FGMR

September 25-28, 2017

University of Bayreuth, Bayreuth, Germany
RWI Building

Meet ACD/Labs Staff

Sergey Golotvin

Rostislav Pol

Poster Schedule

Generating Unbiased Structural Alternatives for Automated Structure Verification
Sergey Golotvin, Rostislav Pol, Mikhail Elyashberg, Dimitris Argyropoulos, Karim Kassam
Session: Small molecules/Honogeneous catalysts

Abstract: Automated structure verification (ASV) using NMR data is gaining acceptance as a routine application for qualitative evaluation of large compound libraries produced by synthetic chemistry. A proposed structure is confirmed if it fits a number of conditions from 1D 1H NMR data, or from a combination of 1D-1H and HSQC data.1

Although it is easy to conclude that a proposed structure does not pass this "NMR filter" it is not trivial to guarantee the opposite—that a proposed structure passing this filter is the correct one. There is always a possibility that an isomeric structure fits the same NMR data better than the proposed structure. One way to decrease the possibility that false structures will pass is to use as many NMR experiments as possible for structure validation (1D-13C, HMBC, etc.). Another method is to bring in and simultaneously verify several structures isomeric to the proposed.2 This concurrent structure verification enables structural differences to be highlighted through gradual tightening of NMR prediction tolerances until only a single structure remains.

The similarity of isomeric structures to the proposed structure means that spectral interpretation is biased by the chemist's expectations and may result in false positives.

We present here a method of generating alternative 'unbiased' structures for ASV based on the structure generator used in a CASE system.3 Using this approach we are able to generate all the isomers that fit the particular NMR dataset without using any prior available knowledge. Practical aspects of this 'unbiased' verification are discussed and several examples are shown.

(1) Golotvin SS.; Vodopianov E.; Pol R.; Lefebvre B.A.; Williams A.J.; Rutkowske R.D.; Spitzer T.D. (2007). Mag. Res. Chem. 45(10): 803-813.
(2) Golotvin SS.; Pol R.; Sasaki R.R.; Nikitina A.; Keyes P. (2012). Mag. Res. Chem. 50(6): 429-435.
(3) Elyashberg M. E.; Williams A. J.; Blinov K.A. "Contemporary computer-assisted approaches to molecular structure elucidation", RSC, Cambridge, 2012.

Computer Assisted Structure Elucidation of Preussilides A-F, Bicyclic Polyketides from the Endophytic Fungus Preussia similis
Soleiman E. Helaly, Sara R. Noumeur, Rolf Jansen, Marcus Gereke, Theresia E.B. Stradal, Daoud Harzallah, Marc Stadler, Dimitris Argyropoulos, Tim Salbert
Session: Small molecules/Honogeneous catalysts

Abstract: Six novel bioactive bicyclic polyketides (1-6) were isolated from cultures of an endophytic fungus of the medicinal plant Globularia alypum collected in Batna, Algeria1. The producer organism was identified as Preussia similis using morphological and molecular phylogenetic methods. The structures of metabolites 1-6, for which the trivial names preussilides A-F are proposed, were elucidated using a combination of high resolution mass spectrometry, NMR spectra, a Computer Assisted Structure Elucidator system2 and CD spectroscopy.

Preussilides A-F
Figure 1: Preussilides A-F (1-6)

Preussilides were tested for antimicrobial and antiproliferative effects and, in particular, compounds 1 and 3 showed selective activities against eukaryotes. Here we describe the advanced computational method used for elucidating the structures using a series of 1D and 2D NMR experiments.

(1) Noumeur, S. R.; Helaly, S. E.; Jansen, R.; Gereke, M.; Stradal, T. E. B.; Harzallah, D.; Stadler, M. (2017). J. Nat. Prod. 80: 1531–1540.
(2) Elyashberg M. E.; Williams A. J.; Blinov K.A. “Contemporary computer-assisted approaches to molecular structure elucidation”, RSC, Cambridge, 2012.