Mitja M Zdouc, Hannah E Augustijn, Nataliia V Machushynets, Lina M Bayona, Sylvia Soldatou, Niek F de Jonge, Sarah Casu, Marcel Jaspars, Gilles P van Wezel, Marnix H Medema, Justin J J van der Hooft
Many natural products can selectively modulate biological processes, making them prime candidates for drug discovery. However, the complexity of biological samples makes clear attribution of activity to molecules challenging, thereby hampering hypothesis-driven prioritization, with liquid chromatography-tandem mass spectrometry routinely detecting hundreds of molecules per sample. Existing biochemometric tools typically focus on facilitating data-driven exploration to support manual interpretation, rather than more objective, data-driven prioritization and hypothesis generation. Here, we introduce FERMO, a free online dashboard interface for biochemometrics-based prioritization of molecular features and samples. FERMO accepts qualitative and quantitative bioactivity assay data and further integrates group metadata and results from genome mining. FERMO performs automated data processing, organization, and annotation, supporting prioritization with the calculation of custom scores. FERMO supports both exploratory and targeted analysis through efficient interactive visualization, reproducible prioritization, and data filtering. We demonstrate FERMO's utility in benchmarking studies prioritizing bioactive natural products from complex biological matrices. FERMO is freely available at https://fermo.bioinformatics.nl/.