Fmoc-Gly-OH-13C2,15N is an Fmoc-protected glycine derivative bearing isotopic labels at the carbon and nitrogen positions, placing it in the class of protected, isotopically labeled amino acid building blocks for peptide chemistry. The molecule contains an Fmoc carbamate protecting group on the amino functionality and a free carboxylic acid, with the side chain consisting of a hydrogen substituent typical of glycine, while the 13C2 and 15N labels enable stable isotope tracking in analytical and labeling workflows. In synthesis, it is employed as a stepwise amino acid input for protected peptide assembly where the isotopic enrichment supports mass spectrometric detection, NMR-based characterization, and quantitative studies of peptide and amino acid incorporation.
Fmoc-Gly-OH-13C2,15N is an Fmoc-protected glycine bearing stable isotope labels (13C2 and 15N) on the amino acid backbone, provided as a peptide synthesis building block for isotope-resolved workflows. The labeled backbone and Fmoc carbamate allow incorporation into peptide sequences using standard protected-amino-acid coupling strategies, while the isotopic enrichment supports quantitative LC-MS and MS-based tracking where mass shifts are required for confident identification and differentiation.
1. Isotope-Labeled Peptide Synthesis
Fmoc-Gly-OH-13C2,15N is used by peptide chemists and analytical peptide developers to prepare isotope-resolved peptide standards and internal calibration materials in which glycine positions must be distinguished by mass. The Fmoc-protected form enables routine solid-phase peptide synthesis workflows, allowing the labeled glycine to be introduced at defined locations within short peptides, protease-digestion mimics, or synthetic fragments used for method validation. Laboratories commonly rely on the 13C2/15N backbone labeling to reduce ambiguity in LC-MS/MS readouts, particularly when analyzing complex mixtures where unlabeled analogs may overlap in precursor or fragment ion space.
2. Proteomics Quantification Standards
Fmoc-Gly-OH-13C2,15N supports quantitative proteomics and targeted mass spectrometry workflows by providing a labeled amino acid building block for generating peptide standards that behave similarly to endogenous tryptic or enzymatic peptides. Researchers use labeled peptide constructs for calibration curves, surrogate peptides, and normalization strategies in experiments where glycine-containing peptides are critical readouts. The stable isotope composition (13C2,15N) provides a predictable mass shift that improves assignment confidence and helps separate labeled standards from native peptide signals during LC-MS detection.
3. Targeted LC-MS Method Development
Fmoc-Gly-OH-13C2,15N is frequently selected for analytical method development and troubleshooting in LC-MS assays that require isotope-resolved controls, such as monitoring, recovery checks, and system suitability evaluations. By incorporating the labeled glycine into defined peptide sequences, method developers can generate reference materials that reflect the chromatographic and fragmentation behavior of glycine-containing targets while maintaining clear isotopic discrimination. This approach is particularly useful when optimizing sample preparation, digestion conditions, and ionization settings, because the labeled peptide standard provides a controllable benchmark for signal stability and data processing.
4. Stable Isotope Tracer Controls
Fmoc-Gly-OH-13C2,15N is also used as a building block for preparing isotope-labeled peptide or peptide-like tracers that serve as controls in chemical biology and metabolic research experiments where isotopic labeling is monitored by mass spectrometry. Researchers may synthesize labeled peptide fragments to validate workflows that quantify incorporation patterns, digestion efficiency, or downstream detection performance. The backbone-specific 13C2/15N enrichment helps ensure that tracer-derived signals can be tracked with high specificity relative to unlabeled controls, supporting robust interpretation of isotope-resolved datasets.
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