ArticleProtein science : a publication of the Protein Society2024
Efficient and economic protein labeling for NMR in mammalian expression systems: Application to a preT-cell and T-cell receptor protein.
Article in Protein science : a publication of the Protein Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The trial behind it
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Cancers modulate processing and presentation of p53 neoantigens to evade T cell detection.Immunity · 2026Article
- Methyl-specific NMR of therapeutic antibodies: cost-effective isotopic labeling strategies in CHO cells for high-resolution structural characterization.Journal of biomolecular NMR · 2026Article
- Human cells for human proteins: Isotope labeling in mammalian cells in suspension for functional NMR studies.Protein science : a publication of the Protein Society · 2026Article
- In-Cell Residue-Resolved NMR of Micromolar α-Synuclein and Tau at 310 K.Journal of the American Chemical Society · 2025Article
- Atomistic TCR-ligand interactions instruct memory T-cell differentiation.bioRxiv : the preprint server for biology · 2025Article
- Efficient and economic protein labeling for NMR in mammalian expression systems: Application to a preT-cell and T-cell receptor protein.Protein science : a publication of the Protein Society · 2024Article
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 2 countries.
Funding
Abstract
Protein nuclear magnetic resonance (NMR) spectroscopy relies on the ability to isotopically label polypeptides, which is achieved through heterologous expression in various host organisms. Most commonly, Escherichia coli is employed by leveraging isotopically substituted ammonium and glucose to uniformly label proteins with
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.