Streamlined Discovery of Antifungal Compounds in Costa Rican Piper Species Using Weighted Gene Correlation Network Analysis of crude 1H NMR Data

The discovery of bioactive natural products is hindered by bottlenecks encountered during the isolation, characterization, and confirmation of the active compounds. We have applied a weighted gene correlation network analysis (WCGNA) to identify groups of 1H resonances associated with bioactivity directly from crude 1H NMR spectra of metabolites extracted from various Piper species from Costa Rica. Our screening of 30 methanolic leaf extracts against S. cereviseae revealed that three Piper species produce compounds that exhibit prominent antifungal activity. By incorporating known structural motifs into the 1H NMR networks of crude extracts, we could approximate general structural types of some of the bioactive compounds during the initial phases of this targeted approach. Using unique resonances that correlated with antifungal activity, we isolated and characterized four novel compounds, three of which were identified as the active antifungal components of the mixtures. Subsequent growth inhibition assays with purified or synthetic compounds validated their efficacy, demonstrating the potential of this approach. Overall, this method reduces the need for repeated biological assessments of fractions in a traditional bioassay-guided isolation, making it a streamlined approach to identify bioactive natural products that can be used in a variety of applications.