Evidence map›Paper›PMID 42102182›Full record

ArticleProtein engineering, design & selection : PEDS2026

A photo-enhanced oxidative coupling for site-specific protein Labeling via noncanonical amino acid incorporation.

Xin Shang, Bin Ma, Wei Niu, Jiantao Guo

Abstract read
In one paragraph

Article in Protein engineering, design & selection : PEDS, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xin ShangDepartment of Chemistry, University of Nebraska-Lincoln, Lincoln, NE, 68588, United States.
Bin MaDepartment of Chemistry, University of Nebraska-Lincoln, Lincoln, NE, 68588, United States.
Wei NiuDepartment of Chemical & Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68588, United States.
Jiantao GuoDepartment of Chemistry, University of Nebraska-Lincoln, Lincoln, NE, 68588, United States.ORCID 0000-0001-6983-9953

Funding

Targeted mass spectrometry approaches to understand CART processing and recepter interactionsP20GM113126 · NIGMS · UNIVERSITY OF NEBRASKA LINCOLN · PI GUO, JIANTAO · 2016 to 2025
$20.8M
Developing synthetic chemical biology strategies for biochemical investigations and biomedical applicationsR35GM149322 · NIGMS · UNIVERSITY OF NEBRASKA LINCOLN · PI Jiantao Guo · 2023 to 2026
$1.5M
NIGMS NIH HHS P20 GM113126NIGMS NIH HHS R35 GM149322
6 · The paper itself

Abstract

Genetically encoded noncanonical amino acids (ncAAs) enable site-specific installation of chemical functionalities into proteins, expanding the scope of protein engineering and bioconjugation. Here we report a photo-enhanced oxidative coupling strategy that leverages a vinyl sulfide-containing ncAA for selective protein labeling. An ortho-naphthoquinone methide (oNQM) intermediate is generated in situ from a stable precursor under mild oxidative conditions using ferricyanide, and labeling efficiency is markedly enhanced upon 365 nm irradiation. Ethyl vinyl sulfide was identified as a compact, electronically suitable dienophile that can be incorporated into proteins either through lysine modification or via genetic encoding of N6-((2-(vinylthio)ethoxy)carbonyl)-L-lysine (VtK). Under photo-enhanced oxidative conditions, robust labeling was observed at pH 6-7 with minimal background modification of wild-type proteins. Site-specific incorporation of VtK into the outer membrane protein OmpX enabled selective labeling in cell lysates and in live Escherichia coli cells, demonstrating compatibility with complex biological environments. This work establishes a genetically encodable, photo-enhanced oxidative coupling modality that complements existing ncAA-based bioconjugation strategies and expands the protein engineering toolbox.

Indexed as

Amino AcidsBacterial Outer Membrane ProteinsEscherichia coli ProteinsLysineOxidative CouplingProtein EngineeringEscherichia coliLightOxidation-ReductionStaining and LabelingAmino AcidsBacterial Outer Membrane ProteinsEscherichia coli ProteinsLysinenoncanonical amino acidoxidative couplingphoto-enhanced bioconjugationprotein engineeringsite-specific protein labeling

Identifiers

PMID42102182
PMCPMC13170128

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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.