Literature DB >> 24266806

Rational design of matrix metalloproteinase-13 activatable probes for enhanced specificity.

Lei Zhu1, Ying Ma, Dale O Kiesewetter, Ye Wang, Lixin Lang, Seulki Lee, Gang Niu, Xiaoyuan Chen.   

Abstract

Because of the important roles that matrix metalloproteinases (MMPs) play in tumor invasion and metastasis, various activatable optical probes have been developed to visualize MMP activities in vitro and in vivo. Our recently developed MMP-13 activatable probe, l-MMP-P12, has been successfully applied to image the expression and inhibition of MMPs in a xenografted tumor model [Zhu, L., et al. (2011) Theranostics 1, 18-27]. In this study, to further optimize the in vivo behavior of the proteinase activatable probe, we tracked and profiled the metabolites by a high-resolution liquid chromatography-mass spectrometry (LC-MS) system. Two major metabolites that contributed to the fluorescence recovery were identified. One was specifically cleaved between glycine (G(4)) and valine (V(5)) by MMP, while the other one was generated by nonspecific cleavage between glycine (G(7)) and lysine (K(8)). To visualize the MMP activity more accurately and specifically, a new probe, D-MMP-P12, was designed by replacing the l-lysine with d-lysine in the MMP substrate sequence. The metabolic profile of the new probe, D-MMP-P12, was further characterized by in vitro enzymatic assay, and no nonspecific metabolite was found by LC-MS. Our in vivo optical imaging also demonstrated that D-MMP-P12 had a tumor-to-background ratio (TBR, 5.55 ± 0.75) significantly higher than that of L-MMP-P12 (3.73 ± 0.31) 2 h postinjection. The improved MMP activatable probe may have the potential for drug screening, tumor diagnosis, and therapy response monitoring. Moreover, our research strategy can be further extended to study other protease activatable probes.

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Year:  2013        PMID: 24266806      PMCID: PMC3944097          DOI: 10.1021/cb400698s

Source DB:  PubMed          Journal:  ACS Chem Biol        ISSN: 1554-8929            Impact factor:   5.100


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