# The transformative power of structural predictions with AI in plant science

## TL;DR

AI-based structural prediction is revolutionizing plant science by enabling accurate protein structure modeling and accelerating discoveries in protein function and interactions.

## Contribution

The paper highlights how AI-driven structural prediction tools are transforming plant science through enhanced functional discovery and analysis of protein interactions.

## Key findings

- AI tools like AlphaFold and RoseTTAFold enable high-confidence protein structure predictions in plants.
- Structural predictions have revealed novel protein functions and evolutionary insights.
- In silico screens using these tools have identified new autophagy receptors and immune hydrolase inhibitors.

## Abstract

Since the introduction of various structural prediction programs, the emerging transformative power of these technologies in plant science is apparent. Not only programs like AlphaFold but also RoseTTAFold, Chai‐1 and Boltz suddenly enable plant scientists to predict structures with high confidence. This ability has facilitated the discovery of novel protein functions inspired by structural homology and provided novel insights into how proteins evolved from ancestral folds. Prediction of protein oligomers and their interactions with lipids was crucial for studying immune receptors that assemble into resistosomes, while prediction of peptide–protein interactions has enabled the engineering of broad‐range cell surface receptors. In silico screens for novel protein interactions identified novel autophagy receptors and inhibitors of immune hydrolases. More discoveries will soon follow with the development of new tools to predict and analyse structures. These and many other recent discoveries highlight the transformative power of structural predictions with artificial intelligence in plant science.

Artificial intelligence (AI)‐based structural prediction is transforming plant sciences. High‐confidence protein models have accelerated functional discovery, illuminated evolutionary origins, enabled analysis of oligomers and receptor–ligand interactions and uncovered novel protein–protein interactions, illustrating a profound impact on plant science.