Development of proteome-derived cyclic peptide libraries via ortho-phthalaldehyde-assisted cyclization.

Ying Wei, Kangze Feng, Wenxuan Hou, Xiaolin Tian, Yuanyuan Xue, Wenhao Zhang, Haiteng Deng

Abstract read

In one paragraph

Article in iScience, 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

7 authors.

Ying WeiMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, State Key Laboratory of Complex, Severe, and Rare Diseases, School of Life Sciences, Tsinghua University, Beijing, China.

Kangze FengMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, State Key Laboratory of Complex, Severe, and Rare Diseases, School of Life Sciences, Tsinghua University, Beijing, China.

Wenxuan HouMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, State Key Laboratory of Complex, Severe, and Rare Diseases, School of Life Sciences, Tsinghua University, Beijing, China.

Xiaolin TianMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, State Key Laboratory of Complex, Severe, and Rare Diseases, School of Life Sciences, Tsinghua University, Beijing, China.

Yuanyuan XueMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, State Key Laboratory of Complex, Severe, and Rare Diseases, School of Life Sciences, Tsinghua University, Beijing, China.

Wenhao ZhangZhejiang Key Laboratory of Multiomics and Molecular Enzymology, Yangtze Delta Region Institute of Tsinghua University, Jiaxing 314006, China.

Haiteng DengMOE Key Laboratory of Bioinformatics, Center for Synthetic and Systematic Biology, State Key Laboratory of Complex, Severe, and Rare Diseases, School of Life Sciences, Tsinghua University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cyclic peptides possess unique structural features and binding capabilities that make them attractive scaffolds for molecular recognition. However, strategies for generating functionally diverse libraries directly from natural proteomes remain comparatively underdeveloped. Here, we present a proteome-informed approach for constructing cyclic peptide libraries by integrating cysteine-enrichment protocols with ortho-phthalaldehyde (OPA)-mediated macrocyclization. This method enables direct library generation from proteome digests and is compatible with liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based annotation and downstream functional screening. We systematically identify key parameters governing OPA-mediated cyclization topology and develop a rule-based pipeline for automated library annotation of OPA-cyclized peptides. Applying this strategy, we generate a library of over 15,000 unique cyclic peptides and perform target-specific screening against human IgG. This yielded cyclic peptide binder candidates, including one lead peptide showing cyclization-dependent IgG-binding potential. Our study establishes an OPA-enabled, proteome-informed workflow for cyclic peptide library construction and annotation.

Indexed as

cyclic peptide libraryIgG-binding peptidemass spectrometryOPAortho-phthalaldehydeprotein recognition

Identifiers

PMID42827899

DOI10.1016/j.isci.2026.117598

PMCPMC13632188

What OpenQuestion holds

Textmetadata

Read underepoch 390

Registered trials

None linked

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.