Clustering of 3D‐Structure Similarity Based Network of Secondary Metabolites Reveals Their Relationships with Biological Activities. Issue 11 (24th November 2014)

• Record Type: Journal Article
• Authors: Ohtana, Yuki; Abdullah, Azian Azamimi; Altaf‐Ul‐Amin, Md.; Huang, Ming; Ono, Naoaki; Sato, Tetsuo; Sugiura, Tadao; Horai, Hisayuki; Nakamura, Yukiko; Morita (Hirai), Aki; Lange, Klaus W.; Kibinge, Nelson K.; Katsuragi, Tetsuo; Shirai, Tsuyoshi; Kanaya, Shigehiko
• Is Part Of: Molecular informatics. Volume 33:Issue 11/12(2014)
• Page Start: 790
• Page End: 801
• Publication Date: 2014-11-24
• Subjects: Clustering of 3D‐structure similarity -- Network of secondary metabolites -- Metabolites -- Biological activities -- KNApSAcK family databases -- Phytochemistry -- Structureproperty relationships -- Visualization, Cheminformatics -- ′Bioinformatics; Cheminformatics -- Periodicals; QSAR (Biochemistry) -- Periodicals; Structure-activity relationships (Biochemistry) -- Periodicals; Drugs -- Structure-activity relationships -- Periodicals; 615.19
• DOI: 10.1002/minf.201400123
• Languages: English
• ISSNs: 1868-1743

Abstract

Abstract: Developing database systems connecting diverse species based on omics is the most important theme in big data biology. To attain this purpose, we have developed KNApSAcK Family Databases, which are utilized in a number of researches in metabolomics. In the present study, we have developed a network‐based approach to analyze relationships between 3D structure and biological activity of metabolites consisting of four steps as follows: construction of a network of metabolites based on structural similarity (Step 1), classification of metabolites into structure groups (Step 2), assessment of statistically significant relations between structure groups and biological activities (Step 3), and 2‐dimensional clustering of the constructed data matrix based on statistically significant relations between structure groups and biological activities (Step 4). Applying this method to a data set consisting of 2072 secondary metabolites and 140 biological activities reported in KNApSAcK Metabolite Activity DB, we obtained 983 statistically significant structure group‐biological activity pairs. As a whole, we systematically analyzed the relationship between 3D‐chemical structures of metabolites and biological activities. Abstract :