The past, present, and future of FRET-guided structural modeling.

Abstract

Biomolecules' conformational landscapes span multiple timescales and structural populations, challenging traditional structural biology methods that predominantly capture static states. Over the past three decades, Förster resonance energy transfer (FRET) has evolved from a qualitative molecular ruler into a quantitative framework for integrative structural biology. Advances in single-molecule FRET (smFRET), fluorophore modeling, molecular simulations, and experimental standardization have transformed FRET into a powerful approach for reconstructing dynamic structural ensembles. We didactically reviewed the various developments in FRET-guided structural modeling and discussed the next frontier of FRET-guided structural biology, where machine learning, AlphaFold-based structure prediction, and super-resolution microscopy are converging with smFRET to validate, refine, and visualize dynamic conformational ensembles directly in their native cellular context. Together, these advances position FRET-guided structural modeling as a central experimental framework for the next generation of dynamic structural biology.