VersaDB is python-based program that first create a DB of natural products according to taxonomical criteria then predict MS/MS spectra and ¹³C NMR chemical shift to produce spectral DB ready for integration in dereplication workflows.

Abstract

Compound identification in complex mixtures by NMR and MS is best achieved through experimental databases (DB) mining. Experimental DB frequently show limitations regarding their completeness, availability or data quality, thus making predicted database of increasing common use. Querying large databases may lead to select unlikely structure candidates. Two approaches to dereplication are thus possible: filtering of a large DB before search or scoring of the results after a large scale search. The present work relies on the former approach. As far as we know, nmrshiftdb2 is the only open-source ¹³NMR chemical shift predictor that can be freely operated in batch mode. CFM-ID 4.0 is one of the best-performing open-source tools for ESI-MS/MS spectra prediction. LOTUS is a freely usable and comprehensive collection of secondary metabolites. Integrating the open source database and software LOTUS, CFM-ID, and nmrshiftdb2 in a dereplication workflow requires presently programming skills, owing to the diversity of data encoding and processing procedures. A graphical user interface that integrates seamlessly chemical structure collection, spectral data prediction and database building still does not exist, as far as we know. The present work proposes a stand–alone software tool that assists the identification of mixture components in a simple way.