Rational Design of Organelle-Targeted Fluorescent Probes: Insights from Artificial Intelligence
Jie Dong,
Jie Qian,
Kunqian Yu,
Shuai Huang,
Xiang Cheng,
Fei Chen,
Hualiang Jiang,
Wenbin Zeng
Affiliations
Jie Dong
Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410083, P.R. China.
Jie Qian
National Engineering Research Center of Rice and Byproduct Deep Processing, School of Food Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, P.R. China.
Kunqian Yu
State Key Laboratory of Drug Research, Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, P.R. China.
Shuai Huang
Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410083, P.R. China.
Xiang Cheng
Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410083, P.R. China.
Fei Chen
Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410083, P.R. China.
Hualiang Jiang
State Key Laboratory of Drug Research, Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, P.R. China.
Wenbin Zeng
Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410083, P.R. China.
Monitoring the physiological changes of organelles is essential for understanding the local biological information of cells and for improving the diagnosis and therapy of diseases. Currently, fluorescent probes are considered as the most powerful tools for imaging and have been widely applied in biomedical fields. However, the expected targeting effects of these probes are often inconsistent with the real experiments. The design of fluorescent probes mainly depends on the empirical knowledge of researchers, which was inhibited by limited chemical space and low efficiency. Herein, we proposed a novel multilevel framework for the prediction of organelle-targeted fluorescent probes by employing advanced artificial intelligence algorithms. In this way, not only the targeting mechanism could be interpreted beyond intuitions but also a quick evaluation method could be established for the rational design. Furthermore, the targeting and imaging powers of the optimized and synthesized probes based on this methodology were verified by quantitative calculation and experiments.
