Evidence map›Paper›PMID 42643689›Full record

ReviewRSC advances2026

Advancements and applications of click chemistry in protein labeling and bioconjugation.

Usman Nazeer, Guoting Qin, Chengzhi Cai

Abstract readReview
In one paragraph

Review in RSC advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

3 authors.

Usman NazeerDepartment of Chemistry, University of Houston Houston TX 77204 USA unazeer@cougarnet.uh.edu.ORCID https://orcid.org/0009-0004-2598-7224
Guoting QinDepartment of Vision Sciences, University of Houston Houston TX 77204 USA.
Chengzhi CaiDepartment of Chemistry, University of Houston Houston TX 77204 USA unazeer@cougarnet.uh.edu.ORCID https://orcid.org/0000-0001-9800-7769

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Click chemistry has emerged as a versatile and efficient chemical strategy for constructing complex molecules under mild conditions. Its core reaction is copper(i)-catalyzed azide-alkyne cycloaddition (CuAAC), which provides high yields, stereoselectivity, and biocompatibility. Click reactions, particularly the copper(i)-catalyzed azide-alkyne cycloaddition (CuAAC) and strain-promoted azide-alkyne cycloaddition (SPAAC), were highlighted for their high selectivity, efficiency, and bioorthogonality. In addition to these, other click reactions reported in the study included thiol-ene reactions, Diels-Alder cycloadditions (particularly inverse electron-demand Diels-Alder, IEDDA), and electro-click chemistry, all of which expanded the click chemistry toolbox for diverse biological applications. Recent advancements in both CuAAC and copper-free click strategies are explored, emphasizing their applications in protein tagging, imaging, proteomics, and drug development. Various innovative methodologies, such as bioorthogonal non-canonical amino acid tagging (BONCAT), click chemistry-assisted RNA interactome capture (CARIC), electro-click chemistry, and cross-linking mass spectrometry, demonstrate the versatility of click reactions in studying cellular processes and biomolecular interactions. Furthermore, the review highlights the use of click chemistry in live-cell labeling, biomaterials development, enzyme profiling, and disease-related studies through protein tagging. Copper-free strategies were emphasized for overcoming toxicity limitations. Overall, click chemistry was presented as a versatile and rapidly evolving platform for precise biomolecular modification.

Identifiers

PMID42643689
PMCPMC13504544

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Registered trials

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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.