Machine-learning screening of luminogens with aggregation-induced emission characteristics for fluorescence imaging
-
Published:2023-03-25
Issue:1
Volume:21
Page:
-
ISSN:1477-3155
-
Container-title:Journal of Nanobiotechnology
-
language:en
-
Short-container-title:J Nanobiotechnol
Author:
Zhang Yibin,Fan Miaozhuang,Xu Zhourui,Jiang Yihang,Ding Huijun,Li Zhengzheng,Shu Kaixin,Zhao Mingyan,Feng Gang,Yong Ken-Tye,Dong Biqin,Zhu Wei,Xu Gaixia
Abstract
AbstractDue to the excellent biocompatible physicochemical performance, luminogens with aggregation-induced emission (AIEgens) characteristics have played a significant role in biomedical fluorescence imaging recently. However, screening AIEgens for special applications takes a lot of time and efforts by using conventional chemical synthesis route. Fortunately, artificial intelligence techniques that could predict the properties of AIEgen molecules would be helpful and valuable for novel AIEgens design and synthesis. In this work, we applied machine learning (ML) techniques to screen AIEgens with expected excitation and emission wavelength for biomedical deep fluorescence imaging. First, a database of various AIEgens collected from the literature was established. Then, by extracting key features using molecular descriptors and training various state-of-the-art ML models, a multi-modal molecular descriptors strategy has been proposed to extract the structure-property relationships of AIEgens and predict molecular absorption and emission wavelength peaks. Compared to the first principles calculations, the proposed strategy provided greater accuracy at a lower computational cost. Finally, three newly predicted AIEgens with desired absorption and emission wavelength peaks were synthesized successfully and applied for cellular fluorescence imaging and deep penetration imaging. All the results were consistent successfully with our expectations, which demonstrated the above ML has a great potential for screening AIEgens with suitable wavelengths, which could boost the design and development of novel organic fluorescent materials.
Funder
National Natural Science Foundation of China The Science Foundation of Zhejiang Sci-Tech University Guangdong Natural Science Foundation Science, Technology and Innovation Commission of Shenzhen Municipality
Publisher
Springer Science and Business Media LLC
Subject
Pharmaceutical Science,Applied Microbiology and Biotechnology,Biomedical Engineering,Molecular Medicine,Medicine (miscellaneous),Bioengineering
Reference54 articles.
1. Vendrell M, Zhai D, Er JC, Chang Y-T. Combinatorial strategies in fluorescent Probe Development. Chem Rev. 2012;112:4391–420. 2. Ma W, Zhang L, Shi Y, Ran Y, Liu Y, You J. Molecular Engineering to Access fluorescent trackers of organelles by cyclization: Chemical Environment of Nitrogen Atom-Modulated targets. Adv Funct Mater. 2020;30:2004511–9. 3. Lee J-S, Kang N-y, Kim YK, Samanta A, Feng S, Kim HK, Vendrell M, Park JH, Chang Y-T. Synthesis of a BODIPY Library and its application to the development of live cell Glucagon Imaging Probe. JACS. 2009;131:10077–82. 4. Mei J, Leung NLC, Kwok RTK, Lam JWY, Tang BZ. Aggregation-Induced Emission: together we Shine, United we soar! Chem Rev. 2015;115:11718–940. 5. Jiang Y, Zhu W, Xu Z, Zhang Z, Tang S, Fan M, Li Z, Zhang J, Yang C, Law W-C, et al. A mitochondrion-targeting two-photon photosensitizer with aggregation-induced emission characteristics for hypoxia-tolerant photodynamic therapy. Chem Eng J. 2022;448:137604–13.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|