Bioinformatic Prediction of S-Nitrosylation Sites in Large Protein Datasets

Rosario Carmona; M Claros; Juan de Alché

doi:10.1007/978-1-4939-7695-9_19

Bioinformatic Prediction of S-Nitrosylation Sites in Large Protein Datasets

Methods Mol Biol. 2018:1747:241-250. doi: 10.1007/978-1-4939-7695-9_19.

Authors

Rosario Carmona¹, M Claros², Juan de Alché³

Affiliations

¹ Plant Reproductive Biology Laboratory, Department of Biochemistry, Cellular and Molecular Biology of Plants, Estación Experimental del Zaidín (CSIC), Granada, Spain.
² Departamento de Biología Molecular y Bioquímica, Universidad de Málaga, Málaga, Spain.
³ Plant Reproductive Biology Laboratory, Department of Biochemistry, Cellular and Molecular Biology of Plants, Estación Experimental del Zaidín (CSIC), Granada, Spain. juandedios.alche@eez.csic.es.

PMID: 29600464
DOI: 10.1007/978-1-4939-7695-9_19

Abstract

S-nitrosylation is an essential and reversible posttranslational modification of proteins involved in numerous biological processes. The experimental determination of S-nitrosylation sites is laborious and time-consuming. Therefore, the use of computational prediction tools of this modification represents a convenient first approach to generate useful information for subsequent experimental verification. Here we describe an in silico analysis pipeline to integrate the use of several bionformatic tools while dealing with big query protein sets.

Keywords: Nitric oxide; PTMs prediction; Posttranslational modification; S-nitrosylation.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Computational Biology* / methods
Molecular Sequence Annotation
Nitrosation
Protein Processing, Post-Translational*
Proteins / metabolism*
S-Nitrosothiols / metabolism*

Substances

Proteins
S-Nitrosothiols