Interpretable artificial intelligence decodes the chemical structural essence of TICT and PICT!
ResearchIntramolecular charge transfer (ICT) is one of the most important photophysical mechanisms in organic fluorophores. Among ICT processes, TICT (Twisted Intramolecular Charge Transfer) and PICT (Planar Intramolecular Charge Transfer) represent two highly representative yet frequently confused mechanisms. Although their ground-state structures appear remarkably similar, their excited-state conformations and emission behaviors diverge dramatically. This “similar structures but opposite properties” paradox has long hindered the rational design of fluorescent molecules, making probe development costly, time-consuming, and difficult to scale to large molecular libraries. To address this challenge, the authors Prof. Jie Dong and Prof. Wenbin Zeng from the Xiangya School of Pharmaceutical Sciences, Central South University employed interpretable artificial intelligence to unveil the deep chemical structural essence distinguishing TICT and PICT fluorophores at a systematic level. They further proposed AI-guided design rules for intelligent fluorophore development, significantly improving design efficiency. The key highlights of the study include: (1) Constructing the first comprehensive TICT and PICT fluorophore dataset, covering molecules from nearly a decade of research. (2) Using interpretable algorithms to successfully identify the key factors that critically influence TICT and PICT mechanisms. (3) Releasing an easy-to-use decision tree only based on simple molecular descriptors and fingerprints, ensuring a fast decision and modification when designing TICT and PICT molecules. (4) Proposing the first AI-guided structural design rules for TICT and PICT fluorophores. (5) Conducting both experimental tests and quantitative calculations which confirmed the potential of the approach for the efficient and reliable discovery of TICT and PICT fluorophore candidates.
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- Research
- Funder
- National Natural Science Foundation of China, Science and Technology Innovation Program of Hunan Province, Innovation-Driven Project of Central South University