De novo Discovery of Natural Products Using Progenesis QI and Natural Product Atlas Library

Importance of the Topic

Natural product discovery remains a cornerstone of pharmaceutical and biomedical research due to its proven track record in yielding novel bioactive compounds. Complex mixtures found in botanical, microbial, and marine extracts challenge analytical chemists to develop robust workflows that can separate, detect, and characterize unknown molecules with high confidence. Combining high-resolution mass spectrometry with informatic libraries accelerates de novo identification and streamlines the path from crude extract to compound annotation.

Objectives and Study Overview

This application note outlines an integrated workflow that pairs liquid chromatography–ion mobility–high resolution mass spectrometry (LC–IM–HRMS) with Progenesis QI software and the Natural Products Atlas library. The primary goals are to demonstrate automated batch searching, confident compound annotation, and custom library creation for ongoing natural product research.

Methodology and Instrumentation

Extracts showing biological activity undergo chromatographic fractionation on an ACQUITY UPLC system. Separation is followed by data capture on a quadrupole time-of-flight instrument, either a SYNAPT XS with ion mobility (HDMSE mode) or a Xevo G2-XS in MSE mode. The workflow captures precursor and fragment ion exact masses, retention time (RT), and, when available, collisional cross section (CCS). Progenesis QI imports raw data, aligns runs, and performs automatic database searches against the NP Atlas library based on accurate mass tolerance, isotopic pattern matching, theoretical fragmentation, RT, and CCS parameters.

Instrumentation Used

• ACQUITY Premier UPLC I-Class PLUS System for high-resolution chromatographic separation
• SYNAPT XS High Resolution Mass Spectrometer with ion mobility enabled data independent acquisition (HDMSE)
• Xevo G2-XS Q-Tof High Resolution MS for MSE acquisition when ion mobility is not employed
• Progenesis QI software for data processing and library searching

Main Results and Discussion

Using NP Atlas as a searchable database within Progenesis QI, the workflow successfully identified erythromycin G in complex microbial extracts by matching precursor mass, fragment ions, and isotope similarity. Exporting this result into a custom library retained experimentally derived spectra, RT, and CCS, enabling rapid annotation of subsequent samples. Searches against the custom library leveraged five orthogonal parameters, greatly increasing identification confidence. Hyperlinks to the NP Atlas web portal and integration with GNPS provided seamless routes for cluster and molecular network analysis.

Benefits and Practical Applications

• Accelerated compound identification via batch searching against a tailored NP Atlas library
• Improved confidence through multi-parameter scoring (mass accuracy, isotope similarity, RT, fragmentation, CCS)
• Flexible database creation to capture in-house experimental spectra for future studies
• Direct linkage to external tools (GNPS, MIBiG) for extended dereplication and network analysis

Future Trends and Applications

Future developments may include expansion of curated spectral libraries to encompass broader taxonomic origins, integration of machine learning for predictive fragmentation, and enhanced cloud-based collaboration for real-time library updates. Improvements in ion mobility resolution and software algorithms will further empower structure elucidation in ultra-complex matrices.

Conclusion

The described workflow demonstrates a streamlined approach for de novo natural product discovery by coupling LC–IM–HRMS with Progenesis QI and the Natural Products Atlas. Automated database searching, custom library creation, and multi-parameter scoring significantly reduce the time and effort required for confident compound annotation, thereby facilitating faster progression from extract to bioactive lead.

Reference

1. van Santen JA, Jacob G, Singh AL, Aniebok V, Balunas MJ, Bunsko D, Carnevale Neto F, et al. The Natural Products Atlas: An Open Access Knowledge Base for Microbial Natural Products Discovery. ACS Cent Sci. 2019;5(11):1824–33. DOI:10.1021/acscentsci.9b00806.