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Updated: Jun 28, 2026
09:19
NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode
Published on: June 4, 2021
Automated compound verification using 2D-NMR HSQC data in an open-access environment.
Philip Keyes1, Gonzalo Hernandez, Giovanni Cianchetta
1Lexicon Pharmaceuticals, Analytical Chemistry, 350 Carter Road, Princeton, New Jersey, 08540, USA. pkeyes@lexpharma.com
Magnetic Resonance in Chemistry : MRC
|November 11, 2008
Summary
Medicinal chemists can now automate Nuclear Magnetic Resonance (NMR) verification using predicted data. This system enhances compound library confidence and frees scientists for drug discovery.
Area of Science:
- Chemical analysis
- Drug discovery
- Analytical chemistry
Background:
- Automated compound registration systems aim to simplify data interpretation for medicinal chemists.
- Previous systems relied on High-Performance Liquid Chromatography (HPLC) and Liquid Chromatography-Mass Spectrometry (LCMS) data.
- Nuclear Magnetic Resonance (NMR) data has not been integrated into these automated verification workflows.
Purpose of the Study:
- To extend automated compound verification to include NMR data.
- To compare experimentally acquired NMR data with predicted NMR spectra.
- To integrate NMR data into existing compound registration and sample submission processes.
Main Methods:
- Utilized gradient-heteronuclear single quantum coherence (HSQC) experiments for NMR data acquisition.
- Developed a system to compare experimental (1)H and (13)C NMR data against predicted spectra.
- Integrated the NMR data processing with the industry-standard compound registration system and analytical instruments.
Main Results:
- Achieved unattended and automated NMR verification for submitted compound collections.
- Enabled comparison of experimental NMR data with predicted NMR data.
- Successfully integrated NMR verification into the existing sample submission and registration workflow.
Conclusions:
- Automated NMR verification enhances confidence in compound libraries.
- The system frees medicinal chemists from tedious data manipulation.
- This automation allows scientists to dedicate more time to the drug discovery process.
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