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Automated Structure Verification: What are the Right Experiments and Processing?
EP23987
Automated Structure Verification: What are the Right Experiments and Processing?
Submitted on 25 Apr 2016

Sergey Golotvin1, Patrick Wheeler1, Phil Keyes2, Rostislav Pol1 and Gerd Rheinwald1
1Advanced Chemistry Development, Inc. (ACD/Labs), 8 King Street East, Suite 107, Toronto, ON, Canada, M5C 1B5 2Lexicon Pharmaceuticals, Princeton, New Jersey, USA
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Poster Abstract
Standard chemical structure characterization regularly employs a variety of 2D NMR techniques. However, past practice for the computer automation of this technique, Automated Structure Verification (ASV), primarily employs either 1D 1H NMR only, or a combination of 1D 1H NMR and 2D 1H-13C HSQC. Recent development makes the inclusion of a wide array of experimental data possible in fully automated structure verification work. The inclusion of expanded data types supports more accurate structure verification, decreasing the likelihood that false structures may pass through a verification process.

Recent experimental work has provided a rich array of experimental data on a large variety of structures for chemical samples that are derived from several sources. Included are 1D 1H, 1D 13C, 1D 13C DEPT, 1H-13C DEPT-edited HSQC, unedited 1H-13C HSQC, COSY, TOCSY, and HMBC data. Coupling the analysis of such data with the ability to create spectroscopically relevant challenge structures enhances the certainty of the chemist that they have synthesized the correct structure, and the confidence with which an organization can assume that the structure of any component in its library is completely correct.

1. Automated compound verification using 2D-NMR HSQC data in an open-access environment, Keyes, P., Hernandez, G., Cianchetta, G., Robinson, J., Lefebvre, B. Magnetic Resonance in Chemistry, Volume 47, Issue 1, pages 38-52, 2009.
2. Concurrent combined verification: reducing false positives in automated NMR structure verification through the evaluation of multiple challenge control structures, Golotvin, S., Pol, R., Sasaki, R., NikitinaA., Keyes, P. Magnetic Resonance in Chemistry, Volume 50, Issue 6, pages 429–435, 2012.
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