Cluster Analysis as Selection and Dereplication Tool for the Identification of New Natural Compounds from Large Sample Sets
Open Access
- 23 June 2006
- journal article
- research article
- Published by Wiley in Chemistry & Biodiversity
- Vol. 3 (6) , 622-634
- https://doi.org/10.1002/cbdv.200690065
Abstract
Cluster analysis of gas-chromatographic (GC) data of ca. 500 bacterial isolates was used as an aid in detection and identification of new natural compounds. This approach reduces the number of GC/MS analysis (dereplication) and concomitantly improves the selection of samples with high probability to contain unknown natural products. Lipophilic bacterial extracts were derivatized and analyzed by GC under standardized conditions. A program was developed to convert chromatographic data into a two-dimensional matrix. Based on the results of hierarchical cluster analysis samples were selected for further investigation by GC/MS and NMR. This approach avoided unnecessary analysis of similar samples. By this method, the unusual oligoprenylsesquiterpenes 1 and 2 as well as new aromatic amides 7 and 8 were identified.Keywords
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