Generating readily synthesizable small molecule fluorophore scaffolds with reinforcement learning

TL;DR

This paper introduces SyntheFluor-RL, a reinforcement learning-based generative AI model that designs synthesizable small molecule fluorophores with desirable optical properties, validated by synthesizing and characterizing promising candidates.

Contribution

The study presents a novel reinforcement learning framework incorporating reaction constraints and property prediction to generate synthesizable fluorophore scaffolds, advancing AI-driven chemical design.

Findings

Generated 11,590 candidate molecules with filtering to 19 promising structures.

Synthesized 14 molecules, with 13 confirmed to have dye-like properties.

The top compound showed strong fluorescence, large Stokes shift, and long excited-state lifetime.

Abstract

Developing new fluorophores for advanced imaging techniques requires exploring new chemical space. While generative AI approaches have shown promise in designing novel dye scaffolds, prior efforts often produced synthetically intractable candidates due to a lack of reaction constraints. Here, we developed SyntheFluor-RL, a generative AI model that employs known reaction libraries and molecular building blocks to create readily synthesizable fluorescent molecule scaffolds via reinforcement learning. To guide the generation of fluorophores, SyntheFluor-RL employs a scoring function built on multiple graph neural networks (GNNs) that predict key photophysical properties, including photoluminescence quantum yield, absorption, and emission wavelengths. These outputs are dynamically weighted and combined with a computed pi-conjugation score to prioritize candidates with desirable optical characteristics and synthetic feasibility. SyntheFluor-RL generated 11,590 candidate molecules, which were filtered to 19 structures predicted to possess dye-like properties. Of the 19 molecules, 14 were synthesized and 13 were experimentally confirmed. The top three were characterized, with the lead compound featuring a benzothiadiazole chromophore and exhibiting strong fluorescence (PLQY = 0.62), a large Stokes shift (97 nm), and a long excited-state lifetime (11.5 ns). These results demonstrate the effectiveness of SyntheFluor-RL in the identification of synthetically accessible fluorophores for further development.