Work

Identification of novel HIF2α inhibitors: a structure‐based virtual screening approach

Year: 2026

Type: article

Abstract: HIF2α is aberrantly upregulated in some renal cell carcinomas due to VHL mutations, supporting HIF2α inhibition as a compelling therapeutic approach for such cases. Therefore, the six compounds (designated as Compounds 1–6) were screened from the Maybridge database based on the constructed pharmacophore model and molecular docking. Subsequently, the docking models of Compounds 1–6 with HIF2α were analysed. Affinity assays revealed that both Compound-4 and Compound-5 exhibited robust affinity towards human recombinant HIF2α. MD simulations displayed that Compound-4 and Compound-5 stably bound to the active pocket of HIF2α. Cell experiments demonstrated that Compound-4 effectively inhibited the growth of the 786-O human renal cell carcinomas line (IC50 = 1.35 ± 0.06 μM). This study demonstrates that Compound-4 may serve as a potential candidate compound for renal cell carcinomas therapy.

Source: Journal of Enzyme Inhibition and Medicinal Chemistry

DOI: 10.1080/14756366.2025.2606435

Authors: Shasha Zhou, Shengnan Yin, Shudan Yang, Yuting Wang, Panfeng Feng

Institutions: Second Affiliated Hospital of Nantong University, Nanjing University of Chinese Medicine, China Pharmaceutical 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: gold

Estimated APC paid: $2,306