AI-Driven Acceleration of Fluorescence Probe Discovery.

ABSTRACT: Fluorescence imaging probes are indispensable tools for clinical navigation and preclinical research. However, the discovery of target-specific probes is hampered by the scarcity of targetable fluorophore scaffolds, making the development process slow, costly, and heavily reliant on trial-and-error design. Here, we present a hybrid strategy that integrates AI with bioassays to accelerate the development of target-specific fluorescent probes. We developed an AI model (PROBY) based on over one million molecule entries from nine datasets, capable of identifying fluorescent molecules and predicting seven key photophysical properties. Applying PROBY to a library of 26,416 target-validated molecules, we identified thousands of candidates with both target affinity and favorable optical characteri

SUBMITTER: Jiang X 

PROVIDER: S-EPMC12915096 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature