Bioactive Natural Products Identification Using Automation of Molecular Networking Software

J Chem Inf Model. 2022 Dec 26;62(24):6378-6385. doi: 10.1021/acs.jcim.2c00307. Epub 2022 Aug 10.

Abstract

Secondary metabolites from natural sources are promising starting points for discovering and developing drug prototypes and new drugs, as many current treatments for numerous diseases are directly or indirectly related to such compounds. Recent advances in bioinformatics tools and molecular networking methods have made it possible to identify novel bioactive compounds. In this study, a workflow combining network-based methods for identifying bioactive compounds found in natural products was streamlined by innovating an automated bioinformatics software. The workflow relies on Global Natural Product Social Molecular Networking (GNPS), a web-based mass spectrometry ecosystem that aims to be an open-access knowledge base for community-wide organization and sharing of raw, processed, or annotated fragmentation mass spectrometry data. By combining computational tools including MZmine2, GNPS, and Cytoscape, the integrated dashboard quickly creates bioactive molecular networks with minimal user intervention and reduces the processing time of the original workflow by over 80%. This newly automated workflow quickens the process of discovering bioactive compounds from natural products. This study uses extracts from Psidium guajava leaves to demonstrate the application of our automated software.

MeSH terms

  • Automation
  • Biological Products* / chemistry
  • Ecosystem
  • Mass Spectrometry
  • Software

Substances

  • Biological Products