Visualizing diverse chemical families with molecular networking

Molecular networking (MN) is an analytical technique that relies on tandem mass spectrometry spectra to serve as a chemical finger print for molecular entities. MN has been shown to improve many areas of natural product workflows including dereplication, discovery, and unveiling environmental niche chemistries. Recently, we have gathered MS/MS data on a thousands of pure compounds received from the NIH, user contributed data to the Global Social Natural Products (gnps.ucsd.edu) library, Massbank, and ReSpect. We have used these library spectra to mine for discernable patterns in the MS/MS data, analogous to structural class identification using 1 H NMR. These patterns and other chemical trends have been explored to gather the maximum amount of information from a single MS/MS spectrum while simultaneously using various workflows on GNPS. Fig. 1: 1 H NMR (bottom) and MS/MS spectrum (top) for glycocholic acid, both indicative of a steroid core.