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Promising Terpenes as Natural Antagonists of Cancer: An In-Silico Approach

机译:有希望的萜烯作为癌症的天然拮抗剂:一种硅内方法

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摘要

Overexpression of murine double minute 2 (MDM2) results in the inactivation of p53 and causes cancer which is a leading cause of death in recent era. In recent decades, much attention has been paid to discover potential inhibitors against MDM2 in order to cure cancer. Outcomes from studies proposes that the MDM2 is a hot target to screen potent antagonists. Thus, this study aims at discovering natural compounds using several computational approaches to inhibit the MDM2 and to eliminate p53-MDM2 interaction, which would result in the reactivation of p53 activity. A library of 500 terpenes was prepared and several virtual screening approaches were employed to find out the best hits which could serve as p53-MDM2 antagonists. On the basis of the designed protocol, three terpenes were selected. In the present study, for the stability and validation of selected three protein-ligand complexes 20 ns molecular dynamics simulations and principal component analyses (PCA) were performed. Results found that the selected terpenes hits (3- - -coumaroyl maslinic acid, Silvestrol and Betulonic acid) are potential inhibitors of p53–MDM2 interaction and could serve as potent antagonists.
机译:鼠双分钟2(MDM2)的过表达导致p53失活,并导致癌症,这是近代人死亡的主要原因。在最近的几十年中,人们非常关注发现潜在的MDM2抑制剂以治愈癌症。研究结果表明,MDM2是筛选有效拮抗剂的热门靶标。因此,本研究旨在使用几种计算方法来发现天然化合物,以抑制MDM2并消除p53-MDM2相互作用,这将导致p53活性的重新激活。制备了500个萜烯的文库,并采用了几种虚拟筛选方法来找出可以用作p53-MDM2拮抗剂的最佳匹配。根据设计的方案,选择了三个萜烯。在本研究中,为稳定和验证所选的三种蛋白质-配体复合物,进行了20 ns的分子动力学模拟和主成分分析(PCA)。结果发现,选定的萜烯命中物(3---香豆酰马来酸,西尔维斯托尔和Betulonic acid)是p53-MDM2相互作用的潜在抑制剂,可以作为有效的拮抗剂。

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