The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
A Unique “Integration” Strategy for the Rational Design of Optically Tunable Near-Infrared Fluorophores
Abstract
Fluorescence imaging is a rapidly growing technique for noninvasive imaging of biological molecules and processes with high spatial and temporal resolution. For effective biological imaging, it is essential and important to develop robust fluorescent dyes, in particular, near-infrared (NIR) fluorescent dyes with favorable optical properties. Compared with the visible light emitting dyes, NIR dyes have relatively longer emission wavelengths (650-900 nm) with lower energy and are advantageous as imaging agents owing to the minimum photodamage of NIR light to biological samples, deep penetration into tissues, and low interference from autofluorescence of biomolecules. Although great efforts have been devoted to engineer NIR fluorophores, it is still very challenging to regulate their photophysical properties as they often lack optically tunable mechanisms, and this shortcoming considerably restricts the realization of their full potential. Consequently, the rational design of small-molecule optically tunable NIR fluorophores is of high priority and great value. In general, two key characteristics are indispensable for designing excellent optically tunable NIR fluorescent dyes. First, NIR fluorescent dyes should display the maximal absorption and emission located in the NIR region and also have the prominent properties including excellent fluorescence quantum yields, large Stokes shifts, good chemical stability and photostability, low cytotoxicity, and desirable compatibility with biological systems. Second, in principle, functional NIR dyes should also possess optically tunable groups, which can be easily modified to afford responsive sites for the targets of interest. With these considerations in mind, in this Account, we described a unique "integration" strategy for judicious design of the optically tunable NIR fluorophores, which are an intuitive combination of the traditional NIR dyes and the optically tunable mechanisms in the visible light emissive dyes. Thus, the versatile strategy may allow not only retention of the NIR emission properties of NIR dyes but also inheritance of the optically tunable mechanisms from the visible light emissive dyes. By the unique integration strategy, a built-in optically tunable group is strategically installed into the traditional NIR fluorescent dyes to directly tune their optical properties. Herein, we present a concise review of the rational design strategy and biological applications of small-molecule optically tunable NIR fluorescent dyes via the unique integration strategy, and we focused mainly on our work and some representative examples from other groups based on our NIR platforms. This Account includes the detailed integration strategy of each class of the NIR fluorescent dyes, the development of their derivatives, and their imaging applications in living systems.
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Cites
Fluorescent Chemosensors Based on Spiroring-Opening of Xanthenes and Related Derivatives
Chen, X., Pradhan, T., Wang, F., Kim, J. S., & Yoon, J. (2012) · Chemical Reviews · doi:10.1021/cr200201z · Cited by 1,984
Recent Development of Chemosensors Based on Cyanine Platforms
Sun, W., Guo, S., Hu, C., Fan, J., & Peng, X. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00001 · Cited by 1,109
A Long-Wavelength Fluorescent Chemodosimeter Selective for Cu(II) Ion in Water
Dujols, V., Ford, F., & Czarnik, A. W. (1997) · Journal of the American Chemical Society · doi:10.1021/ja971221g · Cited by 987
A Unique Approach to Development of Near-Infrared Fluorescent Sensors for in Vivo Imaging
Yuan, L., Lin, W., Zhao, S., Gao, W., Chen, B., He, L., & Zhu, S. (2012) · Journal of the American Chemical Society · doi:10.1021/ja305802v · Cited by 679
Self-citationYuan, L., Lin, W., Yang, Y., & Chen, H. (2012) · Journal of the American Chemical Society · doi:10.1021/ja209292b · Cited by 562
Self-citationKundu, K., Knight, S. F., Willett, N., Lee, S., Taylor, W. R., & Murthy, N. (2009) · Angewandte Chemie International Edition · doi:10.1002/anie.200804851 · Cited by 339
Functional Near‐Infrared Fluorescent Probes
Kiyose, K., Kojima, H., & Nagano, T. (2008) · Chemistry - An Asian Journal · doi:10.1002/asia.200700267 · Cited by 248
Near-infrared fluorescent sensor for in vivo copper imaging in a murine Wilson disease model
Hirayama, T., Van de Bittner, G. C., Gray, L. W., Lutsenko, S., & Chang, C. J. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1113729109 · Cited by 220
Near-Infrared Dyes for High Technology Applications
(1998) · Springer eBooks · doi:10.1007/978-94-011-5102-3 · Cited by 217
“Donor–Two-Acceptor” Dye Design: A Distinct Gateway to NIR Fluorescence
Karton-Lifshin, N., Albertazzi, L., Bendikov, M., Baran, P. S., & Shabat, D. (2012) · Journal of the American Chemical Society · doi:10.1021/ja308124q · Cited by 216
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Wang, L., Du, W., Hu, Z., Uvdal, K., Li, L., & Huang, W. (2019) · Angewandte Chemie International Edition · doi:10.1002/anie.201901061 · Cited by 348
NIR-II bioimaging of small organic molecule
Su, Y., Yu, B., Wang, S., Cong, H., & Shen, Y. (2021) · Biomaterials · doi:10.1016/j.biomaterials.2021.120717 · Cited by 251
Xu, Y., Dou, Y., Li, Q., Ye, H., Li, Y., Qiu, S., Xiong, X., Li, J., & Sun, Y. (2023) · Coordination Chemistry Reviews · doi:10.1016/j.ccr.2023.215320 · Cited by 39
Metadata
- Authors
- Chen, H., Dong, B., Tang, Y., & Lin, W.
- Venue
- Accounts of Chemical Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-05-11
- Volume
- 50
- Issue
- 6
- Pages
- 1410-1422
- ISSN
- 0001-4842 (ISSN-L)
- 1520-4898
- OpenAlex
- W2612254178
- Cited by
- 322
- References
- 27
- FWCI
- 19.31
- Type
- journal article
- Language
- en
- Open access
- closed
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