Stemming from these observations, the aim of this study is to comprehensively compare and evaluate how different types of molecular fingerprints perform for modeling the NP chemical space, and ultimately to (a) provide effective recommendations to cheminformatics practitioners in the field of NPs, and (b) underscore future directions for the development of molecular fingerprints. We systematically compared 20 different molecular fingerprinting algorithms from four packages, on two cheminformatics tasks. First, we evaluate the similarity of fingerprints encoding using the COCONUT database, containing over 400,000 unique NPs from 52 different sources, and a wide variety of organisms, geographic locations and applications. Then, we evaluated the selected fingerprints for quantitative structure-activity relationship (QSAR) modeling, using 13 datasets from the CMNPD database. The diverse fingerprint behavior in similarity searches and QSAR modelling using NPs allowed us to shed on their effect in representing the chemical space of natural products.