Authors
Junzhe Wang, Livia Philip, Tharuka Beragama Vithanage, Andrew Gulewicz, Hawau Abdulsalam, Hien M Nguyen
Published in
Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents. Volume 35. Issue 4. Pages 834-846. Epub Apr 25, 2026.
Abstract
Heparanase (HPSE) plays a critical role in tumor progression by degrading heparan sulfate chains in the extracellular matrix and modulating the tumor microenvironment. As a result, it has emerged as a promising therapeutic target. Aminoglycoside-derived sulfated glycan mimetics have shown potential as HPSE inhibitors, but rational optimization is challenged by complex steric and electrostatic interactions. Here, we used three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling to identify key structural features governing HPSE inhibition, providing new predictive structure-activity insights for sulfated aminoglycoside-based HPSE inhibitors. Guided by these insights, we evaluated the lead compound L17 in HPSE-dependent cancer cell lines and observed concentration-dependent inhibition of proliferation, suppression of invasion, and reduction of extracellular HPSE levels. In silico ADMET predictions flagged CYP3A4 as a potential liability, but experimental assays confirmed minimal inhibition, indicating a favorable metabolic profile. This integrated approach provides mechanistic insight into aminoglycoside-based HPSE inhibitors and supports their rational optimization as anticancer therapeutics.
PMID:
42446733
Bibliographic data and abstract were imported from PubMed on 14 Jul 2026.
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