Evidence map›Paper›PMID 41169593›Full record

ArticleJACS Au2025

Discovery of Unprecedented Arylation Coupling Cyclopeptide Inspires Natural Product-like Antitubercular Lead Compounds.

Qun Zhang, Wei-Feng Xu, Qian-Qian Jing, Yi-Qian Han, Yan-Wei Wu, Yu-Cheng Gu, Mei-Yan Wei, Chang-Lun Shao

Abstract read
In one paragraph

Article in JACS Au, 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. Review
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

8 authors.

Qun ZhangKey Laboratory of Marine Drugs, The Ministry of Education of China, School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, People's Republic of China.
Wei-Feng XuKey Laboratory of Marine Drugs, The Ministry of Education of China, School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, People's Republic of China.ORCID https://orcid.org/0009-0004-2590-4820
Qian-Qian JingKey Laboratory of Marine Drugs, The Ministry of Education of China, School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, People's Republic of China.
Yi-Qian HanKey Laboratory of Marine Drugs, The Ministry of Education of China, School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, People's Republic of China.
Yan-Wei WuKey Laboratory of Marine Drugs, The Ministry of Education of China, School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, People's Republic of China.
Yu-Cheng GuSyngenta Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, U.K.ORCID https://orcid.org/0000-0002-6400-6167
Mei-Yan WeiKey Laboratory of Marine Drugs, The Ministry of Education of China, School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, People's Republic of China.
Chang-Lun ShaoKey Laboratory of Marine Drugs, The Ministry of Education of China, School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, People's Republic of China.ORCID https://orcid.org/0000-0001-7230-188X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB) remains one of the world's deadliest communicable diseases. Naturally derived antibiotics appear frequently in nature as collections of structurally similar compounds representing an adaptive evolutionary response to drug resistance development. Herein, we report an undescribed versicomycin (

Indexed as

aryl couplingcyclopeptidesdrug developmentmarine natural productstuberculosis

Identifiers

PMID41169593
PMCPMC12569659

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.