CDK5 predictor

screenshot_2021-12-03-template_report_background-pptxCDK5 predictor allows you to evaluate the potential inhibitory activity of small molecules, by using a machine learning model based on Random Forest algorithm trained with Morgan Fingerprints of known active and inactive compounds.

To use CDK5 predictor, you need to provide the SMILES string of the molecule to be analyzed.
You can sketch the 2D structure of  a molecule using the JMSE widget provided below
and get the corresponding SMILES by directly in the field below the widget.


If you want to use CDK5 predictor for a large number of molecules, please contact us at .

Di Stefano, M.; Galati, S.; Ortore, G.; Caligiuri, I.; Rizzolio, F.; Ceni, C.; Bertini, S.; Bononi, G.; Granchi, C.; Macchia, M.; Poli, G.; Tuccinardi, T. Machine learning-based virtual screening for the identification of Cdk5 inhibitors.  Int. J. Mol. Sci. 2022, 23, 10653.

This research project is funded by Tuscany Region (Bando Ricerca Salute 2018, DEM-AGING)

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