Fold on Tight: Ten Things to Know About AI Structure Prediction in Plant Immunity

AI-driven protein structure prediction has made structural models a routine part of everyday biological research. Plant immunity and molecular plant–microbe interactions provide a powerful illustration of this transformation, with structural predictions revealing hidden evolutionary relationships and transient protein–protein interactions, as well as guiding immune receptor engineering. Here, we distil recent progress into ten conceptual and practical lessons for using structural predictions critically and effectively. Together, these lessons highlight both the transformative potential of AI-driven structural modelling and the importance of interpreting predictions through biological context, rigorous benchmarking, and experimental validation.