THIS PAGE IS PRELIMINARY AND UNDER CONSTRUCTION.
This site provides information about predicitve computational methodology for the identification of known natural products and assistance in the elucidation of congeners from 1H NMR spectral data.
The following publication reports on predictive computational methodology which utilizes classification binary trees (CBTs) for the dereplication of Actaea (syn./including Cimicifuga) triterpenes:
Qiu F, Imai A, McAlpine J, Lankin D, Burton I, Karakach T, Farnsworth N, Chen SN, Pauli GF
Dereplication, Residual Complexity and Rational Naming - the Case of the Actaea Triterpenes
Journal of Natural Products, 75: in press (2012) [http://dx.doi.org/10.1021/np200878s]
The software is currently not publically available.
Can you still use it? Yes. We are open to requests for ActaFinder runs on 3rd party data sets. Input consists of an organized list of assigned 1H chemical shifts of the compound in question, as per the above publication. Please send inquiries to the corresponding author.
The online version of The Ecdysone Handbook, 3rd edition (online), compiled by R. Lafon, J. Harmatha, F. Marion-Poll, L. Dinin, and I. Wilson, provides continuously updated information on over 450 ecdysteroids, including their UV, IR, MS, and NMR data
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