Dereplicator is a computational tool developed for identification of known natural products from LC/MS-MS data. Given a database of chemical structures, Dereplicator generates in-silico mass spectra of compounds by predicting how they fragment during mass spectrometry, and combines them to experimental LC/MS-MS and detects similarities. The similarity score is converted to a statistical significance, and significant matches are reported.

You can try Dereplicator workflow online at GNPS website (registration is needed but it is quick and simple). See documentation for details.

Example of Dereplicator output on the whole publicly available GNPS data is here and its manual curation and evaluation is here.

The tool is developed in collaboration with University of California, San Diego.


Please cite the following if you are using Dereplicator:

Hosein Mohimani, Alexey Gurevich, Alla Mikheenko, Neha Garg, Louis-Felix Nothias, Akihiro Ninomiya, Kentaro Takada, Pieter C. Dorrestein, Pavel A. Pevzner,
Dereplication of Peptidic Natural Products Through Database Search of Mass Spectra,
Nature Chemical Biology (2016). doi: 10.1038/nchembio.2219
First published online: October 31, 2016