UWA School of Agriculture and Environment, University of Western Australia, 35-Stirling Highway, Perth, WA, 6009, Australia.
Breast Cancer Res Treat. 2024 Jan;203(1):29-47. doi: 10.1007/s10549-023-07107-7. Epub 2023 Sep 20.
This research focused on the identification of herbal compounds as potential anti-cancer drugs, especially for breast cancer, that involved the recognition of Notch downstream targets NOTCH proteins (1-4) specifically expressed in breast tumours as biomarkers for prognosis, along with P53 tumour antigens, that were used as comparisons to check the sensitivity of the herbal bio-compounds.
After investigating phytochemical candidates, we employed an approach for computer-aided drug design and analysis to find strong breast cancer inhibitors. The present study utilized in silico analyses and protein docking techniques to characterize and rank selected bio-compounds for their efficiency in oncogenic inhibition for use in precise carcinomic cell growth control.
Several of the identified phytocompounds found in herbs followed Lipinski's Rule of Five and could be further investigated as potential medicinal molecules. Based on the Vina score obtained after the docking process, the active compound Epigallocatechin gallate in green tea with NOTCH (1-4) and P53 proteins showed promising results for future drug repurposing. The stiffness and binding stability of green tea pharmacological complexes were further elucidated by the molecular dynamic simulations carried out for the highest scoring phytochemical ligand complex.
The target-ligand complex of green tea active compound Epigallocatechin gallate with NOTCH (1-4) had the potential to become potent anti-breast cancer therapeutic candidates following further research involving wet-lab experiments.
本研究专注于鉴定草药化合物作为潜在的抗癌药物,特别是针对乳腺癌,涉及识别 Notch 下游靶标 NOTCH 蛋白(1-4),这些蛋白特异性表达在乳腺癌肿瘤中,作为预后的生物标志物,同时还使用了 P53 肿瘤抗原作为对照,以检查草药生物化合物的敏感性。
在研究植物化学候选物之后,我们采用了计算机辅助药物设计和分析的方法来寻找针对乳腺癌的强抑制剂。本研究利用计算机模拟分析和蛋白质对接技术,对选定的生物化合物进行特征描述和排序,以评估它们在致癌抑制方面的效率,从而用于精确的致癌细胞生长控制。
从草药中发现的几种鉴定出的植物化合物符合 Lipinski 规则五,可以进一步研究作为潜在的药用分子。根据对接过程后获得的 Vina 得分,绿茶中的活性化合物表没食子儿茶素没食子酸酯与 NOTCH(1-4)和 P53 蛋白的结合显示出有希望的结果,可用于未来的药物再利用。通过对得分最高的植物化学配体复合物进行分子动力学模拟,进一步阐明了绿茶药理复合物的刚性和结合稳定性。
绿茶活性化合物表没食子儿茶素没食子酸酯与 NOTCH(1-4)的靶标-配体复合物具有成为潜在的抗乳腺癌治疗候选物的潜力,这需要进一步进行涉及湿实验室实验的研究。