Optimization of LC-MS Data Acquisition Parameters for Molecular Networking Applied to Marine Natural Products.

Since the introduction of the online open-source GNPS, molecular networking has quickly become a widely applied tool in the field of natural products chemistry, with applications from dereplication, genome mining, metabolomics, and visualization of chemical space. Studies have shown that data dependent acquisition (DDA) parameters affect molecular network topology but are limited in the number of parameters studied. With an aim to optimize LC-MS parameters for integrating GNPS-based molecular networking into our marine natural products workflow, a design of experiment (DOE) was used to screen the significance of the effect that eleven parameters have on both Classical Molecular Networking workflow (CLMN) and the new Feature-Based Molecular Networking workflow (FBMN).