix H Medema; Michael A Fischbach
Journal:  Nat Chem Biol       Date:  2015-09       Impact factor: 15.040

Review 5.  Harnessing plant metabolic diversity.

Authors:  Charlie Owen; Nicola J Patron; Ancheng Huang; Anne Osbourn
Journal:  Curr Opin Chem Biol       Date:  2017-05-17       Impact factor: 8.972

Review 6.  Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices.

Authors:  Saleh Alseekh; Asaph Aharoni; Yariv Brotman; Kévin Contrepois; John D'Auria; Jan Ewald; Jennifer C Ewald; Paul D Fraser; Patrick Giavalisco; Robert D Hall; Matthias Heinemann; Hannes Link; Jie Luo; Steffen Neumann; Jens Nielsen; Leonardo Perez de Souza; Kazuki Saito; Uwe Sauer; Frank C Schroeder; Stefan Schuster; Gary Siuzdak; Aleksandra Skirycz; Lloyd W Sumner; Michael P Snyder; Huiru Tang; Takayuki Tohge; Yulan Wang; Weiwei Wen; Si Wu; Guowang Xu; Nicola Zamboni; Alisdair R Fernie
Journal:  Nat Methods       Date:  2021-07-08       Impact factor: 47.990

Review 7.  Systems biology in the context of big data and networks.

Authors:  Md Altaf-Ul-Amin; Farit Mochamad Afendi; Samuel Kuria Kiboi; Shigehiko Kanaya
Journal:  Biomed Res Int       Date:  2014-05-27       Impact factor: 3.411

8.  Development and mining of a volatile organic compound database.

Authors:  Azian Azamimi Abdullah; Md Altaf-Ul-Amin; Naoaki Ono; Tetsuo Sato; Tadao Sugiura; Aki Hirai Morita; Tetsuo Katsuragi; Ai Muto; Takaaki Nishioka; Shigehiko Kanaya
Journal:  Biomed Res Int       Date:  2015-09-30       Impact factor: 3.411

9.  StreptomeDB 2.0--an extended resource of natural products produced by streptomycetes.

Authors:  Dennis Klementz; Kersten Döring; Xavier Lucas; Kiran K Telukunta; Anika Erxleben; Denise Deubel; Astrid Erber; Irene Santillana; Oliver S Thomas; Andreas Bechthold; Stefan Günther
Journal:  Nucleic Acids Res       Date:  2015-11-28       Impact factor: 16.971

Review 10.  A Glimpse to Background and Characteristics of Major Molecular Biological Networks.

Authors:  Md Altaf-Ul-Amin; Tetsuo Katsuragi; Tetsuo Sato; Shigehiko Kanaya
Journal:  Biomed Res Int       Date:  2015-09-30       Impact factor: 3.411

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.