Open AccessBurning the Hay to Find the Needle – Data Mining Strategies in Natural Product Dereplication
Author(s) -
Dietmar Wolf,
Karsten Siems
Publication year - 2007
Publication title -
chimia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.387
H-Index - 55
eISSN - 2673-2424
pISSN - 0009-4293
DOI - 10.2533/chimia.2007.339
Subject(s) - ranking (information retrieval) , natural product , product (mathematics) , computer science , cluster analysis , data mining , chemistry , chromatography , information retrieval , mathematics , artificial intelligence , stereochemistry , geometry
The acquisition and use of data from the LC/MS-ELSD analysis of extracts is described. The methodology requires MS spectra to be recorded in the positive/negative ESI mode, as well as the determination of retention time and peak area from ELSD. Subsequent calculation of molecular weight, referenced retention time, and normalized peak area, results in the creation of a peak library, which can be used for different data mining strategies: i) the dereplication of previously isolated natural products; ii) clustering/ranking of extracts for the creation of highly diverse natural product libraries; iii) a selection tool for the focused isolation of bioactive natural products and iv) to search for alternative sources of a target natural product.