Hit Dexter 2.0: How likely is my compound a frequent hitter?

Hit Dexter is a machine learning approach to estimate how likely a small molecule is to trigger a positive response in biochemical assays. The models were derived from a dataset of 250,000 compounds with experimentally determined activity for at least 50 different protein groups. For further detail see Hit Dexter 2.0: Machine-Learning Models for the Prediction of Frequent Hitters

Enter SMILES

example: CCOC(=O)N1CCN(CC1)C2=C(C(=O)C2=O)N3CCN(CC3)C4=CC=C(C=C4)OC

or upload a file with a list of SMILES (for examples see About page)

or draw your own molecule