pCysMod: Prediction of Multiple Cysteine Modifications Based on Deep Learning Framework - Li, Shihua; Yu, Kai; Wu, Guandi; Zhang, Qingfeng; Wang, Panqin; Zheng, Jian; Liu, Ze-Xian; Wang, Jichao; Gao, Xinjiao; Cheng, Han (Frontiers in Cell and Developmental Biology, 2021)
Thiol groups on cysteines can undergo multiple post-translational modifications (PTMs), acting as a molecular switch to maintain redox homeostasis and regulating a series of cell signaling transductions. Identification of sophistical protein cysteine modifications is crucial for dissecting its underlying regulatory mechanism. Instead of time-consuming and labor-intensive experimental method, various computational methods have attracted intense research interest due to their convenience and low cost. Here, we developed the first comprehensive deep learning based tool pCysMod for multiple protein cysteine modification prediction, including S-nitrosylation, S-palmitoylation, S-sulfenylation, S-sulfhydration and S-sulfinylation. Experimentally verified cysteine sites curated from literature and sites collected by other databases and predicting tools were integrated as benchmark dataset. Several protein sequence features were extracted and united into a deep learning model, and the hyperparameters were optimized by particle swarm optimization algorithms. Cross validations indicted our model showed excellent robustness and outperformed existing tools, which was able to achieve an average AUC of 0.793, 0.807, 0.796, 0.793 and 0.876 for S-nitrosylation, S-palmitoylation, S-sulfenylation, S-sulfhydration and S-sulfinylation, demonstrating pCysMod was stable and suitable for protein cysteine modification prediction. And besides, we constructed a comprehensive protein cysteine modification prediction web server based on this model to benefit the researches finding the potential modification sites of their interested proteins, which could be accessed at http://pcysmod.omicsbio.info. This work will undoubtedly greatly promote the study of protein cysteine modification, and contribute to clarifying the biological regulation mechanisms of cysteine modification within and amongst the cells.