Classifying protein kinase conformations with machine learning: data

This data collection accompanies the manuscript "Classifying protein kinase conformations with machine learning". It is created using the kinactive v0.1 tool written in pure Python v3.10. <strong>Note that the data are provided for the reference and reproducibility purposes and will not be compatible with later versions of `kinactive` built upon lXtractor &gt; 0.1.1.</strong> Refer to the kinactive documentation for instructions on how to obtain an actualized version of the structural kinome collection. File descriptions: db_v3.tar.gz -- a structural kinome collection archive. One can unpack it and inspect the contents or load it into the Python interpreter using `kinactive` or `lXtractor` tools. db_af2.tar.gz -- an AlphaFold2 kinome collection for Swiss-Prot sequences. default_*_vs.tsv -- structure/sequence variables calculated with lXtractor and used in an interpretable ML pipeline. *_features.tsv -- lists of ranked features selected by the eBoruta tool for each classifier. Supplement_labels.tsv -- ML model predictions for each PK domain structure found in db_v3. predictions_af2.csv -- Active/Inactive and DFG labels predicted for domains in db_af2.