Zhang Haixia
College of Traditional Chinese Medicine, Hebei North University, Zhangjiakou City, 075000, China.
Iran J Pharm Res. 2024 Dec 25;23(1):e153579. doi: 10.5812/ijpr-153579. eCollection 2024 Jan-Dec.
Herbal compounds sourced from various plants are becoming targeted therapies for breast cancer.
This study aims to explore the potential of focusing on herbal compounds as targeted therapies for breast cancer using computational techniques.
A total of 129 herbal compounds linked with breast cancer were identified from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database. Molecular docking and MD simulation were carried out against three protein targets linked with breast cancer. Network pharmacology was used to identify the common plant sources for the bioactive compounds, and interaction networks were constructed. The ADME-toxicity profiles and density functional theory (DFT) analysis were calculated for the top docking hits.
Dipiperitylmagnolol and sophoranone were identified as the top docking hits and lead compounds. Network pharmacology analysis revealed as the common plant sources having multiple bioactive compounds. MD simulation analysis revealed conformational stability of the top docking hits. The analyses underscore the robust binding potential of dipiperitylmagnolol and its possible therapeutic relevance in targeting breast cancer pathways. ADME-toxicity and DFT analysis provided insights into the pharmacokinetic and electronic behavior of the top docking hit. Combinatorial study of herbal therapies with conventional treatments will increase the therapeutic efficacy for breast cancer treatment.
The study provides insights into the implications of herbal compounds as targeted therapy for breast cancer. Therefore, the study recommends further experimental validation and development of herbal-based compounds for the treatment of breast cancer.
源自各种植物的草药化合物正成为乳腺癌的靶向治疗药物。
本研究旨在利用计算技术探索将草药化合物作为乳腺癌靶向治疗药物的潜力。
从中药系统药理学数据库及分析平台(TCMSP)数据库中鉴定出129种与乳腺癌相关的草药化合物。针对三种与乳腺癌相关的蛋白质靶点进行分子对接和分子动力学(MD)模拟。利用网络药理学确定生物活性化合物的常见植物来源,并构建相互作用网络。对对接得分最高的化合物进行药物代谢动力学(ADME)毒性分析和密度泛函理论(DFT)分析。
二聚厚朴酚和槐果酮被确定为对接得分最高的化合物及先导化合物。网络药理学分析显示[此处原文缺失具体植物名称]为含有多种生物活性化合物的常见植物来源。MD模拟分析显示对接得分最高的化合物具有构象稳定性。这些分析强调了二聚厚朴酚强大的结合潜力及其在靶向乳腺癌通路方面可能的治疗相关性。ADME毒性和DFT分析为对接得分最高的化合物的药代动力学和电子行为提供了见解。草药疗法与传统治疗方法的联合研究将提高乳腺癌治疗的疗效。
本研究为草药化合物作为乳腺癌靶向治疗的意义提供了见解。因此,该研究建议对基于草药的化合物进行进一步的实验验证和开发,用于治疗乳腺癌。