Effective tools are needed to enable prioritization of lead molecules in natural products drug discovery research. As the field of mass spectrometry continues to advance, more people have access to high-resolution instruments, and more researchers rely on this technology for metabolite and compound class identification. To effectively access lead molecules from natural product mixtures, it is important to comprehensively assess large datasets in the most timely and cost-effective manner. For analyses based on liquid chromatography-mass spectrometry (LC-MS), several post-acquisition data analysis approaches can be employed to identify analogues of a lead molecule of interest. With this study, we sought to compare the effectiveness of mass defect filtering and molecular networking for this purpose. Secondary metabolite production by the ambuic acid-producing endophytic fungus Pestalotiopsis microspora was used as a test case for these analyses. Eight putative analogues of ambuic acid were identified using mass defect filtering and molecular networking analyses. Our results illustrate advantages and disadvantages of molecular networking and mass defect filtering and suggest that the combination of both data mining techniques may enable the most comprehensive evaluation of analogues.