Computational protocol: TBC2target: A Resource of Predicted Target Genes of Tea Bioactive Compounds

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Protocol publication

[…] With 3D structures of TBCs available, we used the web server PharmMapper to predict target genes of TBCs. PharmMapper () is designed based on a pharmacophore mapping strategy to accurately identify potential target genes using a small molecule as query in its background database, which is a large-scale pharmacophore repertoire curated from target information in TargetBank (in-house data in PharmMapper project), DrugBank (), BindingDB (), and PDTD (). The server PharmMapper can help to find the optimal mapping poses of the user-uploaded small molecules against all the target genes in PharmTargetDB and the top N potential candidates together with the respective molecules’ aligned poses are outputted. In this study, the targets with a Fit Score value higher than 4.000 were selected as potential targets to ensure the high-confidence of TBC-target interactions (). [...] A bipartite network was constructed to describe the predicted TBC-target interactions. In this network, a node represented a TBC or a gene, and an edge represented the interacting relationship between a TBC and a gene. We used the Cytoscape Web () to present a network visualization interface, from which the global TBC-target network and direct interacting sub-network of a TBC or a gene can be displayed for users. In the network visualization, TBC and gene were marked with different shapes and colors (Figure ). To further topological analysis of the network, several typical parameters, such as degree, betweenness, radiality and neighborhood, were computed for a TBC or a gene using the Cytoscape plugin NetworkAnalyzer (). […]

Pipeline specifications

Software tools PharmMapper, Cytoscape Web, NetworkAnalyzer
Databases DrugBank BindingDB PDTD
Application Protein interaction analysis
Organisms Homo sapiens
Diseases Osteitis Deformans