Planta Med 2019; 85(18): 1414-1415
DOI: 10.1055/s-0039-3399703
Abstracts of Short Lectures
Short Lectures Tuesday, September 03, 2019
Short Lectures E: Applied NMR Session
© Georg Thieme Verlag KG Stuttgart · New York

Eliciting Nature’s Activities (ELINA): a biochemometric approach to unravel complex bioactive mixtures

U Grienke
1   Department of Pharmacognosy, Faculty of Life Sciences, University of Vienna, Althanstraße 14, 1090 Vienna, Austria
,
P Foster
2   Institute of Metabolism and Systems Research, University of Birmingham,Birmingham B15 2TT, United Kingdom
3   Centre for Endocrinology, Diabetes, and Metabolism, Birmingham Health Partners, Birmingham, United Kingdom
,
J Zwirchmayr
1   Department of Pharmacognosy, Faculty of Life Sciences, University of Vienna, Althanstraße 14, 1090 Vienna, Austria
,
A Tahir
1   Department of Pharmacognosy, Faculty of Life Sciences, University of Vienna, Althanstraße 14, 1090 Vienna, Austria
,
JM Rollinger
1   Department of Pharmacognosy, Faculty of Life Sciences, University of Vienna, Althanstraße 14, 1090 Vienna, Austria
,
E Mikros
1   Department of Pharmacognosy, Faculty of Life Sciences, University of Vienna, Althanstraße 14, 1090 Vienna, Austria
4   Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Athens, Panepistimiopolis Zografou, Athens, Greece
› Author Affiliations
Further Information

Publication History

Publication Date:
20 December 2019 (online)

 

Although bio-guided isolation is a well-established method for the discovery of bioactive compounds from natural sources, it has many drawbacks, e.g. it is tedious, time-consuming, and not always successful. To improve this, biochemometric approaches have emerged in recent years. However, hit discovery from a complex extract containing close structural analogues remains challenging.

Hence, the aim of this work was to unravel a complex bioactive mixture of the same compound class. This was achieved by a 1H NMR-MS workflow which we named ELINA (Eliciting Nature’s Activities) [1]. ELINA detects chemical features that are positively (‘hot’) or negatively (‘cold’) correlated with bioactivity prior to any isolation. The approach is exemplified in the discovery of steroid sulfatase (STS) [2] inhibiting lanostane triterpenes (LTTs) from the polypore fungus Fomitopsis pinicola Karst.

To reduce the complexity of the extract, a single fractionation step was performed to give 32 fractions. This was done in a way to achieve varying concentrations of a constituent over several fractions. Aliquots of all fractions were forwarded to 1H NMR, LC-HRESIMS, and bioactivity testing. Using statistical heterocovariance analysis (HetCA) [3], 1H NMR spectra were correlated with bioactivity data and complemented with MS data.

The effectiveness of this approach was demonstrated by disclosing chemical features crucial for STS inhibition, thus taking advantage from the innate compound library produced by the polypore’s biosynthetic machinery. As a proof of concept piptolinic acid D and pinicolic acid B equipped with these imperative features were isolated and showed IC₅₀s of 10.5 µM and 12.4 µM, respectively [1].

Zoom Image
Fig. 1
 
  • References

  • 1 Grienke U, Foster PA, Zwirchmayr J. et al. 1H NMR-MS-based heterocovariance as a drug discovery tool for fishing bioactive compounds out of a complex mixture of structural analogues. Sci Rep 2019. doi: DOI:10.1038/s41598-019-47434-8.
  • 2 Mueller JW, Gilligan LC, Idkowiak J. et al. The regulation of steroid action by sulfation and desulfation. Endocr Rev 2015; 36: 526-563.
  • 3 Aligiannis N, Halabalaki M, Chaita E. et al. Heterocovariance based metabolomics as a powerful tool accelerating bioactive natural product identification. ChemistrySelect 2016; 1: 2531-2535.