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Clustering of 3D‐Structure Similarity Based Network of Secondary Metabolites Reveals Their Relationships with Biological Activities
Author(s) -
Ohtana Yuki,
Abdullah Azian Azamimi,
AltafUlAmin 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
Publication year - 2014
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201400123
Subject(s) - cluster analysis , knapsack problem , similarity (geometry) , biological network , biological data , computational biology , data mining , computer science , metabolomics , bioinformatics , biology , artificial intelligence , algorithm , image (mathematics)
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.