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September 16-19, 2018
Philadelphia 201 Hotel, Philadelphia, PA, USA

Related Materials

Related presentations, posters, and scientific talks from this event have been posted here for your reference. Please click the associated link to download.

A New Method for the Reliable Detection of 13C Multiplets of Fluorine Containing Compounds, D. Argyropoulos, R. Pol, V. Mikhailenko, and S. Golotvin

ACD/Labs NMR Software Symposium at SMASH

SUNDAY, SEPT. 16th, 1:30–4:00 PM
Philadelphia 201 Hotel, Room: Liberty B

Time Details
1:30–1:40 PM Introductions & Welcome
1:40–2:00 PM Reflecting on 20 Years of ACD/Structure Elucidator: What CASE has Accomplished and What Lies Ahead
Jessica Litman, ACD/Labs
2:00–2:20 PM Implementing Tools for Automated Structure Verification at AMGEN
Stephan Zech, Amgen
2:20–2:40 PM Exciting Features in V.2018: Automated C-F multiplet analysis, enhanced mixture analysis, and more
Arvin Moser, ACD/Labs
2:40–3:00 PM Analytical Workflows in Pharmaceutical Discovery & Development
Steven Coombes, AstraZeneca
3:00–3:20 PM Using Open Resources and Predicted 13C NMR Spectra for Structure Dereplication
Dimitris Argyropoulos, ACD/Labs
3:20–3:40 PM NMR Macro Applications and Development Using ACD/Labs Software For Analytical Research Support of Small Molecule Products within Koch Industries, Inc.
Cindy Dozier, Invista
3:40–4:00 PM Questions and Follow-up Discussion

ACD/Labs Presence at SMASH


MONDAY, SEPT. 17TH, 2:00–3:30 PM

Workshop I: CASE—Computer Aided Structural Elucidation
Chair: Armando Navarro (Federal de Pernambuco)
Participants: Arvin Moser (ACD/Labs) and Pavel Kessler (Bruker Biospin)

Liberty Ballroom A&B

Arvin Moser (ACD/Labs) will present on the following:
Advances in NMR hardware, pulse sequences, computer hardware, and expert systems led to the evolution of several commercial and open-source Computer-Assisted Structure Elucidation (CASE) software packages. CASE software is capable of successfully deducing the chemical constitution of complex natural and synthetic products with minimum human intervention. Using a CASE software system to elucidate the structure of an unknown compound can be likened to using a mathematical calculator for solving a math problem. Additionally, the application of CASE can strengthen a chemists’ elucidation skills.

This interactive workshop will discuss:

  1. Sample preparation and experiment choice amongst the multitude of options available in modern 1D and 2D NMR, such as 1H-13C and 1H-15N direct and long range correlation experiments and 2D-ADEQUATE and INADEQUATE
  2. Selected examples comparing the different approaches for CASE and manual elucidation
  3. Recommendations for the interpretation of experimental NMR data and deducing possible fragments
  4. Searching NMR databases for known fragments and applying filters to narrow down candidates
  5. The application of NMR chemical predictors, strategies for dealing with overlapping and/or absent signals in NMR spectra
  6. The impact of CASE algorithms within the generation workflow
  7. Extension to the determination of three-dimensional structure (CASE-3D) using either empirical predictions, quantum mechanical calculations (DFT) and/or NOE, NOESY and RDC spectra

Questions and discussions are welcome from participants during the workshop.

Poster Presentations

A New Method for the Reliable Detection of 13C Multiplets of Fluorine Containing Compounds
Dimitris Argyropoulos, Rostislav Pol, Vladimir Mikhailenko and Sergey Golotvin
Poster #: 57
Read Abstract

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

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. These 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. 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 excessive power that would be required. Consequently, this approach is not considered practical for routine use.

Expansion of the <sup>1</sup>H decoupled <sup>13</sup>C spectrum of 1,2,3-Trichloro-5-(trifluoromethyl)benzene, indicating the overlapping multiplets due to the 19F-<sup>13</sup>C 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. 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. (2011). Nature's building blocks: An A–Z guide to the elements (2nd ed.). Oxford University Press.
  2. Swinson, Joel. (2005). Fluorine-A vital element in the medicine chest. PharmaChem., 4: 26–27.

Using Predicted 13C NMR Spectra with Open Resources for Structure Dereplication of Natural Products
Dimitris Argyropoulos, Sergey Golotvin, Rostislav Pol, Arvin Moser, Nico Ortlieb, Steffen Breinlinger, Tomasz Chilczuk and Timo H. J. Niedermeyer
Poster #: 58
Read Abstract

Using Predicted 13C NMR Spectra with Open Resources for Structure Dereplication of Natural Products
Dimitris Argyropoulos1, Sergey Golotvin1, Rostislav Pol1, Arvin Moser1, Nico Ortlieb2, Steffen Breinlinger2, Tomasz Chilczuk2 and Timo H. J. Niedermeyer2

  1. Advanced Chemistry Development, Toronto, ON, 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. (2016). PubChem Substance and Compound databases. Nucleic Acids Res., 44(D1): 1202-1213.
  2. Data presented by Burkhard Kirste, FU Berlin, 38th FGNMR Meeting, Sept. 2016, Dusseldorf.