scikit-fingerprints/MoleculeACE_chembl204_ki
MoleculeACE ChEMBL204 Ki ChEMBL204 dataset, originally part of ChEMBL database [1], processed in MoleculeACE [2] for activity cliff evaluation. It is intended to be use through scikit-fingerprints library. The task is to predict the inhibitor constant (Ki) of molecules against the Prothrombin target. Characteristic Description Tasks 1 Task type regression Total samples 2754 Recommended split activity_cliff Recommended metric RMSE References… See the full description on the dataset page: https://huggingface.co/datasets/scikit-fingerprints/MoleculeACE_chembl204_ki.
MoleculeACE ChEMBL204 Ki
ChEMBL204 dataset, originally part of ChEMBL database [[1]](#1), processed in MoleculeACE [[2]](#2) for activity cliff evaluation. It is intended to be use through scikit-fingerprints library.
The task is to predict the inhibitor constant (Ki) of molecules against the Prothrombin target.
References
<a id="1">[1]</a> B. Zdrazil et al., “The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods,” Nucleic Acids Research, vol. 52, no. D1, Nov. 2023, doi: https://doi.org/10.1093/nar/gkad1004.
<a id="2">[2]</a> D. van Tilborg, A. Alenicheva, and F. Grisoni, “Exposing the Limitations of Molecular Machine Learning with Activity Cliffs,” Journal of Chemical Information and Modeling, vol. 62, no. 23, pp. 5938–5951, Dec. 2022, doi: https://doi.org/10.1021/acs.jcim.2c01073.