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Site selectivity for protein tyrosine nitration: insights from features of structure and topological network

Shangli Cheng1, Baofeng Lian, Juan Liang

  • 1State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, and MOE Key Laboratory of Scientific and Engineering Computing, Shanghai Jiao Tong University, Shanghai 200240, China. yileizhao@sjtu.edu.cn.

Molecular Biosystems
|September 24, 2013
PubMed

Insights

Tyrosine nitration, a key protein modification, is selective. Structural and network analysis reveals specific residue environments disfavor nitration, improving predictive models.

Area of Science:

  • Biochemistry
  • Proteomics
  • Structural Biology

Background:

  • Tyrosine nitration is a post-translational modification regulating protein function.
  • This modification impacts cellular signaling pathways, including tyrosine phosphorylation.
  • Tyrosine nitration is a selective process, not occurring at all tyrosine residues in vivo.

Purpose of the Study:

  • To investigate the structural and topological features governing tyrosine nitration selectivity.
  • To develop a more accurate predictive model for tyrosine nitration sites.
  • To understand the chemical environment influencing tyrosine nitration.

Main Methods:

  • Analysis of local protein structures and amino acid topological networks (AAPs, AATs) for nitrated and non-nitrated tyrosine sites.
  • Integration of structural, topological, and sequence features into a predictive model.
  • Utilizing data from the RCSB Protein Data Bank (PDB).

Main Results:

  • Aromatic and aliphatic residues with large, aromatic, aliphatic, or acidic side chains are disfavored for nitration.
  • The predictive model incorporating structural and network features achieved 63.30% sensitivity and 92.24% specificity.
  • Improved accuracy compared to models relying solely on protein sequence information.

Conclusions:

  • Site selectivity in tyrosine nitration is influenced by local protein structure and chemical environment.
  • An open, hydrophilic, and high-pH environment around tyrosine residues may favor nitration.
  • Structural and network features are crucial for accurate prediction of tyrosine nitration sites.

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