Bioactive Natural Products Identification Using Automation of Molecular Networking Software

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.

Targeted Offline Two-Dimensional HPLC and UHPLC-Orbitrap-MS Combined with Molecular Networking Reveal the Effect of Processing on Chemical Constituents of Xuetong (the Stem of Kadsura heteroclita)

“…PCA analysis of the peak areas of all features (Figure S3) showed tight clustering of all QC samples, confirming the method's stability and reliability. While Global Natural Products Social Molecular Networking (GNPS, https://gnps.ucsd.edu, accessed on 28 February 2024) is commonly used for molecular network analysis [21,22], its limitations in data conversion, computational power, and compound recognition were encountered in this study. Specifically, GNPS failed to recognize triterpenoids and cluster them into a molecular network in this study.…”

Celebrating Diversity, Equity, Inclusion, and Respect in Computational and Theoretical Chemistry

“…The six compounds showed micromolar activity, and the binding analysis showed that the nitro-thiophene adopts a different binding mode than the nitro-furan compounds . In another study, Baskiyar et al present an automated workflow combining network-based methods and bioinformatics software that speed up the process for identifying bioactive compounds found in natural products that speeds the discovery …”