Artemisinins ameliorate polycystic ovarian syndrome by mediating LONP1-CYP11A1 interaction

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL
Yang Liu, Jing-jing Jiang, Shao-yue Du, Liang-shan Mu, Jian-jun Fan, Jun-chi Hu, Yao Ye, Meng Ding, Wei-yu Zhou, Qiu-han Yu, Yi-fan Xia, Hong-yu Xu, Yi-jie Shi, Shu-wen Qian, Yan Tang, Wei Li, Yong-jun Dang, Xi Dong, Xiao-ying Li, Cong-jian Xu, Qi-qun Tang
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引用次数: 0

Abstract

Polycystic ovary syndrome (PCOS), a prevalent reproductive disorder in women of reproductive age, features androgen excess, ovulatory dysfunction, and polycystic ovaries. Despite its high prevalence, specific pharmacologic intervention for PCOS is challenging. In this study, we identified artemisinins as anti-PCOS agents. Our finding demonstrated the efficacy of artemisinin derivatives in alleviating PCOS symptoms in both rodent models and human patients, curbing hyperandrogenemia through suppression of ovarian androgen synthesis. Artemisinins promoted cytochrome P450 family 11 subfamily A member 1 (CYP11A1) protein degradation to block androgen overproduction. Mechanistically, artemisinins directly targeted lon peptidase 1 (LONP1), enhanced LONP1-CYP11A1 interaction, and facilitated LONP1-catalyzed CYP11A1 degradation. Overexpression of LONP1 replicated the androgen-lowering effect of artemisinins. Our data suggest that artemisinin application is a promising approach for treating PCOS and highlight the crucial role of the LONP1-CYP11A1 interaction in controlling hyperandrogenism and PCOS occurrence.

Abstract Image

青蒿素通过介导 LONP1-CYP11A1 相互作用改善多囊卵巢综合征
多囊卵巢综合征(PCOS)是育龄妇女普遍存在的一种生殖障碍,其特点是雄激素过多、排卵功能障碍和多囊卵巢。尽管多囊卵巢综合征的发病率很高,但对其进行特异性药物干预却很困难。在这项研究中,我们发现青蒿素类药物是抗多囊卵巢综合征的药物。我们的研究结果表明,青蒿素衍生物能有效缓解啮齿类动物模型和人类患者的多囊卵巢综合征症状,通过抑制卵巢雄激素合成抑制高雄激素血症。青蒿素类药物能促进细胞色素 P450 家族 11 亚家族 A 成员 1 (CYP11A1) 蛋白降解,从而阻止雄激素过度分泌。从机理上讲,青蒿素类药物直接靶向长肽酶1(LONP1),增强了LONP1-CYP11A1的相互作用,并促进了LONP1催化的CYP11A1降解。过表达 LONP1 复制了青蒿素降低雄激素的作用。我们的数据表明,应用青蒿素是治疗多囊卵巢综合征的一种有前景的方法,并强调了LONP1-CYP11A1相互作用在控制高雄激素和多囊卵巢综合征发生中的关键作用。
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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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