Evidence map›Paper›PMID 40678487›Full record

ArticleJournal of pharmaceutical analysis2025

Scaffold and SAR studies on c-MET inhibitors using machine learning approaches.

Jing Zhang, Mingming Zhang, Weiran Huang, Changjie Liang, Wei Xu, Jinghua Zhang, Jun Tu, Innocent Okohi Agida, Jinke Cheng, Dong-Qing Wei and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of pharmaceutical analysis, 2025. 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

13 authors.

Jing ZhangClinical Research Institute & School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Mingming ZhangDepartment of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Weiran HuangEngineering Research Center of Cell & Therapeutic Antibody, School of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, China.
Changjie LiangAcademy of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China.
Wei XuCore Facility of Basic Medical Sciences, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Jinghua ZhangCore Facility of Basic Medical Sciences, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Jun TuDepartment of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Innocent Okohi AgidaDepartment of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Jinke ChengDepartment of Biochemistry and Molecular Cell Biology, Shanghai Key Laboratory for Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Dong-Qing WeiSchool of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200030, China.
Buyong MaEngineering Research Center of Cell & Therapeutic Antibody, School of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, China.
Yanjing WangEngineering Research Center of Cell & Therapeutic Antibody, School of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, China.
Hongsheng TanClinical Research Institute & School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous c-mesenchymal-epithelial transition (c-MET) inhibitors have been reported as potential anticancer agents. However, most fail to enter clinical trials owing to poor efficacy or drug resistance. To date, the scaffold-based chemical space of small-molecule c-MET inhibitors has not been analyzed. In this study, we constructed the largest c-MET dataset, which included 2,278 molecules with different structures, by inhibiting the half maximal inhibitory concentration (IC

Indexed as

Active cliffc-MET inhibitorsHierarchical clusteringMachine learningScaffold based chemical spaceStructure-activity relationship

Identifiers

PMID40678487
PMCPMC12268054

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.