The DOI matches its Crossref record; 101 of the 101 references it cites were found in a registry or an index.
Design and Synthesis of Curcumin Analogues for in Vivo Fluorescence Imaging and Inhibiting Copper-Induced Cross-Linking of Amyloid Beta Species in Alzheimer’s Disease
Open accessAbstract
In this article, we first designed and synthesized curcumin-based near-infrared (NIR) fluorescence imaging probes for detecting both soluble and insoluble amyloid beta (Aβ) species and then an inhibitor that could attenuate cross-linking of Aβ induced by copper. According to our previous results and the possible structural stereohindrance compatibility of the Aβ peptide and the hydrophobic/hydrophilic property of the Aβ13-20 (HHQKLVFF) fragment, NIR imaging probe CRANAD-58 was designed and synthesized. As expected CRANAD-58 showed significant fluorescence property changes upon mixing with both soluble and insoluble Aβ species in vitro. In vivo NIR imaging revealed that CRANAD-58 was capable of differentiating transgenic and wild-type mice as young as 4 months old, the age that lacks apparently visible Aβ plaques and Aβ is likely in its soluble forms. According to our limited studies on the interaction mechanism between CRANAD-58 and Aβ, we also designed CRANAD-17 to attenuate the cross-linking of Aβ42 induced by copper. It is well-known that the coordination of copper with imidazoles on Histidine-13 and 14 (H13, H14) of Aβ peptides could initialize covalent cross-linking of Aβ. In CRANAD-17, a curcumin scaffold was used as an anchoring moiety to usher the designed compound to the vicinity of H13 and H14 of Aβ, and imidazole rings were incorporated to compete with H13/H14 for copper binding. The results of SDS-PAGE gel and Western blot indicated that CRANAD-17 was capable of inhibiting Aβ42 cross-linking induced by copper. This raises a potential for CRANAD-17 to be considered for AD therapy.
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Cites
The Amyloid Hypothesis of Alzheimer’s Disease: Progress and Problems on the Road to Therapeutics
Hardy, J., & Selkoe, D. J. (2002) · Science · doi:10.1126/science.1072994 · Cited by 13,864
Soluble protein oligomers in neurodegeneration: lessons from the Alzheimer's amyloid β-peptide
Haass, C., & Selkoe, D. J. (2007) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2101 · Cited by 4,744
Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound‐B
Klunk, W. E., Engler, H., Nordberg, A., Wang, Y., Blomqvist, G., Holt, D. P., Bergström, M., Savitcheva, I., Huang, G., Estrada, S., et al. (2004) · Annals of Neurology · doi:10.1002/ana.20009 · Cited by 4,496
Terry, R. D., Masliah, E., Salmon, D. P., Butters, N., DeTeresa, R., Hill, R., Hansen, L. A., & Katzman, R. (1991) · Annals of Neurology · doi:10.1002/ana.410300410 · Cited by 4,397
Correlative Memory Deficits, Aβ Elevation, and Amyloid Plaques in Transgenic Mice
Hsiao, K., Chapman, P., Nilsen, S., Eckman, C., Harigaya, Y., Younkin, S., Yang, F., & Cole, G. (1996) · Science · doi:10.1126/science.274.5284.99 · Cited by 4,210
Common structure of soluble amyloid oligomers implies common mechanism of pathogenesis
Kayed, R., Head, E., Thompson, J. L., McIntire, T. M., Milton, S. C., Cotman, C. W., & Glabe, C. G. (2003) · Science · doi:10.1126/science.1079469 · Cited by 4,064
Shankar, G. M., Li, S., Mehta, T. H., Garcia-Munoz, A., Shepardson, N. E., Smith, I., Brett, F. M., Farrell, M. A., Rowan, M. J., Lemere, C. A., et al. (2008) · Nature Medicine · doi:10.1038/nm1782 · Cited by 3,685
Yang, F., Lim, G. P., Begum, A. N., Ubeda, O. J., Simmons, M. R., Ambegaokar, S. S., Chen, P. P., Kayed, R., Glabe, C. G., Frautschy, S. A., et al. (2005) · Journal of Biological Chemistry · doi:10.1074/jbc.m404751200 · Cited by 2,336
Molecular mechanism of Thioflavin-T binding to amyloid fibrils
Biancalana, M., & Koide, S. (2010) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2010.04.001 · Cited by 2,195
Decreased Clearance of CNS β-Amyloid in Alzheimer’s Disease
Mawuenyega, K. G., Sigurdson, W., Ovod, V., Munsell, L., Kasten, T., Morris, J. C., Yarasheski, K. E., & Bateman, R. J. (2010) · Science · doi:10.1126/science.1197623 · Cited by 2,078
Cited by
Microglia constitute a barrier that prevents neurotoxic protofibrillar Aβ42 hotspots around plaques
Condello, C., Yuan, P., Schain, A., & Grutzendler, J. (2015) · Nature Communications · doi:10.1038/ncomms7176 · Cited by 718
Fu, W., Yan, C., Guo, Z., Zhang, J., Zhang, H., Tian, H., & Zhu, W.-H. (2019) · Journal of the American Chemical Society · doi:10.1021/jacs.8b12820 · Cited by 444
Clinical development of curcumin in neurodegenerative disease
Hu, S., Maiti, P., Ma, Q., Zuo, X., Jones, M. R., Cole, G. M., & Frautschy, S. A. (2015) · Expert Review of Neurotherapeutics · doi:10.1586/14737175.2015.1044981 · Cited by 179
Yang, J., Yin, W., Van, R., Yin, K., Wang, P., Zheng, C., Zhu, B., Ran, K., Zhang, C., Kumar, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17783-4 · Cited by 123
Self-citationThe Multifaceted Role of Neuroprotective Plants in Alzheimer’s Disease Treatment
Zieneldien, T., Kim, J., & Cao, C. (2022) · Geriatrics · doi:10.3390/geriatrics7020024 · Cited by 29
Near-infrared II theranostic agents for the diagnosis and treatment of Alzheimer’s disease
Zhou, C., Zeng, F., Yang, H., Liang, Z., Xu, G., Li, X., Liu, X., & Yang, J. (2024) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-024-06690-1 · Cited by 14
Research Mechanism and Progress of the Natural Compound Curcumin in Treating Alzheimer’s Disease
Li, L., Wang, F., Jia, X., Yao, L., & Liu, Y. (2024) · Mini-Reviews in Medicinal Chemistry · doi:10.2174/0113895575263783231009051957 · Cited by 11
Metadata
- Authors
- Zhang, X., Tian, Y., Li, Z., Tian, X., Sun, H., Liu, H., Moore, A., & Ran, C.
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-10-25
- Volume
- 135
- Issue
- 44
- Pages
- 16397-16409
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W2001447241
- Cited by
- 354
- References
- 101
- FWCI
- 12.24
- Type
- journal article
- Language
- en
- Open access
- green
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