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Discovery of CDK8/CycC Ligands with a New Virtual Screening Tool.
ChemMedChem ( IF 3.4 ) Pub Date : 2018-12-10 , DOI: 10.1002/cmdc.201800559
Wei Chen 1, 2, 3 , Xiaodong Ren 1 , Chia-En A Chang 1
Affiliation  

Selective inhibition of cyclin-dependent kinase 8 and cyclin C (CDK8/CycC) has been suggested as a promising strategy for decreasing mitogenic signals in cancer cells with reduced toxicity toward normal cells. We developed a novel virtual screening protocol for drug development and applied it to the discovery of new CDK8/CycC type II ligands, which is likely to achieve long residence time and specificity. We first analyzed the binding thermodynamics of 11 published pyrazolourea ligands using molecular dynamics simulations and a free-energy calculation method, VM2, and extracted the key binding information to assist virtual screening. The urea moiety was found to be the critical structural contributor of the reference ligands. Starting with the urea moiety, we conducted substructure-based searches with our newly developed superposition and single-point energy evaluation method, followed by free-energy calculations, and singled out three purchasable compounds for bioassay testing. The ranking from the experimental results is completely consistent with the predicted rankings. A potent drug-like compound was found to have a Kd value of 42.5 nm, which is similar to those of the most potent reference ligands; this provided a good starting point for further improvement. This study shows that our novel virtual screening protocol is an accurate and efficient tool for drug development.

中文翻译:

使用新的虚拟筛选工具发现CDK8 / CycC配体。

已经提出对细胞周期蛋白依赖性激酶8和细胞周期蛋白C(CDK8 / CycC)的选择性抑制是减少癌细胞中有丝分裂信号并降低对正常细胞毒性的有前途的策略。我们开发了一种用于药物开发的新型虚拟筛选方案,并将其应用于发现新的CDK8 / CycC II型配体,这很可能会获得较长的停留时间和特异性。我们首先使用分子动力学模拟和自由能计算方法VM2分析了11种已发布的吡唑并脲配体的结合热力学,并提取了关键的结合信息以辅助虚拟筛选。发现脲部分是参考配体的关键结构贡献者。从尿素部分开始 我们使用新开发的叠加和单点能量评估方法进行了基于子结构的搜索,然后进行自由能计算,并挑选出了三种可购买的化合物进行生物测定测试。实验结果的排名与预测排名完全一致。发现一种有效的类药物化合物的Kd值为42.5 nm,与最有效的参考配体相似。这为进一步改进提供了良好的起点。这项研究表明,我们新颖的虚拟筛选方案是一种准确有效的药物开发工具。实验结果的排名与预测排名完全一致。发现一种有效的类药物化合物的Kd值为42.5 nm,与最有效的参考配体相似。这为进一步改进提供了良好的起点。这项研究表明,我们新颖的虚拟筛选方案是一种准确有效的药物开发工具。实验结果的排名与预测排名完全一致。发现一种有效的类药物化合物的Kd值为42.5 nm,与最有效的参考配体相似。这为进一步改进提供了良好的起点。这项研究表明,我们新颖的虚拟筛选方案是一种准确有效的药物开发工具。
更新日期:2018-12-10
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