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Updated: May 5, 2026
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Specificity Analysis of Protein Lysine Methyltransferases Using SPOT Peptide Arrays
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PBertKla: a protein large language model for predicting human lysine lactylation sites
Hongyan Lai1, Diyu Luo1, Mi Yang2
1Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.
BMC Biology
|April 6, 2025
Summary
A new tool, PBertKla, accurately predicts human lactylation sites (Kla). This advancement aids in understanding lactylation
Area of Science:
- Biochemistry
- Proteomics
- Bioinformatics
Background:
- Lactylation is a novel post-translational modification occurring on lysine residues.
- Lysine lactylation (Kla) influences cell function, fate, and disease progression.
- Accurate identification of Kla sites is crucial for biological and medical research.
Purpose of the Study:
- To develop a precise predictor for human lactylation sites.
- To leverage protein large language models for Kla site prediction.
Main Methods:
- Curated a reliable benchmark dataset for training.
- Trained a protein large language model with optimized hyperparameters.
- Validated the model's performance using independent datasets.
Main Results:
- PBertKla demonstrated robust human Kla site prediction ability.
- Achieved an AUC value exceeding 0.880 on independent validation data.
- Outperformed existing models in prediction accuracy and transferability.
Conclusions:
- PBertKla serves as an effective automatic predictor for human Kla sites.
- This tool will accelerate research into lactylation modifications in health and disease.
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