利用基于结构的经典药物设计,将植物化学物质重新用于抗击乳腺癌(MCF-7)。

Faten Essam Hussain Aldoghachi, Amjad Oraibi, Noor Hamid Mohsen, Sara S Hassan
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引用次数: 0

摘要

背景:乳腺癌在全球的高发病率和潜在的严重健康后果证明了它对公众健康的重大影响。抑制 MCF-7 细胞系中雌激素受体α(ERα)的增殖效应对乳腺癌治疗具有重要意义:目前的研究工作涉及到用于识别ERα潜在抑制剂的硅学技术:方法:该方法将基于机器学习的 QSAR 模型与分子对接相结合,以确定 ERα 的潜在结合剂。此外,分子动力学模拟研究了复合物的稳定性,ADMET 分析验证了化合物的特性:结果:两个化合物(162412 和 443440)与 ERα 有明显的结合亲和力,结合能与已确定的粘合剂 RL4 相当。其 ADMET 质量显示出与药物相似的优势特性。分子动力学模拟证实了这些配体在动态条件下与 ERα 活性区的稳定结合。RMSD 图和构象稳定性支持配体持续占据蛋白质的结合位点。模拟后发现,162412 和 443440 的蛋白质配体复合物中有两个氢键,结合自由能分别为 -27.32 kcal/mol 和 -25.00 kcal/mol:研究表明,162412 和 443440 化合物可用于开发创新型抗 ERα 药物。然而,还需要更多的研究来证明这两种化合物对乳腺癌的治疗效果。这将有助于开发ERα相关乳腺癌的新疗法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Repurposing Phytochemicals against Breast Cancer (MCF-7) using Classical Structure-Based Drug Design.

Background: The significant public health effect of breast cancer is demonstrated by its high global prevalence and the potential for severe health consequences. The suppression of the proliferative effects facilitated by the estrogen receptor alpha (ERα) in the MCF-7 cell line is significant for breast cancer therapy.

Objective: The current work involves in-silico techniques for identifying potential inhibitors of ERα.

Methods: The method combines QSAR models based on machine learning with molecular docking to identify potential binders for the ERα. Further, molecular dynamics simulation studied the stability of the complexes, and ADMET analysis validated the compound's properties.

Result: Two compounds (162412 and 443440) showed significant binding affinities with ERα, with binding energies comparable to the established binder RL4. The ADMET qualities showed advantageous characteristics resembling pharmaceutical drugs. The stable binding of these ligands in the active region of ERα during dynamic conditions was confirmed by molecular dynamics simulations. RMSD plots and conformational stability supported the ligands' persistent occupancy in the protein's binding site. After simulation, two hydrogen bonds were found within the protein-ligand complexes of 162412 and 443440, with binding free energy values of -27.32 kcal/mol and -25.00 kcal/mol.

Conclusion: The study suggests that compounds 162412 and 443440 could be useful for developing innovative anti-ERα medicines. However, more research is needed to prove the compounds' breast cancer treatment efficacy. This will help develop new treatments for ERα-associated breast cancer.

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