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Issue 4, 2011
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GPS-YNO2: computational prediction of tyrosinenitration sites in proteins

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The last decade has witnessed rapid progress in the identification of proteintyrosine nitration (PTN), which is an essential and ubiquitous post-translational modification (PTM) that plays a variety of important roles in both physiological and pathological processes, such as the immune response, cell death, aging and neurodegeneration. Identification of site-specific nitrated substrates is fundamental for understanding the molecular mechanisms and biological functions of PTN. In contrast with labor-intensive and time-consuming experimental approaches, here we report the development of the novel software package GPS-YNO2 to predict PTN sites. The software demonstrated a promising accuracy of 76.51%, a sensitivity of 50.09% and a specificity of 80.18% from the leave-one-out validation. As an example application, we predicted potential PTN sites for hundreds of nitrated substrates which had been experimentally detected in small-scale or large-scale studies, even though the actual nitration sites had still not been determined. Through a statistical functional comparison with the nitric oxide (NO) dependent reversible modification of S-nitrosylation, we observed that PTN prefers to attack certain fundamental biological processes and functions. These prediction and analysis results might be helpful for further experimental investigation. Finally, the online service and local packages of GPS-YNO2 1.0 were implemented in JAVA and freely available at: http://yno2.biocuckoo.org/.

Graphical abstract: GPS-YNO2: computational prediction of tyrosine nitration sites in proteins

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Supplementary files

Article information

15 Nov 2010
21 Dec 2010
First published
21 Jan 2011

Mol. BioSyst., 2011,7, 1197-1204
Article type

GPS-YNO2: computational prediction of tyrosine nitration sites in proteins

Z. Liu, J. Cao, Q. Ma, X. Gao, J. Ren and Y. Xue, Mol. BioSyst., 2011, 7, 1197
DOI: 10.1039/C0MB00279H

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