Clustering of 3D structure similarity based network of secondary metabolites to reveal their relationships with biological activities

Abstract

Developing database systems connecting diverged 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 and applied to a data set consisting of 2,072 secondary metabolites and 140 biological activities reported in KNApSAcK Metabolite Activity DB. As a whole, we systematically analyzed the relationship between 3D-chemical structures of metabolites and biological activities.