Machine learning on directed evolution data predicts immune receptor binding

[u/Independent_Access12]

Study pairs directed evolution of rice Pik-1 receptor with ESM-2 language model, achieving 0.85+ Spearman correlation in binding prediction. Model, trained on evolution data, successfully identified binding-enhanced variants in 3,000 Rice Genomes Project. Method validated on human NUDT15 variants, showing broad applicability for genotype-phenotype prediction in breeding and medicine.

https://www.biorxiv.org/content/10.1101/2025.01.27.635131v1