Molecular Networking as a Dereplication Strategy

TLDR

A major goal in natural product discovery programs is to rapidly dereplicate known entities from complex biological extracts. We demonstrate that molecular networking, which organizes MS/MS data by chemical similarity, is a powerful complement to traditional dereplication strategies. The method uses MS/MS spectra from mixtures and known standards or well‑characterized organisms, organized in robust databases, and can integrate data from ambient ionization, direct infusion, and LC platforms to enable cross‑correlation of spectra. Molecular networking dereplicates known compounds and captures related analogues, successfully identifying 58 molecules—including analogues—from diverse marine and terrestrial microbial samples.

Abstract

A major goal in natural product discovery programs is to rapidly dereplicate known entities from complex biological extracts. We demonstrate here that molecular networking, an approach that organizes MS/MS data based on chemical similarity, is a powerful complement to traditional dereplication strategies. Successful dereplication with molecular networks requires MS/MS spectra of the natural product mixture along with MS/MS spectra of known standards, synthetic compounds, or well-characterized organisms, preferably organized into robust databases. This approach can accommodate different ionization platforms, enabling cross correlations of MS/MS data from ambient ionization, direct infusion, and LC-based methods. Molecular networking not only dereplicates known molecules from complex mixtures, it also captures related analogues, a challenge for many other dereplication strategies. To illustrate its utility as a dereplication tool, we apply mass spectrometry-based molecular networking to a diverse array of marine and terrestrial microbial samples, illustrating the dereplication of 58 molecules including analogues.