Abstract
Identification of the biological targets of a compound is of paramount importance for the exploration of the mechanism of action of drugs and for the development of novel drugs. A concept of the Connectivity Map (CMap) was previously proposed to connect genes, drugs, and disease states based on the common gene-expression signatures. For a new query compound, the CMap-based method can infer its potential targets by searching similar drugs with known targets (reference drugs) and measuring the similarities into their specific transcriptional responses between the query compound and those reference drugs. However, the available methods are often inefficient due to the requirement of the reference drugs as a medium to link the query agent and targets. Here, we developed a general procedure to extract target-induced consensus gene modules from the transcriptional profiles induced by the treatment of perturbagens of a target. A specific transcriptional gene module pair (GMP) was automatically identified for each target and could be used as a direct target signature. Based on the GMPs, we built the target network and identified some target gene clusters with similar biological mechanisms. Moreover, a gene module pair-based target identification (GMPTI) approach was proposed to predict novel compound-target interactions. Using this method, we have discovered novel inhibitors for three PI3K pathway proteins PI3Kα/β/δ, including PU-H71, alvespimycin, reversine, astemizole, raloxifene HCl, and tamoxifen.