PlantPTM

PlantPTM is the first integrated deep-learning framework for large-scale prediction of plant post-translational modification (PTM) sites. By combining protein language models, multi-view deep learning, and evolutionary information, PlantPTM enables accurate prediction of nine major PTM types, including N-glycosylation, S-acylation, 2-hydroxyisobutyrylation, crotonylation, malonylation, succinylation, acetylation, ubiquitination, and phosphorylation across six representative plant species: Arabidopsis thaliana, Oryza sativa, Triticum aestivum, Zea mays, Glycine max, and papaya.

Designed for both model and non-model plants, PlantPTM demonstrates strong generalization ability in crops such as wheat and tomato, supporting proteome-scale PTM analysis and functional discovery in diverse plant species. Independent in-house mass spectrometry (MS) validation further confirmed the reliability of PlantPTM predictions for N-glycosylation, acetylation, and ubiquitination sites.