TargetNet is an open web server that could be used for netting or predicting the binding of multiple targets for any given molecule. TargetNet simultaneously constructs a large number of QSAR models based on current chemogenomics data to make future predictions. When the user submits a molecule, the server will predict the activity of the user’s molecule across 623 human proteins by establishing the high quality QSAR model for each human protein, thus generating a drug-target interaction (DTI) profiling that can used as a feature vector for wide applications.

The 623 QSAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75%-100%. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling.

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