Identification of Single-Molecule Catecholamine Enantiomers Using a Programmable Nanopore

Area of Science:

• Biochemistry
• Nanotechnology
• Analytical Chemistry

Background:

• Enantiomers, chiral isomers, exhibit distinct pharmacological profiles but are difficult to differentiate due to similar physicochemical properties.
• Accurate enantiomer identification is crucial for drug safety, efficacy, and quality control in pharmaceutical manufacturing.

Purpose of the Study:

• To develop a rapid and accurate method for discriminating between enantiomers of important biomolecules.
• To leverage programmable nanoreactors for stochastic sensing (PNRSS) to achieve high-accuracy chiral discrimination.

Main Methods:

• Incorporation of phenylboronic acid (PBA) into Mycobacterium smegmatis porin A (MspA) to create a programmable nanoreactor.
• Utilizing a machine learning algorithm to analyze stochastic sensing signals for enantiomer identification.
• Measuring enantiomeric excess (ee) to determine enantiomeric purity of catecholamine mixtures.

Main Results:

• Achieved 98.2% accuracy in identifying enantiomers of norepinephrine and epinephrine.
• Demonstrated the ability to measure enantiomeric excess (ee) for purity determination.
• The developed sensing strategy significantly outperforms traditional methods in speed.

Conclusions:

• The MspA-PBA nanoreactor system provides a highly accurate and rapid method for enantiomer discrimination.
• This approach offers a valuable tool for quality control in the industrial production of enantiomeric drugs.
• The PNRSS strategy presents a promising advancement in chiral analysis and pharmaceutical quality assurance.