Chirality is a fundamental property of nature. Many biologically significant molecules, including amino acids, nucleotides and saccharides, are chiral in nature. Enantiomers, which are chiral isomers with opposite chirality, usually demonstrate differences in their pharmacology, metabolism and toxicity, and have the same chemical composition and very similar physiochemical properties. Norepinephrine and epinephrine are important neurotransmitters and hormones that play critical roles in vasoconstriction, blood pressure control and the transmission of nerve impulses. They are also used as emergency medications in cardiac arrest and anaphylaxis. However, both norepinephrine and epinephrine contain a single chiral centre, and each have two enantiomers with different pharmacodynamic effects. The activity in vivo of the corresponding L-enantiomers is 100 times that of the D-enantiomers. In addition, the L-enantiomers are spontaneously converted into D-enantiomers by racemization, and this results in gradual loss of their therapeutic effectiveness, posing challenges to drug storage. In the production of L-norepinephrine and epinephrine, D-enantiomers are generally treated as undesired products which affect the synthesis efficiency and product quality. Therefore, it is necessary to develop a rapid enantiomer identification method for norepinephrine and epinephrine for quality control during drug production and storage.
Biological nanopores can in principle discriminate between enantiomers when the target molecule is transiently trapped near the pore constriction, because of their chiral lumen environment and a sufficient resolution of sensing, However, owing to the technical complexity associated with the chemical engineering of the pore lumen, direct discrimination of enantiomers has been only rarely reported with nanopores. Programmable nanoreactors for stochastic sensing (PNRSS), is a versatile strategy originally developed by Prof. Shuo Huang’s group in our department in recent years for studying single molecule reactions. It omits the complexities associated with pore engineering by introducing instead a synthetic strand of chemically engineered nucleic acid strands to the pore lumen.
Figure 1. Concept demonstration of programmable nanopore for identification of norepinephrine enantiomers
On this basis, Prof. Shuo Huang’s group recently reported a technique for chiral single-molecule identification of norepinephrine and epinephrine using a programmable nanopore in ACS Nano (Figure 1). Phenylboronic acid was introduced into the MspA nanopore by PNRSS as the molecular recognition element of norepinephrine and epinephrine, and the single-molecule identification of L-norepinephrine, D-norepinephrine, L-epinephrine and D-epinephrine was successfully realized.
Figure 2. Identification of catecholamine enantiomers assisted by machine learning
Assisted by machine learning, the general accuracy score of catecholamine enantiomers identification was 98.2%, and events from a mixture can be identified (Figure 2). This can quickly report enantiomeric excess (ee) values and is extremely useful in evaluation of the enantiomeric purity and the racemization process of catecholamines. Through the direct detection of commercial epinephrine hydrochloride injection, the corresponding enantiomeric excess value was obtained, which verified the feasibility of this strategy for the quality control of catecholamine enantiomers.
The related paper entitled Identification of single molecule catecholamine enantiomers using a programmable nanopore has been published on ACS nano on Apr 9, 2022. (DOI: 10.1021/acsnano.2c01017, paper link: https://pubs.acs.org/doi/full/10.1021/acsnano.2c01017). The first author is Ph.D. student Jia Wendong and Prof. Shuo Huang from our department is the corresponding author of the paper. Academician Hong-yuan Chen gave important guidance to this work. Prof. Jing Ma, Ph.D. Qiang Zhu and Ph.D. student Yuming Gu of our department put forward valuable opinions on the mechanism. This project was funded by National Natural Science Foundation of China (Grant No. 31972917, No. 91753108, No. 21675083, No. 22033004), Supported by the Fundamental Research Funds for the Central Universities (Grant No.020514380257, No.020514380261), Programs for high-level entrepreneurial and innovative talents introduction of Jiangsu Province (individual and group program), Natural Science Foundation of Jiangsu Province (Grant No. BK20200009), Excellent Research Program of Nanjing University (Grant No. ZYJH004), Shanghai Municipal Science and Technology Major Project, State Key Laboratory of Analytical Chemistry for Life Science (Grant No. 5431ZZXM1902), Technology innovation fund program of Nanjing University, China Postdoctoral Science Foundation (Grant No. 2021M691508).