Evidence map›Paper›PMID 39813251›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Assembly-enhanced recognition: A biomimetic pathway to achieve ultrahigh affinities.

Fang-Yuan Chen, Wen-Chao Geng, Meng-Meng Chen, Rong Fu, Han Han, Zhan-Zhan Zhang, Wen-Bo Li, Yuan-Qiu Cheng, Juan-Juan Li, J Fraser Stoddart and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Fang-Yuan ChenCollege of Chemistry, State Key Laboratory of Elemento-Organic Chemistry, Key Laboratory of Functional Polymer Materials (Ministry of Education), Frontiers Science Center for New Organic Matter, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Nankai University, Tianjin 300071, China.
Wen-Chao GengCollege of Chemistry, State Key Laboratory of Elemento-Organic Chemistry, Key Laboratory of Functional Polymer Materials (Ministry of Education), Frontiers Science Center for New Organic Matter, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Nankai University, Tianjin 300071, China.
Meng-Meng ChenCollege of Chemistry, State Key Laboratory of Elemento-Organic Chemistry, Key Laboratory of Functional Polymer Materials (Ministry of Education), Frontiers Science Center for New Organic Matter, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Nankai University, Tianjin 300071, China.
Rong FuCollege of Chemistry, Nankai University, Tianjin 300071, China.
Han HanDepartment of Chemistry, The University of Hong Kong, Hong Kong Special Administrative Region 999077, China.
Zhan-Zhan ZhangSchool of Medical Imaging, Tianjin Medical University, Tianjin 300203, China.
Wen-Bo LiCollege of Chemistry, State Key Laboratory of Elemento-Organic Chemistry, Key Laboratory of Functional Polymer Materials (Ministry of Education), Frontiers Science Center for New Organic Matter, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Nankai University, Tianjin 300071, China.
Yuan-Qiu ChengCollege of Chemistry, State Key Laboratory of Elemento-Organic Chemistry, Key Laboratory of Functional Polymer Materials (Ministry of Education), Frontiers Science Center for New Organic Matter, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Nankai University, Tianjin 300071, China.
Juan-Juan LiCollege of Chemistry, State Key Laboratory of Elemento-Organic Chemistry, Key Laboratory of Functional Polymer Materials (Ministry of Education), Frontiers Science Center for New Organic Matter, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Nankai University, Tianjin 300071, China.
J Fraser StoddartDepartment of Chemistry, The University of Hong Kong, Hong Kong Special Administrative Region 999077, China.ORCID 0000-0003-3161-3697
Kang CaiCollege of Chemistry, Nankai University, Tianjin 300071, China.
Dong-Sheng GuoCollege of Chemistry, State Key Laboratory of Elemento-Organic Chemistry, Key Laboratory of Functional Polymer Materials (Ministry of Education), Frontiers Science Center for New Organic Matter, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Nankai University, Tianjin 300071, China.ORCID 0000-0002-0765-5427

Funding

MOST | National Natural Science Foundation of China (NSFC) 22271164MOST | National Natural Science Foundation of China (NSFC) 22371147MOST | National Natural Science Foundation of China (NSFC) U20A20259
6 · The paper itself

Abstract

On the one hand, nature utilizes hierarchical assemblies to create complex biological binding pockets, enabling ultrastrong recognition toward substrates in aqueous solutions. On the other hand, chemists have been fervently pursuing high-affinity recognition by constructing covalently well-preorganized stereoelectronic cavities. The potential of noncovalent assembly, however, for enhancing molecular recognition has long been underestimated. Inspired by (strept)avidin, an amphiphilic azocalix[4]arene derivative capable of assembly in aqueous solutions has been explored by us and demonstrated to exhibit ultrahigh binding affinity (up to 10

Indexed as

Biomimetic MaterialsBiomimeticsCalixarenesHumansPhotochemotherapyPhotosensitizing AgentsCalixarenesPhotosensitizing Agentsazocalixarenebiomimetic strategycontrolled releasehigh-affinity recognitionnoncovalent assembly

Identifiers

PMID39813251
PMCPMC11759898

What OpenQuestion holds

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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.