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当归贝母苦参丸治疗前列腺癌的潜在药物靶点预测:基于网络药理学的虚拟筛选研究。

Herb-target virtual screening and network pharmacology for prediction of molecular mechanism of Danggui Beimu Kushen Wan for prostate cancer.

机构信息

Discipline of Chinese Medicine, School of Health and Biomedical Sciences, RMIT University, PO Box 71, Bundoora, VIC, 3083, Australia.

School of Science, RMIT University, Melbourne, VIC, 3000, Australia.

出版信息

Sci Rep. 2021 Mar 23;11(1):6656. doi: 10.1038/s41598-021-86141-1.

Abstract

Prostate cancer (PCa) is a cancer that occurs in the prostate with high morbidity and mortality. Danggui Beimu Kushen Wan (DBKW) is a classic formula for patients with difficult urination including PCa. This study aimed to investigate the molecular mechanisms of DBKW for PCa. We obtained DBKW compounds from our previous reviews. We identified potential targets for PCa from literature search, currently approved drugs and Open Targets database and filtered them by protein-protein interaction network analysis. We selected 26 targets to predict three cancer-related pathways. A total of 621 compounds were screened via molecular docking using PyRx and AutoDock Vina against 21 targets for PCa, producing 13041 docking results. The binding patterns and positions showed that a relatively small number of tight-binding compounds from DBKW were predicted to interact strongly and selectively with three targets. The top five high-binding-affinity compounds were selected to generate a network, indicating that compounds from all three herbs had high binding affinity against the 21 targets and may have potential biological activities with the targets. DBKW contains multi-targeting agents that could act on more than one pathway of PCa simultaneously. Further studies could focus on validating the computational results via experimental studies.

摘要

前列腺癌(PCa)是一种发生在前列腺的癌症,具有较高的发病率和死亡率。当归贝母苦参丸(DBKW)是一种治疗包括 PCa 在内的排尿困难患者的经典方剂。本研究旨在探讨 DBKW 治疗 PCa 的分子机制。我们从之前的综述中获得了 DBKW 化合物。我们从文献检索、目前批准的药物和 Open Targets 数据库中筛选出针对 PCa 的潜在靶点,并通过蛋白质-蛋白质相互作用网络分析对其进行筛选。我们选择了 26 个靶点来预测三种与癌症相关的途径。我们使用 PyRx 和 AutoDock Vina 对 21 个 PCa 靶点进行了分子对接,共筛选出 621 种化合物,得到 13041 个对接结果。结合模式和位置表明,DBKW 中的少数紧密结合化合物被预测与三个靶点具有强烈和选择性的相互作用。选择前五个高结合亲和力的化合物生成网络,表明来自三种草药的化合物对 21 个靶点均具有较高的结合亲和力,可能与这些靶点具有潜在的生物学活性。DBKW 含有多种靶向药物,可同时作用于 PCa 的多个途径。进一步的研究可以集中在通过实验研究验证计算结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4903/7988104/7256efe0039c/41598_2021_86141_Fig1_HTML.jpg

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