Improvement of molecular networking using in silico fragmentation and subnetwork storage and search

Abstract

Molecular networking combined with a large fragmentation database has a broad range of applications to natural products community. However, the compound identification is hampered by limitations on the chemical space coverage of fragmentation databases. Recent advances on in silico fragmentation have shown the potential to predict fragmentation spectrum from compound structure libraries, that can be matched against experimental spectrum. The fusion of molecular networking, spectral database matching and in silico fragmentation matching can extend the applications of networking beyond the known chemical space. Once we achieve a comprehensively annotated molecular network, expert knowledge for network manual inspection is still require. This project aims to create a simple proof of concept application, that can add in silico fragmentation annotation to the molecular network generated by GnPS, and search subnetworks created and stored by users. The ability of store annotated network signatures on large network can further impact on several applications and accelerate the understanding of metabolism. (AU)