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MOOT NMR Symposium

October 26-27, 2019
University of Ottawa, Ottawa, ON, Canada



Efficient Approaches for Addressing Spectral Ambiguities in Computer Assisted Structure Elucidation (CASE) Systems
Jessica Litman, Rostislav Pol, Mikhail Elyashberg, Sergey Golotvin and Dimitris Argyropoulos

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Efficient Approaches for Addressing Spectral Ambiguities in Computer Assisted Structure Elucidation (CASE) Systems

Jessica Litman, Rostislav Pol, Mikhail Elyashberg, Sergey Golotvin and Dimitris Argyropoulos

Advanced Chemistry Development, Toronto, ON, Canada

Since their development over 50 years ago, Computer Assisted Structure Elucidation (CASE) systems (or Expert Systems, ES) have significantly facilitated the de novo structure elucidation of both natural and synthesized organic compounds, especially in cases where using the traditional (manual) methods would has been very challenging or even impossible to perform [1,2].  Current ES are based on 1D and 2D NMR spectra, given that the molecular formula has already been determined by HR-MS.  At present, there are several free and commercially available CASE systems offering the following main advantages [3]: i) ES deliver all (without any exception) structures which can be deduced from a given set of NMR data; ii) Application of fast empirical methods for NMR chemical shift prediction allows the program to select the most probable structure; iii) If necessary, DFT based chemical shift calculations are used to confirm the selected structure; iiii) ES are now capable of suggesting a 3D model of the elucidated structure.

Despite all the developments, ES are still susceptible to a series of limitations which impede structure elucidation by a human expert.  These limitations are mainly associated with the ambiguity of the experimental data, as well as the overlapping characteristic chemical shift values in NMR spectra.  Experimental ambiguity can result from low resolution 2D spectra, which prohibits the confident assignment of the closely spaced signals.  Further, ambiguity can often be due to the hybridization state of carbon nuclei that appear in the same regions of NMR spectra.  For example, a 13C NMR signal observed at 90 ppm can belong either to a sp2 or a sp3-hybridized carbon connected to one or two oxygen atoms.  If a molecule contains atoms that can have variable valences (e.g., N and/or P), all their possible valences should be explored during structure generation.  Ambiguity can also be observed in some cases where carbon nuclei show no HMBC or COSY correlations; this is especially evident in molecules with hydrogen deficiency which consequently appear as "floating", i.e., potentially could be connected to any other atom.  The presence of "floating" atoms significantly increases both the size of the output and the time of structure generation.

In order to remove uncertainty from spectroscopic data, additional experiments are usually carried out; for example high resolution 2D NMR spectra, such as highly inflated NUS or band selective spectra are collected to reliably assign the correlations.  Additional spectroscopic data (IR, Raman, UV-Vis) could help to identify the characteristic groups and resolve the hybridization or valence status.  However, such solutions are not useful in all cases.

In such cases, the only remaining solution is the exhaustive investigation of all alternatives ensuing from the presence of any ambiguity.  For example, if there are five carbon nuclei with signals in the range of 70-120 ppm, then 25=32 combinations of hybridization (sp3 or sp2) have to be generated and checked. This could significantly extend the structure generation time.

A typical Molecular Connectivity Diagram from a CASE ES:  Dotted lines represent ambiguous correlations, cyan carbon atoms are of either sp3 or sp2 hybridization, several
Figure 1: A typical Molecular Connectivity Diagram from a CASE ES:  Dotted lines represent ambiguous correlations, cyan carbon atoms are of either sp3 or sp2 hybridization, several "floating" atoms are visible.

In this poster by taking advantage of recent programming developments, we will present approaches that enable structure elucidation, under conditions where the initial data contains many ambiguous assumptions.  Examples will be presented, and the strengths together with the limitations of each approach will be discussed.

[1] Blinov, K.A.; Elyashberg, M.E.; Martirosian, E.R.; Molodtsov, S.G.; Williams, A. J.; Sharaf, M. M. H.; Schiff, P. L. Jr.; Crouch, R.C.; Martin, G. E.; Hadden, C.E.; Guido J.E.; Mills, K.A., Quindolinocryptotackieine: the Elucidation of a Novel Indoloquinoline Alkaloid Structure Through the Use of Computer-Assisted Structure Elucidation and 2D NMR.  Magn. Reson. Chem., 41, 577-584 (2003)

[2] M.E. Elyashberg, K.A. Blinov, S.G. Molodtsov, A.J. Williams., Elucidating "Undecipherable" Chemical Structures Using Computer Assisted Structure Elucidation Approaches, Magn. Reson. Chem., 2012, 50, 22-27

[3] M. Elyashberg, D. Argyropoulos. NMR-based Computer-assisted Structure Elucidation (CASE) of Small Organic Molecules in Solution: Recent Advances. eMagRes, 2019, Vol 8: 1–16. DOI 10.1002/9780470034590.emrstm1618.