Proteomics of Nitrotyrosine: Integrating Mass Spectrometry and Immunodetection in Redox‐Driven Pathology

Nitrooxidative stress, driven by excess reactive nitrogen species like peroxynitrite, contributes to the pathogenesis of many chronic diseases. Among its molecular footprints, 3‐nitrotyrosine (3NT) has emerged as a biologically relevant marker of protein nitration. Its accumulation reflects oxidative damage and altered protein function, positioning it as a promising biomarker. Proteomics has advanced our understanding of nitrooxidative stress and its clinical implications. The integration of high‐resolution MS with immunoaffinity and structural modeling enables precise mapping of nitration sites and functional interpretation. However, limitations such as low stoichiometry, ion suppression, and antibody cross‐reactivity still constrain the field. Emerging computational predictors and miniaturized platforms offer promising avenues for expanding the clinical utility of 3NT. Future efforts should focus on standardizing workflows, validating site‐specific modifications, and translating proteomic insights into diagnostic and therapeutic strategies. This review outlines the biochemical mechanisms of 3NT formation, emphasizing peroxynitrite‐dependent and heme peroxidase‐mediated pathways. Proteomic strategies for detecting and quantifying nitrated proteins are discussed, including mass spectrometry workflows, enrichment techniques, and immunodetection. Challenges in site‐specific identification, antibody specificity, and ionization‐induced fragmentation are addressed. Disease‐specific patterns of 3NT accumulation in neurodegenerative, cardiovascular, and oncologic contexts are highlighted, along with in silico prediction of nitration sites. Despite significant methodological advances, key limitations such as low nitration stoichiometry, antibody cross‐reactivity, and ionization‐dependent artifacts continue to challenge confident site‐specific analysis of 3‐nitrotyrosine. Future progress will depend on improved enrichment strategies, standardized mass spectrometry workflows, and the integration of computational prediction tools with experimental validation. Addressing these gaps will be essential for translating nitrotyrosine profiling into robust mechanistic and clinical applications.