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基于药效团模型构建、类药性分析、分子对接和分子动力学模拟的新型 CK2 抑制剂的发现。

Pharmacophore development, drug-likeness analysis, molecular docking, and molecular dynamics simulations for identification of new CK2 inhibitors.

机构信息

Department of Chemistry, Faculty of Sciences, University of Mouloud Maamri, Tizi Ouzou, Algeria.

Laboratory of Theoretical Physico-Chemistry and Computer Chemistry, Faculty of Chemistry, University of Science and Technology Houari Boumédiène, Algiers, Algeria.

出版信息

J Mol Model. 2020 May 29;26(6):160. doi: 10.1007/s00894-020-04408-2.

DOI:10.1007/s00894-020-04408-2
PMID:32472293
Abstract

Protein kinase 2 (CK2), an essential serine/threonine casein kinase, is considered an interesting target for cancer treatments. Different molecular modeling approaches such as pharmacophore modeling, molecular docking, and molecular dynamics simulations have been used to develop new CK2 inhibitors. This study presents a pharmacophore model that was generated by combining and merging the structure-based and ligand-based pharmacophore features and validated using receiver operating characteristic (ROC). Based on validation results revealing good predictive ability, this pharmacophore model was used as a three-dimensional query in a virtual screening simulation. Several compounds with different chemical scaffolds were retrieved as hits, which were further analyzed and refined using several molecular property filters. The obtained compounds were then filtered and compared to the crystallographic ligand on the basis of their predicted docking energies, binding mode, and interactions with CK2 active site residues. This step resulted in a compound with a high pharmacophore fit value and better docking energy. Molecular dynamics simulation indicated stable binding of the predicted compound to CK2 protein, characterized by root mean square deviation (RMSD) and root mean square fluctuation (RMSF) and hydrogen bond. Graphical abstract.

摘要

蛋白激酶 2(CK2)是一种必需的丝氨酸/苏氨酸蛋白激酶,被认为是癌症治疗的一个有趣靶点。已经使用了不同的分子建模方法,如药效团建模、分子对接和分子动力学模拟,来开发新的 CK2 抑制剂。本研究提出了一种药效团模型,该模型通过组合和合并基于结构和基于配体的药效团特征生成,并使用接收者操作特征(ROC)进行验证。基于验证结果显示出良好的预测能力,该药效团模型被用作虚拟筛选模拟中的三维查询。检索到了具有不同化学支架的几种化合物作为命中物,然后使用几种分子性质过滤器对其进行进一步分析和优化。获得的化合物然后根据其预测的对接能、结合模式以及与 CK2 活性位点残基的相互作用进行过滤和比较。这一步得到了一个具有高药效团拟合值和更好对接能的化合物。分子动力学模拟表明,预测化合物与 CK2 蛋白的结合稳定,其特征是均方根偏差(RMSD)和均方根波动(RMSF)和氢键。

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