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De Novo Design of Chemical Stability Near-Infrared Molecular Probes for High-Fidelity Hepatotoxicity Evaluation In Vivo.

机构信息

State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering , Hunan University , Changsha 410082 , P. R. China.

State Key Laboratory of Natural Medicines, School of Basic Medical Sciences and Clinical Pharmacy , China Pharmaceutical University , Nanjing , Jiangsu 211198 , P. R. China.

出版信息

J Am Chem Soc. 2019 Apr 17;141(15):6352-6361. doi: 10.1021/jacs.9b01374. Epub 2019 Apr 2.

DOI:10.1021/jacs.9b01374
PMID:30897899
Abstract

Near-infrared (NIR) fluorescence imaging technique is garnering increasing research attention due to various advantages. However, most NIR fluorescent probes still suffer from a false signals problem owing to their instability in real application. Especially in a pathological environment, many NIR probes can be easily destroyed due to the excessive generation of highly reactive species and causing a distorted false signal. Herein, we proposed an approach for developing a new stable NIR dye platform with an optically tunable group to eliminate false signals using the combination of dyes screening and rational design strategy. The conception is validated by the construction of two high-fidelity NIR fluorescent probes (NIR-LAP and NIR-ONOO) sensing leucine aminopeptidase (LAP) and peroxynitrite (ONOO), the markers of hepatotoxicity. These probes (NIR-LAP and NIR-ONOO) were demonstrated to sensitively and accurately monitor LAP and ONOO (detection limit: 80 mU/L for LAP and 90 nM for ONOO), thereby allowing one to precisely evaluate drug-induced hepatotoxicity. In addition, based on the fluctuation of LAP, the therapeutic efficacy of six hepatoprotective medicines for acetaminophen-induced hepatotoxicity was analyzed in vivo. We anticipate the high-fidelity NIR dye platform with an optically tunable group could provide a convenient and efficient tool for the development of future probes applied in the pathological environment.

摘要

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