Morphing Libraries, models, and active predicted morphs for Glucocorticoid receptor

This Zenodo repository contains datasets and files related to the durg discovery research performed on the glucocorticoid receptor. Morphing Libraries: GRML_library.csv: A collection of virtual compounds created using Molpher and known GR active ligands. RML_library.csv: A collection of virtual compounds created using Molpher and random compounds from the ZINC database. Models: Model33.pkl: Python pickle file containing the trained Random Forest classification models used along with Mondrian cross-conformal prediction to classify GR actives/inactives. Active predicted morphs: all_morphs_actives_predicted.xlsx: An Excel spreadsheet containing two sheets. 1) All GRML active predicted morphs. 2) All RML active predicted morphs. Both sheets contain the QED, NIBR Severity Score, and Molskill Score. Researchers and professionals in the field of drug discovery and cheminformatics may find these resources useful for further analysis and investigations.