The structure of PythiaCHEM is illustrated in Figure . In the following paragraphs, we briefly explain the purpose of each notebook, with detailed descriptions available in the SI S1. Notebook 2: Classification-Fingerprints. This notebook focuses on binary classifica-tion scenarios using fingerprints. Various fingerprint options are available, including Morgan fingerprints, RDKit fingerprints, 46 MACCS keys, 66 atom pair fingerprints, and torsion fingerprints. It handles the removal of features represented as 0 across all fingerprint bits.