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July 1, 2025

AI-designed inhibitor targets key enzyme to fight prostate cancer drug resistance

Cluster analysis of molecular dynamics simulations involving BCA, 3βHSD1 and NAD+. Credit: Proceedings of the National Academy of Sciences (2025). DOI: 10.1073/pnas.2422267122
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Cluster analysis of molecular dynamics simulations involving BCA, 3βHSD1 and NAD+. Credit: Proceedings of the National Academy of Sciences (2025). DOI: 10.1073/pnas.2422267122

Prostate cancer is one of the most common malignancies in men globally. Hormonal therapies targeting the androgen–androgen receptor axis have significantly delayed disease progression. However, drug resistance remains inevitable, and new therapeutic targets and strategies are required to overcome androgen receptor pathway inhibitor (ARPI) resistance.

In a study in the Proceedings of the National Academy of Sciences, Dr. Li Zhenfei's team from the Center for Excellence in Molecular Cell Science (Shanghai Institute of Biochemistry and Cell Biology) of the Chinese Academy of Sciences (CAS), Dr. Hu Youhong's team and Liu Jia's team from the Shanghai Institute of Materia Medica of CAS, and Dr. Ren Ruobing's team from Fudan University designed a novel 3βHSD1 inhibitor, HEAL-116, which has superior enzymatic activity and favorable pharmacokinetic properties, providing a new strategy for and overcoming resistance to second-generation ARPIs.

Previous research by Dr. Li's team has identified the metabolic enzyme 3βHSD1 as a key driver for prostate cancer progression, which regulates the metabolism of androgen, progesterone, and abiraterone, mediating resistance to ARPIs, and has also identified biochanin A (BCA) as a potent 3βHSD1 inhibitor to suppress the development of prostate cancer in , mouse models, and even patients. However, BCA's low oral bioavailability hindered its clinical translation.

In this study, the researchers constructed a high-precision structure model of 3βHSD1 by integrating AlphaFold2 protein structure predictions, molecular dynamics simulations, quantum chemistry calculations and other techniques, and revealed its unique catalytic mechanism and substrate-binding pocket characteristics.

Through systematic optimization of BCA's molecular geometry and charge distribution, the researchers developed HEAL-116, a highly specific inhibitor with enhanced binding affinity and improved oral bioavailability via hydrophilic group modifications.

In vivo and in vitro experiments showed that HEAL-116 potently suppressed 3βHSD1 activity and inhibited the growth of prostate cancer xenografts, when used alone or in combination with ARPIs. The specificity of HEAL-116 was also evaluated, showing no significant effects on transcriptome and kinome.

This study validates the artificial intelligence-driven rational drug design strategy. It provides a new strategy to overcome , and promotes the clinical application of 3βHSD1-targeted therapy.

More information: Dongyin He et al, Fine structural design of 3βHSD1 inhibitors for prostate cancer therapy, Proceedings of the National Academy of Sciences (2025).

Journal information: Proceedings of the National Academy of Sciences

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A novel AI-designed inhibitor, HEAL-116, targets the enzyme 3βHSD1, which drives prostate cancer progression and resistance to androgen receptor pathway inhibitors. HEAL-116 demonstrates high specificity, improved oral bioavailability, and effectively suppresses tumor growth in preclinical models, offering a promising approach to overcoming drug resistance in prostate cancer.

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