60th Experimental Nuclear Magnetic Resonance Conference (ENC), April 7-12, 2019 | ACD/Labs
ACD Labs Logo
MENU

60th Experimental Nuclear Magnetic Resonance Conference (ENC)

April 7-12, 2019
Asilomar Conference Center, Pacific Grove, CA, USA



ACD/Labs NMR Software Symposium

Sunday, April 7th, 1:30–4:00 PM PST

Asilomar Conference Center, Nautilus Room

Please join us for our NMR Software Symposium at ENC in Asilomar. Our presentation schedule features talks from customers at Amgen and the University of Toronto. The full agenda can be seen below:

Time Topic
1:30–1:40 Introductions and Welcome
1:40–1:50 25 Years of ACD/Labs—Accelerating Innovation, Leveraging Knowledge, and Enhancing Collaboration
Sanji Bhal, ACD/Labs 
1:50–2:10 The Evolution of CASE—How it has Broadened the Reach of NMR Analysis Techniques
Jessica Litman, ACD/Labs
2:10–2:30 A CASE (Computer Assisted Structure Elucidation) Study for an Undergraduate Organic Chemistry Class
Amy Jenne, University of Toronto
2:30–2:50 The Latest Developments in Analysis Workflows and Chemical Knowledge Extraction
Brent Pautler, ACD/Labs
2:50–3:10 Implementing Tools for Automated Structure Verification at AMGEN
Chris Wilde, Amgen
3:10–3:30 Analysis of Fluorinated Compounds by 13C NMR: Addressing Difficulties and Providing Solutions
Dimitris Argyropoulos, ACD/Labs
3:30–3:50 Questions and Follow-up Discussion

Poster Sessions

Session: Solution and Small Molecules

Efficient Dereplication of Natural Products Using Predicted 13C Spectra
Poster #: 004
Dimitris Argyropoulos1, Sergey Golotvin1, Rostislav Pol1, Arvin Moser1, Nico Ortlieb2, Steffen Breinlinger2, Tomasz Chilczuk2 and Timo H. J. Niedermeyer2
View Abstract

Efficient Dereplication of Natural Products Using Predicted 13C Spectra

Dimitris Argyropoulos1, Sergey Golotvin1, Rostislav Pol1, Arvin Moser1, Nico Ortlieb2, Steffen Breinlinger2, Tomasz Chilczuk2 and Timo H. J. Niedermeyer2

1. Advanced Chemistry Development, Toronto, Canada
2. Institute of Pharmacy, RG Pharmacognosy, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany

For successful natural product-based drug discovery, it is critical to reliably separate and identify active components in natural product mixtures. Dereplication is the practice of screening active compounds early in the development process, to recognize and eliminate compounds that have been previously studied. This enables scientists to focus on testing truly ‘unknown’ compounds. For efficient dereplication, one must be able to easily identify characteristic spectral “fingerprints” of compounds in order to identify their structure and have access to databases containing known structures.

The 13C NMR spectrum of a compound can be considered a fingerprint since it is virtually unaffected by conditions such as pH, concentration, and solvent effects. It is also largely magnetic field independent, since there are no couplings that could cause variations in stronger or weaker fields. As a result, it is very easy and accurate to predict. To identify experimental 13C spectra, one can consider predicting the 13C spectra of known chemical structures found in “open” chemistry databases (e.g., PubChem[1]) and seeing if there is a match. Predicted spectra benefit from being magnetic field independent, can be adjusted for solvents, and can be very accurate if the correct algorithms are used [2].

Isolated compounds in natural product research are typically low in quantity, thus it may not be experimentally possible to acquire a 1D-13C spectrum. As a result, 13C information is often obtained from indirect detection experiments like HSQC and HMBC. The proposed dereplication method can be adopted to work with this data, providing a very valuable resource to natural products chemists. This presentation explores the possibilities and limitations of this novel technique and applies it to natural products from the fungus Ganoderma pfeifferi, cyanobacteria strains from the genera Nostoc and Cylindrospermum, and actimomycetes of the genus Streptomyces.

[1] Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, Han L, He J, He S, Shoemaker BA, Wang J, Yu B, Zhang J, Bryant SH., Nucleic Acids Res. 44, 1202-1213, 2016.

[2] Data presented by Burkhard Kirste, FU Berlin, 38th FGNMR Meeting, Sept. 2016, Dusseldorf

A New Method for the Reliable Detection of 13C Multiplets of Fluorine Containing Compounds
Poster #: 007
Dimitris Argyropoulos, Rostislav Pol, Vladimir Mikhailenko and Sergey Golotvin
View Abstract

A New Method for the Reliable Detection of 13C Multiplets of Fluorine Containing Compounds

Dimitris Argyropoulos, Rostislav Pol, Vladimir Mikhailenko and Sergey Golotvin

Advanced Chemistry Development, Toronto, Canada

In modern organic and medicinal chemistry, fluorine is commonly used to enhance the chemical properties of molecules in many desirable ways: it may delay the metabolism of the molecule due to the increased stability of the C-F bond, reduce the toxicity of aromatic groups by forbidding the formation of poisonous peroxides during metabolism, or increase the bioavailability due to the higher lipophilicity of the C-F bond vs the C-H bond. As a result, it is estimated that more than 20% of commercial pharmaceutical APIs and 30% of agrochemicals contain at least one fluorine atom [1,2].

In contrast to these benefits, the 13C NMR spectra of fluorinated organic compounds are highly susceptible to interpretation errors. This is because 13C spectra are commonly recorded using only 1H broadband decoupling and the 13C-19F couplings are still present. The 13C-19F coupling constants can be very large (up to 250 Hz or more), which may result in multiplets severely overlapping with other peaks in the spectrum. Additionaly, since 13C spectra inherently have low S/N, it is not uncommon that the lower (outer) parts of a multiplet are below the noise level and not visible. On top of these the carbon atoms connected to fluorine do not benefit from NOE signal enhancement from 1H broadband decoupling as much as those connected to protons are, reducing even further the observed signal intensity. To mitigate this, it is possible to record 13C spectra broadband decoupled from both 1H and 19F but this requires specialized NMR probes and decoupling techniques. Moreover the very broad range of 19F chemical shifts could pose a danger of damage to the probe due to the very high RF power that would be required. Consequently, this approach is not considered practical for general, routine use.

Expansion of the 1H decoupled 13C spectrum of 1,2,3-Trichloro-5-(trifluoromethyl)benzene, indicating the overlapping multiplets due to the 19F-13C couplings.

Figure 1: Expansion of the 1H decoupled 13C spectrum of 1,2,3-Trichloro-5-(trifluoromethyl)benzene, indicating the overlapping multiplets due to the 19F-13C couplings.

Here we present an analysis method that reliably peak-picks and identifies multiplets in the 13C spectra of organic compounds. This technique is based on accurately predicting the 19F coupled 13C spectrum of the proposed compound. Following prediction, we examine the regions of the experimental spectrum where the 19F coupled carbons are expected in order to identify multiplets by peak position and the agreement in the predicted and observed coupling constants, in essence pattern-matching the experimental to the predicted spectrum. Provisions are taken if only part of a multiplet is observed. We show that regardless of whether the final results contain multiple, overlapping multiplets, the expected carbon resonances are reliably identified and assigned for each spectrum. Typical examples from common fluorine containing compounds are shown.

[1] Emsley, John, “Nature's building blocks: An A–Z guide to the elements (2nd ed.)”, Oxford University Press, p. 178, 2011.

[2] Swinson, Joel, "Fluorine – A vital element in the medicine chest", PharmaChem. Pharmaceutical Chemistry: 26–27, 2005.

Applications of Multidimensional NMR Spectroscopy in the Characterization of Complex Environmental Samples
Poster #: 015
Darcy Fallaise1, Brent Pautler2, E. Erin Mack3, Carol Cheyne4, Julie Konzuk4, James Longstaffe1
View Abstract

Applications of Multidimensional NMR Spectroscopy in the Characterization of Complex Environmental Samples

Darcy Fallaise1, Brent Pautler2, E. Erin Mack3, Carol Cheyne4, Julie Konzuk4, James Longstaffe1

1. School of Environmental Sciences, University of Guelph, Guelph On, N1G 2W1
2. Advanced Chemistry Development (ACD/Labs), Toronto, Canada
3. DuPont Corporate Remediation Group, Newark DE, US
4. Geosyntec Consultants International, Toronto Ontario,

This poster describes the application of single and multidimensional NMR methods, including TOCSY, HSQC, and DOSY in the characterization of complex environmental samples collected from a site impacted with coal-tar contamination. Coal-tar contamination is challenging from an analytical standpoint. The combination of targeted analysis for priority contaminants and the non-targeted analysis for molecular size fractions often leaves a significant portion of the total mass uncharacterized. The challenges and benefits of using NMR as a non-targeted analytical method for these types of samples are discussed, including the use of 1D NMR as a rapid fingerprinting method to compare variations in the contaminant fingerprint across the site, the use of correlation experiments to identify specific structures present, with a focus on alkylated aromatic compounds, and the use of DOSY NMR to provide information on the size-distribution of compounds present in complex coal-tar samples coupled to non-targeted structural information in a single analysis.

1H DOSY of a Coal Tar sample.

Figure 1. 1H DOSY of a Coal Tar sample.

Session: Solution and * omics / Natural Products

A CASE (Computer Assisted Structure Elucidation) study for an undergraduate organic chemistry class
Poster #: 160
§Ronald Soong*, Brent G. Pautler, Arvin Moser, §Amy Jenne, §Tony Adamo, §Andre J. Simpson
View Abstract

A CASE (Computer Assisted Structure Elucidation) study for an undergraduate organic chemistry class

§Ronald Soong*, Brent G. Pautler, Arvin Moser, §Amy Jenne, §Tony Adamo, §Andre J. Simpson

§University of Toronto Scarborough, 1265 Military Trail, Toronto, Ontario, M1C 1A4

Advanced Chemistry Development Inc., (ACD/Labs), 8 King Street East, Suite 107, Toronto, Ontario,

Undergraduate organic chemistry courses offer students their first exposure to NMR spectroscopy as a tool for structure determination.1-4 With a plethora of available NMR experiments, organizing, analyzing, and understanding all the spectral data can be challenging at the undergraduate level.3,4  Since NMR spectroscopy is a powerful structure elucidation tool, developing an understanding of this instrument is ideal for a well-rounded education in chemistry. 1-4   Despite its importance as an analytical technique, many students find the principle behind NMR-facilitated structure determination difficult to embrace.  With the recent advances in computer technology, structure determination can be autonomously performed with minimal user inputs.4  Therefore, the incorporation of CASE (Computer Assisted Structure Elucidation) into the current chemistry curriculum can be a power teaching tools for NMR facilitated de novo structure elucidation.3,4  To this end, an Artificial Intelligence (AI) software package, namely ACD/Structure Elucidator, is used to facilitate the teaching of NMR spectroscopy principles and its application in de novo structure elucidation of large complex organic molecules in an upper level organic chemistry class.  For the purpose of demonstration, a set of standard multidimensional NMR spectra of quinidine will be used as an example, illustrating to students the potential of CASE as a tool for better understanding of NMR spectra.  This demonstration is complemented by a worksheet, which allows students to reflect on their findings and concepts at a later date, facilitating the process of autonomous learning. 

A depiction of the correlation mapping process between the resonances in A) HMBC, B) multiplicity-edited HSQC, C) 1D 1H NMR spectrum, and D) 1H-1H COSY of quinidine, leading to the construction of MCD (molecular connectivity diagram) shown in (E)

Figure 1.  A depiction of the correlation mapping process between the resonances in A) HMBC, B) multiplicity-edited HSQC, C) 1D 1H NMR spectrum, and D) 1H-1H COSY of quinidine, leading to the construction of MCD (molecular connectivity diagram) shown in (E).

[1] Winschel, G. A.; Everett, R. K.; Coppola, B. P.; Shultz, G. V; Lonn, S. J. Chem. Educ. 2015, 92 (7), 1188–1193.

[2] Treadwell, E. M.; Yan, Z.; Xiao, X. J. Chem. Educ. 2017, 94 (5), 640–643.

[3] Moser, A.; Pautler, B. G. Magn. Reson. Chem. 2016, 54 (9), 701–704

[4] Elyashberg, M. E. et. al. J. Nat. Prod. 2002, 65 (5), 693–703.