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. 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 > 0.1.1. 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.