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Updated: Jul 11, 2025

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode
Published on: June 4, 2021
Detecting Submicromolar Analytes in Mixtures with a 5 min Acquisition on 600 MHz NMR Spectrometers
Congcong Zhang1, Li Xu1, Qingxia Huang1
1State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200438, China.
Abstract:
Amino compounds are widely present in complex mixtures in chemistry, biology, medicine, food, and environmental sciences involving drug impurities and metabolisms of proteins, biogenic amines, neurotransmitters, and pyrimidine in biological systems. Nuclear magnetic resonance (NMR) spectroscopy is an excellent tool for simultaneously identifying and quantifying these in-mixture compounds but has a limit-of-detection (LOD) over several micromolarities (>5 μM). To break such a sensitivity barrier, we developed a sensitive and rapid method by combining the probe-induced sensitivity enhancement and nonuniform-sampling-based 1H-13C HSQC 2D-NMR (PRISE-NUS-HSQC). We introduced two 13CH3 tags for each analyte to respectively increase the 1H and 13C abundances for up to 6 and 200 fold. This enabled high-resolution detection of 0.4-0.8 μM analytes in mixtures in 5 mm tubes with a 5 min acquisition on 600 MHz spectrometers. The method is much more sensitive and faster than traditional 1H-13C HSQC methods (∼50 μM, >10 h). Using sulfanilic acid as a single reference, furthermore, we established a database covering chemical shifts and relative-response factors for >100 compounds, enabling reliable identification and quantification. The method showed good quantitation linearity, accuracy, precision, and applicability in multiple biological matrices, offering a rapid and sensitive approach for quantitative analysis of large cohorts of chemical, medicinal, metabolomic, food, and other mixtures.
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