Molecular networks: An analysis on annotations and discovery of new assets

Abstract

To speed up the discovery of bioactive natural products (NP), chemists have sought advanced approaches in analytical and computational chemistry in attempt to organize and extract information from large data sets. In this sense, the molecular networks (MN) successfully organized enormous sets of mass spectrometry (MS) data together with samples metadata information in an intuitive visualization in the spectral similarity networks format. GNPS (Global Natural Products Social Molecular Networking), a free online platform for storing and processing MSn data, is a leading application of spectral matching with public databases aimed at the dereplication and discovery of new bioactive products through molecular networks. In this review, we address the concept of GNPS spectral similarity networks, as well as their complementary computational tools, benefits and limitations applied in NP studies associated with dereplication, chemical ecology, functional genetics and determination of biosynthetic pathways.