Fungal secondary metabolites represent a valuable resource for drug discovery pipelines. Numerous front-line therapeutics arise from unique cytostatic, immunosuppressant, lipid-lowering, and antimicrobial compounds encoded in untapped biosynthetic gene clusters (BGCs) and hidden in complex fungal metabolomes. Advances in high-throughput screening, computational genome mining, and synthetic biology have allowed to effectively dissect biosynthetic pathways whose products are likely to have desired bioactivities, identify resistance genes associated with potential targets, and engineer chosen gene clusters into a heterologous host for large-scale metabolite production. Yet, accurately assessing small bioactive molecules from complex fungal extracts remains challenging. Due to the need for high-throughput methods for discovering new molecules, we have redesigned untargeted workflows that combine large-scale metabolomics measurements using liquid chromatography-tandem mass spectrometry (LC-MS2) with computational solutions for data analysis and bioassays. Our approach incorporates mass spectral networks, orthogonal annotation tools built on existing technologies, and gas-phase fragmentation mapping. Utilizing tandem MS-based metabolomics, cell-based assays, and bioinformatics, we aim to speed up biological sample exploration and enable the discovery of novel compounds with novel mechanisms of action.