Classification, clustering, and scaffold-based fingerprints are possible applications that can be used in a second step for picking diverse training and test sets for machine learning models for example . The concept of scaffolds and parent scaffolds as characteristic molecular fragments of molecules can help in the development of QSAR/QSPR models or computerassisted structure elucidation. Applied to NP, scaffolds can serve as starting points for the creation of pseudo-NP that are regarded as promising candidates for new drug molecules . Additionally, the study of macrocyclic structures in NP with existing scaffold methodologies and the development of new, specialised approaches for these structures are promising ways of identifying new drug candidates .