Bioinformatic Tools
Tools for predicting NO-related post-translational modifications
Several bioinformatics tools have been developed to predict nitric oxide (NO)-related post-translational modifications (PTMs), such as S-nitrosation and tyrosine nitration. These modifications play crucial roles in redox signaling and cellular regulation.
Tools like GPS-SNO, iSNO-PseAAC, and SNOSite use machine learning approaches, including support vector machines and position-specific scoring matrices, trained on experimentally validated data. They typically analyze sequence features, structural properties, and amino acid compositions to identify potential NO-sensitive sites.
Some platforms also offer web-based interfaces, allowing users to submit protein sequences for prediction. Despite their utility, the accuracy of predictions may vary, and experimental validation remains essential. Ongoing developments aim to improve prediction reliability by integrating more diverse datasets and advanced algorithms.
In Table 1, software tools developed so far for predicting NO-dependent PTMs (S-nitrosation and tyrosine nitration) are listed. Modified from Kolbert and Lindermayr (2021).
| TOOL NAME | MODIFICATION TYPE | AVAILABILITY | PREDICTION | CITATIONS | REFERENCE |
|---|---|---|---|---|---|
| S-nitrosation | webserver, standalone | Cysteine S-nitrosation sites | 228 (2025 Sept) | Y. Xue, Z. Liu, X. Gao, C. Jin, L. Wen, X. Yao, J. Ren (2010) GPS-SNO: computational prediction of protein S-nitrosation sites with a modified GPS algorithm. PloS One, 5, Article e11290, 10.1371/journal.pone.0011290 | |
| S-nitrosation | webserver | Cysteine S-nitrosation sites | 86 (2025 Sept) | T.Y. Lee, Y.J. Chen, T.C. Lu, H.D. Huang, Y.J. Chen (2011) SNOSite: exploiting maximal dependence decomposition to identify cysteine S-nitrosation with substrate site specificity. PloS One, 6, Article e21849, 10.1371/journal.pone.0021849 | |
| S-nitrosation | webserver | Cysteine S-nitrosation sites | 391 (2025 Sept) | Y. Xu, J. Ding, L.Y. Wu, K.C. Chou (2013) iSNO-PseAAC: predict cysteine S-nitrosation sites in proteins by incorporating position specific amino acid propensity into pseudo amino acid composition. PloS One, 8, Article e55844, 10.1371/journal.pone.0055844 | |
| S-nitrosation | webserver | Cysteine S-nitrosation sites | 280 (2025 Sept) | Y. Xu, X.J. Shao, L.Y. Wu, N.Y. Deng, K.C. Chou (2013) iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosation sites in proteins. Peer J, 1, p. e171, 10.7717/peerj.171 | |
| S-nitrosation | webserver | Cysteine S-nitrosation sites | 93 (2025 Sept) | J. Zhang, X. Zhao, P. Sun, Z. Ma (2014) PSNO: predicting cysteine S-nitrosation sites by incorporating various sequence-derived features into the general form of Chou's PseAAC. Int. J. Mol. Sci., 15, pp. 11204-11219 |
Showing 5 of 12 entries
For more details see
- Kolbert Zs and Lindermayr C Computational prediction of NO-dependent posttranslational modifications in plants: Current status and perspectives.. Plant Physiology and Biochemistry 167, 851-861 (2021).