Work

Discovery of a Potent c-MET Inhibitor for Non-Small Cell Lung Cancer Treatment by AI-Based and Docking-Based Virtual Screening

Year: 2025

Type: article

Abstract: The dysregulation of the mesenchymal-epithelial transition factor (c-MET) signaling pathway is linked to the development and drug resistance of non-small cell lung cancer (NSCLC), highlighting the need for small-molecule inhibitors targeting c-MET. In this study, we identified six potential c-MET inhibitors from a compound library using structure-based and AI-based virtual screening. Four compounds demonstrated c-MET inhibitory activity, with compound 2 exhibiting potent inhibition at an IC 50 of 40.1 nM. Further studies showed that compound 2 effectively inhibited NSCLC cell proliferation, comparable to that of positive controls. ADMET predictions indicate favorable drug-like properties, suggesting its potential as a novel c-MET inhibitor. Molecular dynamics simulations revealed that compound 2 stabilizes its conformation through interactions with Ala1221, Pro1158, and Lys1110, providing valuable insights for further drug development.

Source: ACS Medicinal Chemistry Letters

DOI: 10.1021/acsmedchemlett.5c00503

Authors: Qi Shen, He Li, Minyu Cheng, Yicong Bian, Li Li

Institutions: Zhejiang Hospital, First Affiliated Hospital of Soochow University

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funder: Key Research and Development Program of Zhejiang Province