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基于结构的虚拟筛选昆虫蜕皮激素受体配体的 MM/PBSA 方法。

Structure-based virtual screening for insect ecdysone receptor ligands using MM/PBSA.

机构信息

Division of Applied Life Sciences, Graduate School of Agriculture, Kyoto University, Kyoto 606-8502, Japan.

Division of Applied Life Sciences, Graduate School of Agriculture, Kyoto University, Kyoto 606-8502, Japan.

出版信息

Bioorg Med Chem. 2019 Mar 15;27(6):1065-1075. doi: 10.1016/j.bmc.2019.02.011. Epub 2019 Feb 5.

Abstract

The ecdysone receptor (EcR) is an insect nuclear receptor that is activated by the molting hormone, 20-hydroxyecdysone. Because synthetic EcR ligands disrupt the normal growth of insects, they are attractive candidates for new insecticides. In this study, the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method was used to predict the binding activity of EcR ligands. Validity analyses using 40 known EcR ligands showed that the binding activity was satisfactorily predicted when the ligand conformational free energy term was introduced. Subsequently, this MM/PBSA method was applied to structure-based hierarchical virtual screening, and 12 candidate compounds were selected from a database of 3.8 million compounds. Five of these compounds were active in a cell-based competitive binding assay. The most potent compound is a simple proline derivative with low micromolar binding activity, representing a valuable lead compound for further structural optimization.

摘要

蜕皮激素受体 (EcR) 是一种昆虫核受体,可被蜕皮激素 20-羟基蜕皮激素激活。由于合成的 EcR 配体破坏了昆虫的正常生长,因此它们成为新型杀虫剂的有吸引力的候选物。在这项研究中,使用分子力学/泊松-玻尔兹曼表面积 (MM/PBSA) 方法来预测 EcR 配体的结合活性。使用 40 种已知的 EcR 配体进行的有效性分析表明,当引入配体构象自由能项时,可令人满意地预测结合活性。随后,将这种 MM/PBSA 方法应用于基于结构的层次虚拟筛选,从 380 万种化合物的数据库中选择了 12 种候选化合物。其中 5 种化合物在基于细胞的竞争性结合测定中具有活性。最有效的化合物是一种简单的脯氨酸衍生物,具有低微摩尔的结合活性,代表了进一步结构优化的有价值的先导化合物。

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