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Targeting Human Thrombus by Liposomes Modified with Anti-Fibrin Protein Binders

Authors :
Robert Mikulik
Petr Malý
Milan Kuchař
František Hubatka
Jaroslav Turánek
Josef Mašek
Pavel Kulich
Jan E. Dyr
Renata Héžová
Jana Štikarová
Hana Petroková
Andrea Vítečková Wünschová
Eva Vohlídalová
Jan Kotouček
Milan Raska
Pavlína Turánek Knotigová
Eliška Bartheldyová
Eliška Mašková
Stuart Macaulay
Source :
Pharmaceutics, Volume 11, Issue 12
Publication Year :
2019
Publisher :
MDPI AG, 2019.

Abstract

Development of tools for direct thrombus imaging represents a key step for diagnosis and treatment of stroke. Nanoliposomal carriers of contrast agents and thrombolytics can be functionalized to target blood thrombi by small protein binders with selectivity for fibrin domains uniquely formed on insoluble fibrin. We employed a highly complex combinatorial library derived from scaffold of 46 amino acid albumin-binding domain (ABD) of streptococcal protein G, and ribosome display, to identify variants recognizing fibrin cloth in human thrombus. We constructed a recombinant target as a stretch of three identical fibrin fragments of 16 amino acid peptide of the B&beta<br />chain fused to TolA protein. Ribosome display selection followed by large-scale Enzyme-Linked ImmunoSorbent Assay (ELISA) screening provided four protein variants preferentially binding to insoluble form of human fibrin. The most specific binder variant D7 was further modified by C-terminal FLAG/His-Tag or double His-tag for the attachment onto the surface of nanoliposomes via metallochelating bond. D7-His-nanoliposomes were tested using in vitro flow model of coronary artery and their binding to fibrin fibers was demonstrated by confocal and electron microscopy. Thus, we present here the concept of fibrin-targeted binders as a platform for functionalization of nanoliposomes in the development of advanced imaging tools and future theranostics.

Details

ISSN :
19994923
Volume :
11
Database :
OpenAIRE
Journal :
Pharmaceutics
Accession number :
edsair.doi.dedup.....363f7970b53a778f9c5c698ffcdf17fe