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调控凝聚物微极性以增强小分子药物靶向性。

Navigating condensate micropolarity to enhance small-molecule drug targeting.

作者信息

Ouyang Jian, Chen Junlin, Wu Zhili, You Kaiqiang, Chen Taoyu, Gao Yi Qin, Li Pilong, Zhang Xin, Li Tingting

机构信息

Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.

Key Laboratory for Neuroscience, Ministry of Education/National Health Commission of China, Peking University, Beijing, China.

出版信息

Nat Chem Biol. 2025 Sep 9. doi: 10.1038/s41589-025-02017-9.

Abstract

Many pharmaceutical targets partition into biomolecular condensates, whose microenvironments can significantly influence drug distribution. Nevertheless, it is unclear how drug design principles should adjust for these targets to optimize target engagement. To address this question, we systematically investigated how condensate microenvironments influence drug-targeting efficiency. We found that condensates highlight a notable heterogeneity, with nonpolar-residue-enriched condensates being more hydrophobic and housing more hydrophobic drugs. Furthermore, L1000 dataset analysis revealed a strong positive correlation between inhibitor hydrophobicity and targeting efficiency for phase-separated proteins, represented by estrogen receptor 1 (ESR1) enriched with nonpolar residues. We developed random forest models to predict inhibitor targeting efficiency from molecular properties, with hydrophobicity identified as a key determinant. In cellulo experiments with ESR1 condensates confirmed that both binding affinity and hydrophobicity of inhibitors contribute significantly to potency. These results suggest a new drug design principle for phase-separated proteins by considering condensate micropolarity, potentially leading to drugs with optimal target engagement.

摘要

许多药物靶点会分配到生物分子凝聚物中,其微环境会显著影响药物分布。然而,尚不清楚药物设计原则应如何针对这些靶点进行调整以优化靶点结合。为了解决这个问题,我们系统地研究了凝聚物微环境如何影响药物靶向效率。我们发现凝聚物表现出显著的异质性,富含非极性残基的凝聚物更疏水,容纳更多疏水药物。此外,L1000数据集分析显示,以富含非极性残基的雌激素受体1(ESR1)为代表的相分离蛋白,抑制剂疏水性与靶向效率之间存在强正相关。我们开发了随机森林模型,从分子性质预测抑制剂靶向效率,疏水性被确定为关键决定因素。在ESR1凝聚物的细胞实验证实,抑制剂的结合亲和力和疏水性对效力都有显著贡献。这些结果通过考虑凝聚物微极性,为相分离蛋白提出了一种新的药物设计原则,可能会产生具有最佳靶点结合的药物。

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