Deep-Palm：an integrated deep learning framework for structure-aware prediction of protein S-Palmitoylation

Deng, M.; Huang, J.; Wang, W.; Fu, S.; Wang, H.; Kang, Y.-J.; Xu, B.

doi:10.64898/2026.03.05.709753

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bioRxiv · 10.64898/2026.03.05.709753

Deep-Palm：an integrated deep learning framework for structure-aware prediction of protein S-Palmitoylation

Deng, M.·Huang, J.·Wang, W.·Fu, S.·Wang, H.·Kang, Y.-J.·Xu, B.

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Abstract

Protein S-palmitoylation is a reversible lipid modification that regulates protein localization, trafficking, and signaling. Its dysregulation has been implicated in cancer and therapeutic resistance, making accurate site annotation important for understanding disease-related regulatory mechanisms. However, experimental identification of S-palmitoylation sites remains labor-intensive, highlighting the need for computational tools that can support large-scale candidate-site prioritization. S-palmitoylation-site recognition requires the integration of multiple levels of information surrounding candidate cysteine residues, including sequence context, local protein properties and structural features. Here, we present Deep-Palm, a deep learning framework that integrates four complementary branches: amino acid sequence, physicochemical properties, ESM embedding and spatial structure. On the testing set, Deep-Palm achieved an AUC of 0.950 and outperformed the compared predictors, including pCysMod, MusiteDeep and GPS-Palm. Deep-Palm also showed stable performance across diverse cysteine sequence contexts and Gene Ontology functional groups. Feature-level analyses revealed distinct spatial structural and protein property patterns between palmitoylated and non-palmitoylated peptide windows. Independent mass spectrometry datasets further demonstrated the ability of Deep-Palm to sensitively identify previously unannotated S-palmitoylation sites. Together, Deep-Palm provides an accurate and biologically informative framework for S-palmitoylation-site prediction, facilitating the discovery of novel candidate S-palmitoylation sites.

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Deng, M., Huang, J., Wang, W., Fu, S., Wang, H., Kang, Y.-J., Xu, B.. 2026-03-07. Deep-Palm：an integrated deep learning framework for structure-aware prediction of protein S-Palmitoylation. https://doi.org/10.64898/2026.03.05.709753

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