Evidence map›Paper›PMID 40666468›Full record

ArticleACS medicinal chemistry letters2025

Discovery of Novel c‑MET Inhibitors for Hepatocellular Carcinoma Using an Integrated Virtual Screening Approach.

Rushan Fei, Na Lin, Xin Zhang, Lei Xu, Qingnan Zhang, Zhichao Pan, Xiaowu Dong, Weilin Wang

Abstract read
In one paragraph

Article in ACS medicinal chemistry letters, 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

8 authors.

Rushan FeiDepartment of Colorectal Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, No. 79, Qingchun Road, Hangzhou, Zhejiang Province 310003, China.
Na LinDepartment of Burn and Plastic Surgery, Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310000, PR China.
Xin ZhangAffiliated Yongkang First People's Hospital and School of Pharmaceutical Sciences, Hangzhou Medical College, Hangzhou 310053, P.R. China.
Lei XuSchool of Electrical and Information Engineering, Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou 212003, China.
Qingnan ZhangCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Zhichao PanCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Xiaowu DongCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.ORCID https://orcid.org/0000-0002-2178-4372
Weilin WangDepartment of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, No. 88 Jiefang Road, Hangzhou, Zhejiang 310009, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related mortality worldwide, with the efficacy of current targeted therapies limited by drug resistance and adverse effects. The receptor tyrosine kinase c-MET has been identified as a promising target for HCC therapy due to its involvement in tumor progression, metastasis, and poor prognosis. However, no c-MET inhibitors have been approved for HCC treatment. This study integrates a multistep virtual screening workflow, incorporating molecular docking, machine learning-based predictions, and molecular dynamics simulations, to identify novel c-MET inhibitors with unique structural frameworks. Among several promising candidates, compound

Indexed as

Hepatocellular carcinomaMETmolecular dynamicsVirtual screening

Identifiers

PMID40666468
PMCPMC12257410

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.