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.
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