Hit Dexter 3
How Likely is my Compound a Frequent Hitter?

Calculate similarities:

Provide input molecule(s):

Enter SMILES

Example: C(=NN=c1ccc2ccccc2[nH]1)c1ccccn1

or upload a file with a list of SMILES
or draw your own molecule

Hit Dexter 3

Hit Dexter is a machine learning approach to estimate how likely a small molecule is to trigger a positive response in biochemical and biological assays. The models were derived from a dataset of 250,000 compounds with experimentally determined activity for at least 100 different protein groups.

For more information, see the Documentation page.

How to cite

If you are using Hit Dexter 3 for your research, please cite all of the following publications:

Stork, C.; Mathai, N.; Kirchmair, J. Computational prediction of frequent hitters in target-based and cell-based assays. Artificial Intelligence in the Life Sciences 2021.
doi: 10.1016/j.ailsci.2021.100007

Stork, C.; Embruch, G.; Šícho, M.; de Bruyn Kops, C.; Chen, Y.; Svozil, D.; Kirchmair, J. NERDD: a web portal providing access to in silico tools for drug discovery. Bioinformatics 2020.
doi:10.1093/bioinformatics/btz695