Evidence map›Paper›PMID 33349694›Full record

ArticleNature chemistry2021

Selection of DNA-encoded chemical libraries against endogenous membrane proteins on live cells.

Yiran Huang, Ling Meng, Qigui Nie, Yu Zhou, Langdong Chen, Shilian Yang, Yi Man Eva Fung, Xiaomeng Li, Cen Huang, Yan Cao and 2 more

Abstract read
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In one paragraph

Article in Nature chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

  1. Review
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  3. Identifying a cancer therapeutic target: Cell-SELEX identifies a membrane protein for aptamer-mediated growth suppression.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  6. Review
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  10. Article
  11. Review
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  13. Article
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  17. Review
  18. Small-molecule discovery through DNA-encoded libraries.Nature reviews. Drug discovery · 2023
    Review
  19. Review
  20. Article
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

12 authors.

Yiran HuangDepartment of Chemistry and State Key Laboratory of Synthetic Chemistry, The University of Hong Kong, Hong Kong SAR, China.
Ling MengDepartment of Chemistry and State Key Laboratory of Synthetic Chemistry, The University of Hong Kong, Hong Kong SAR, China.ORCID http://orcid.org/0000-0003-3234-4863
Qigui NieChongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, China.ORCID http://orcid.org/0000-0002-5676-6852
Yu ZhouDepartment of Chemistry and State Key Laboratory of Synthetic Chemistry, The University of Hong Kong, Hong Kong SAR, China.ORCID http://orcid.org/0000-0003-1497-8264
Langdong ChenSchool of Pharmacy, Second Military Medical University, Shanghai, China.ORCID http://orcid.org/0000-0002-9755-7053
Shilian YangChongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, China.ORCID http://orcid.org/0000-0001-9775-5992
Yi Man Eva FungDepartment of Chemistry and State Key Laboratory of Synthetic Chemistry, The University of Hong Kong, Hong Kong SAR, China.ORCID http://orcid.org/0000-0001-5896-1558
Xiaomeng LiDepartment of Chemistry and State Key Laboratory of Synthetic Chemistry, The University of Hong Kong, Hong Kong SAR, China.ORCID http://orcid.org/0000-0002-2819-9678
Cen HuangChongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, China.
Yan CaoSchool of Pharmacy, Second Military Medical University, Shanghai, China. caoyan@smmu.edu.cn.ORCID http://orcid.org/0000-0001-5510-9773
Yizhou LiChongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, China. yizhouli@cqu.edu.cn.ORCID http://orcid.org/0000-0003-1650-3780
Xiaoyu LiDepartment of Chemistry and State Key Laboratory of Synthetic Chemistry, The University of Hong Kong, Hong Kong SAR, China. xiaoyuli@hku.hk.ORCID http://orcid.org/0000-0002-8907-6727

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Membrane proteins on the cell surface perform a myriad of biological functions; however, ligand discovery for membrane proteins is highly challenging, because a natural cellular environment is often necessary to maintain protein structure and function. DNA-encoded chemical libraries (DELs) have emerged as a powerful technology for ligand discovery, but they are mainly limited to purified proteins. Here we report a method that can specifically label membrane proteins with a DNA tag, and thereby enable target-specific DEL selections against endogenous membrane proteins on live cells without overexpression or any other genetic manipulation. We demonstrate the generality and performance of this method by screening a 30.42-million-compound DEL against the folate receptor, carbonic anhydrase 12 and the epidermal growth factor receptor on live cells, and identify and validate a series of novel ligands for these targets. Given the high therapeutic significance of membrane proteins and their intractability to traditional high-throughput screening approaches, this method has the potential to facilitate membrane-protein-based drug discovery by harnessing the power of DEL.

Indexed as

Antibodies, ImmobilizedCarbonic AnhydrasesDNAErbB ReceptorsFluorescein-5-isothiocyanateFolate Receptors, GPI-AnchoredHeLa CellsHumansLigandsMicroscopy, FluorescenceSmall Molecule LibrariesAntibodies, ImmobilizedCarbonic Anhydrasescarbonic anhydrase XIIDNAErbB ReceptorsFluorescein-5-isothiocyanateFolate Receptors, GPI-AnchoredLigandsSmall Molecule Libraries

Identifiers

What OpenQuestion holds

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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.