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ORIGINAL RESEARCH article

Front. Chem.

Sec. Medicinal and Pharmaceutical Chemistry

Volume 13 - 2025 | doi: 10.3389/fchem.2025.1651402

This article is part of the Research TopicNew Theories, Strategies, and Technologies for Designing Original Medicinal MoleculesView all 3 articles

Discovery of Compound 1105486 as a Selective Inhibitor of B4GALT1: Potential for Pancreatic Cancer Therapy

Provisionally accepted
Xu  YunyunXu YunyunMou  YipingMou Yiping*
  • Hangzhou Medicial College, Hangzhou, China

The final, formatted version of the article will be published soon.

Targeting aberrant β-1,4-galactosyltransferase 1 (B4GALT1) activity represents an unexplored therapeutic avenue for pancreatic ductal adenocarcinoma (PDAC). Guided by a concise active-learning structure-based workflow, we rapidly triaged 22.6 million compounds and singled out 1105486 for experimental characterization. In PANC-1 cells, the molecule suppressed proliferation with an IC₅₀ of 19.8 ± 1.3 µM, while hTERT-HPNE epithelial cells retained > 95 % viability at concentrations up to 80 µM, indicating an encouraging initial safety window. Mechanistically, 1105486 engages the UDP-galactose pocket through stable hydrogen bonds to ARG187 and GLU313, a binding mode corroborated by 1 µs molecular-dynamics simulations and MM/GBSA energetics. Unlike previously reported glycosyltransferase inhibitors, which often lack selectivity and may affect multiple family members, 1105486 specifically targets B4GALT1 with high selectivity, occupying its unique catalytic pocket. To our knowledge, 1105486 constitutes the first reported small-molecule inhibitor of B4GALT1 and establishes a tractable chemical scaffold for optimization toward sub-micromolar potency and in-vivo evaluation. The compound's selective cytotoxic profile, promising physicochemical properties, and the potential for further development highlight its in vivo efficacy and its role as a lead candidate for the next generation of glycosylationdirected therapeutics for PDAC.

Keywords: PDAC, B4GALT1, Active-learning, Computational-experimental integration, cytotoxicity safety window

Received: 21 Jun 2025; Accepted: 30 Jul 2025.

Copyright: © 2025 Yunyun and Yiping. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mou Yiping, Hangzhou Medicial College, Hangzhou, China

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