Welcome to PON-P3
PON-P3 predicts the tolerance (pathogenicity) of amino acid substitutions in human MANE specific proteins. It is a machine learning-based approach that utilizes gene and protein, variations and structural features. PON-P3 groups variants into pathogenic, neutral, and uncertain significance (VUS) classes. The method is based on a gradient boosting algorithm and has been trained on a large dataset. It is fast and has high performance. The performance of PON-P3 has been extensively tested and compared with state-of-the-art methods.
PON-P3 was developed in the group of Prof. Mauno Vihinen, Protein Structure and Bioinformatics Research group, Lund University, Sweden.
How to cite?
Kabir, M.; Ahmed, S.; Zhang, H.; RodrÃguez-RodrÃguez, I.; Najibi, S.M.; Vihinen, M. PON-P3: Accurate Prediction of Pathogenicity of Amino Acid Substitutions. Int. J. Mol. Sci. 2025, 26, 2004. https://doi.org/10.3390/ijms26052004.