Konformasyonel Dinamik Yönlendirmeli Farmakofor Modelleme ile Güçlü Antikanser Ajanlarının Belirlenmesi

Nigar Çarşibaşi
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Abstract

Targeting the interaction between tumor suppressor p53 and murine double minute 2(MDM2) has been an attractive therapeutic strategy of recent cancer research. There are a few number of MDM2-targeted anticancer drug molecules undergoing clinical trials, yet none of them have been approved so far. In this study, a new approach is employed in which dynamics of MDM2 obtained by elastic network models are used as a guide in the generation of the ligand-based pharmacophore model prior to virtual screening. Hit molecules exhibiting high affinity to MDM2 were captured and tested by rigid and induced-fit molecular docking. The knowledge of the binding mechanism was used while creating the induced-fit docking criteria. Application of Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) method provided an accurate prediction of the binding free energy values. Two leading hit molecules which have shown better docking scores, binding free energy values and drug-like molecular properties were identified. These hits exhibited extra intermolecular interactions with MDM2, indicating a stable complex formation and hence would be further tested in vitro. Finally, the combined computational strategy employed in this study can be a promising tool in drug design for the discovery of potential new hits.
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用信息动力学指南药效团模型定义强效抗癌药物
靶向肿瘤抑制因子p53与小鼠双分钟2(MDM2)之间的相互作用已成为近年来癌症研究的一种有吸引力的治疗策略。有一些靶向mdm2的抗癌药物分子正在进行临床试验,但到目前为止还没有一个获得批准。在这项研究中,采用了一种新的方法,在虚拟筛选之前,利用弹性网络模型获得的MDM2动力学作为指导,生成基于配体的药效团模型。通过刚性和诱导匹配的分子对接,捕获了与MDM2有高亲和力的Hit分子并对其进行了检测。在创建诱导拟合对接标准时,使用了结合机制的知识。应用分子力学-广义出生表面积(MM-GBSA)方法对结合自由能进行了准确的预测。鉴定出两种具有较好对接分数、结合自由能值和类药物分子特性的先导撞击分子。这些撞击与MDM2表现出额外的分子间相互作用,表明稳定的复合物形成,因此将进一步在体外测试。最后,本研究中采用的组合计算策略可以成为药物设计中发现潜在新靶点的有前途的工具。
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