Literature DB >> 32186291

MT1-MMP activatable fluorogenic probes with enhanced specificity via high-affinity peptide conjugation for tumor imaging.

Xiuru Ji1, Shuping Xie, Yan Jiao, Xiaojuan Zhang, Duxin Sun, Victor C Yang, Mei Wang, Huining He, Lu Sun.   

Abstract

Overlapping substrate specificities within the family of matrix metalloproteinases (MMPs), usually caused by their highly conserved structural topology, increase the potential for a substrate to be cleaved by multiple enzymes within this family, which leads to the decrease in the selectivity of MMP substrate-based probes. To resolve this issue, MT1-MMP activatable fluorogenic probes for tumor detection with enhanced specificity were developed by combining a fluorescence resonance energy transfer (FRET) peptide substrate and its specific binding peptide with different lengths of linkers. The specificity of the probes increased profiting from the high affinity of the MT1-MMP specific binding peptide while keeping the ability to amplify the output imaging signals in response to MMP activity with the FRET substrate. Enzyme kinetics analysis clearly demonstrated that the conjugation of P-1 and MT1-AF7p enhanced both the specificity and selectivity of the fluorogenic probes for MT1-MMP, and introducing a linker composed of 12 PEG subunits into these two fragments led to optimized specificity and selectivity of the fluorogenic probe for MT1-MMP. Both in vitro and in vivo results revealed that the imaging probe with the linker composed of 12 PEG subunits based on our designed strategy could be effectively applied for MT1-MMP positive tumor imaging. Since this strategy for enhancing the specificity of protease sensing probes can be applied to other proteases and is not just limited to MT1-MMP, it is an appealing platform to achieve selective tumor imaging.

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Year:  2020        PMID: 32186291      PMCID: PMC8859983          DOI: 10.1039/c9bm02007a

Source DB:  PubMed          Journal:  Biomater Sci        ISSN: 2047-4830            Impact factor:   6.843


  33 in total

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