Brain-targeted drug delivery by manipulating protein corona functions
Zui Zhang,
Juan Guan,
Zhuxuan Jiang,
Yang Yang,
Jican Liu,
Wei Hua,
Ying Mao,
Cheng Li,
Weiyue Lu,
Jun Qian and
Changyou Zhan ()
Additional contact information
Zui Zhang: Fudan University
Juan Guan: Fudan University
Zhuxuan Jiang: Fudan University
Yang Yang: Fudan University
Jican Liu: Fudan University
Wei Hua: Huashan Hospital Fudan University
Ying Mao: Huashan Hospital Fudan University
Cheng Li: School of Pharmacy & Key Laboratory of Smart Drug Delivery (Fudan University), Ministry of Education
Weiyue Lu: School of Pharmacy & Key Laboratory of Smart Drug Delivery (Fudan University), Ministry of Education
Jun Qian: School of Pharmacy & Key Laboratory of Smart Drug Delivery (Fudan University), Ministry of Education
Changyou Zhan: Fudan University
Nature Communications, 2019, vol. 10, issue 1, 1-11
Abstract:
Abstract Protein corona presents a major obstacle to bench-to-bedside translation of targeted drug delivery systems, severely affecting targeting yields and directing unfavorable biodistribution. Corona-mediated targeting provides a new impetus for specific drug delivery by precisely manipulating interaction modes of functional plasma proteins on nano-surface. Here bio-inspired liposomes (SP-sLip) were developed by modifying liposomal surface with a short nontoxic peptide derived from Aβ1-42 that specifically interacts with the lipid-binding domain of exchangeable apolipoproteins. SP-sLip absorb plasma apolipoproteins A1, E and J, consequently exposing receptor-binding domain of apolipoproteins to achieve brain-targeted delivery. Doxorubicin loaded SP-sLip (SP-sLip/DOX) show significant enhancement of brain distribution and anti-brain cancer effect in comparison to doxorubicin loaded plain liposomes. SP-sLip preserve functions of the absorbed human plasma ApoE, and the corona-mediated targeting strategy works in SP modified PLGA nanoparticles. The present study may pave a new avenue to facilitate clinical translation of targeted drug delivery systems.
Date: 2019
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DOI: 10.1038/s41467-019-11593-z
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