Using Protein Language Models Embeddings to predict O-GlcNAc glycosylation sites - Arcanjo, Adenilson; Mariano, Diego; Bastos, Luana L.; Bastos, Ana L. A.; Pirovani, Milenna; Melo-Minardi, Raquel C. de (Anais do Simpósio Brasileiro de Bioinformática (BSB), 2025)
O-GlcNAcylation is a post-translational modification (PTM) that involves the covalent bonding of an N-acetylglucosamine (GlcNAc) molecule to serine or threonine amino acid residues in nuclear and cytoplasmic proteins. PTMs dysregulation has been implicated in a wide range of diseases, including cancer, metabolic syndromes, and neurodegenerative disorders. Precise mapping of O-GlcNAc sites is essential for advancing both fundamental understanding and the development of targeted therapeutics. However, their detection remains challenging, which has motivated the development of computational tools to predict these sites with greater accuracy. In this study, we used Protein Language Models (PLMs) to address the challenge of predicting protein residues that are O-GlcNAc modification sites. To evaluate our method, we collected data from the O-GlcNAc Atlas. Our results indicate that our model outperformed competitors in all datasets evaluated. We believe the approach presented here can benefit scientists working on any subject where protein post-translational modifications play a role.