Suppr超能文献

利用网络药理学、分子对接和分子动力学模拟解析 在乳腺癌治疗中的作用。

Unraveling the Role of for the Treatment of Breast Cancer Using Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation.

机构信息

School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China.

State Key Lab of Urban Water Resource and Environment, School of Science, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China.

出版信息

Int J Mol Sci. 2023 Feb 10;24(4):3594. doi: 10.3390/ijms24043594.

Abstract

is often used to treat breast cancer, but the molecular mechanism behind the action is unclear. In this study, network pharmacology, molecular docking, and molecular dynamics simulation are combined to reveal the most active compound in and to explore the interaction between the compound molecule and the target protein in the treatment of breast cancer. In total, 25 active compounds and 91 targets were screened out, mainly enriched in lipids in atherosclerosis, the AGE-RAGE signal pathway of diabetes complications, human cytomegalovirus infection, Kaposi-sarcoma-associated herpesvirus infection, the IL-17 signaling pathway, small-cell lung cancer, measles, proteoglycans in cancer, human immunodeficiency virus 1 infection, and hepatitis B. Molecular docking shows that the two most active compounds, i.e., stigmasterol and coptisine, could bind well to the target AKT1. According to the MD simulations, the coptisine-AKT1 complex shows higher conformational stability and lower interaction energy than the stigmasterol-AKT1 complex. On the one hand, our study demonstrates that Scutellaria baicalensis has the characteristics of multicomponent and multitarget synergistic effects in the treatment of breast cancer. On the other hand, we suggest that the best effective compound is coptisine targeting AKT1, which can provide a theoretical basis for the further study of the drug-like active compounds and offer molecular mechanisms behind their roles in the treatment of breast cancer.

摘要

常用来治疗乳腺癌,但作用的分子机制尚不清楚。本研究采用网络药理学、分子对接和分子动力学模拟相结合的方法,揭示了 中的最活跃化合物,并探讨了该化合物分子在治疗乳腺癌中与靶蛋白的相互作用。共筛选出 25 个活性化合物和 91 个靶标,主要富集于动脉粥样硬化中的脂类、糖尿病并发症的 AGE-RAGE 信号通路、人巨细胞病毒感染、卡波西肉瘤相关疱疹病毒感染、IL-17 信号通路、小细胞肺癌、麻疹、癌症中的蛋白聚糖、人类免疫缺陷病毒 1 感染和乙型肝炎。分子对接表明,两种最活跃的化合物,豆甾醇和小檗碱,能够与靶标 AKT1 良好结合。根据 MD 模拟,小檗碱-AKT1 复合物的构象稳定性更高,相互作用能更低。一方面,本研究表明黄芩在治疗乳腺癌方面具有多成分、多靶点协同作用的特点。另一方面,我们建议以 AKT1 为靶点的最佳有效化合物是小檗碱,这可为进一步研究该类药物活性化合物提供理论依据,并为其在治疗乳腺癌中的作用机制提供分子机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c85/9964558/2f9900245024/ijms-24-03594-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验