Identification of Single-Molecule Catecholamine Enantiomers Using a Programmable Nanopore.
Wendong JiaChengzhen HuYuqin WangYao LiuLiying WangShanyu ZhangQiang ZhuYuming GuPan-Ke ZhangJing MaHong-Yuan ChenShuo HuangPublished in: ACS nano (2022)
Enantiomers, chiral isomers with opposite chirality, typically demonstrate differences in their pharmacological activity, metabolism, and toxicity. However, direct discrimination between enantiomers is challenging due to their similar physiochemical properties. Following the strategy of programmable nanoreactors for stochastic sensing (PNRSS), introduction of phenylboronic acid (PBA) to a <i>Mycobacterium smegmatis</i> porin A (MspA) assists in the identification of the enantiomers of norepinephrine and epinephrine. Using a machine learning algorithm, identification of the enantiomers has been achieved with an accuracy of 98.2%. The enantiomeric excess (ee) of a mixture of enantiomeric catecholamines was measured to determine the enantiomeric purity. This sensing strategy is a faster method for the determination of ee values than liquid chromatography-mass spectrometry and is useful as a quality control in the industrial production of enantiomeric drugs.
Keyphrases
- capillary electrophoresis
- mass spectrometry
- single molecule
- liquid chromatography
- machine learning
- quality control
- high resolution mass spectrometry
- gas chromatography
- high performance liquid chromatography
- tandem mass spectrometry
- solid phase extraction
- high resolution
- atomic force microscopy
- bioinformatics analysis
- oxidative stress
- heavy metals
- simultaneous determination
- big data
- ms ms
- solid state
- neural network