CSNAP is a computational approach for compound target identification based on network similarity graphs. Query and reference compounds are populated on the network connectivity map and a graph-based neighbor counting method is applied to rank the consensus targets among the neighborhood of each query ligand. The CSNAP approach can facilitate high-throughput target discovery and off-target prediction for any compound set identified from phenotype-based or cell-based chemical screens.
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Large-scale chemical similarity networks for target profiling of compounds identified in cell-based chemical screens.
Lo YC, Senese S, Li CM, Hu Q, Huang Y, Damoiseaux R, Torres JZ.
PLoS Comput Biol. 2015 Mar 31;11(3):e1004153. doi: 10.1371/journal.pcbi.1004153.