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基于结合位点氢键网络的框架选择进行MM/GBSA评分的性能:蛋白激酶实例

Performance of the MM/GBSA scoring using a binding site hydrogen bond network-based frame selection: the protein kinase case.

作者信息

Adasme-Carreño Francisco, Muñoz-Gutierrez Camila, Caballero Julio, Alzate-Morales Jans H

机构信息

Centro de Bioinformática y Simulación Molecular (CBSM), Escuela de Ingeniería en Bioinformática, Facultad de Ingeniería, Universidad de Talca, 2 Norte 685, Casilla 721, Talca, Chile.

出版信息

Phys Chem Chem Phys. 2014 Jul 21;16(27):14047-58. doi: 10.1039/c4cp01378f. Epub 2014 Jun 5.

Abstract

A conformational selection method, based on hydrogen bond (Hbond) network analysis, has been designed in order to rationalize the configurations sampled using molecular dynamics (MD), which are commonly used in the estimation of the relative binding free energy of ligands to macromolecules through the MM/GBSA or MM/PBSA method. This approach makes use of protein-ligand complexes obtained from X-ray crystallographic data, as well as from molecular docking calculations. The combination of several computational approaches, like long MD simulations on protein-ligand complexes, Hbond network-based selection by scripting techniques and finally MM/GBSA, provides better statistical correlations against experimental binding data than previous similar reported studies. This approach has been successfully applied in the ranking of several protein kinase inhibitors (CDK2, Aurora A and p38), which present both diverse and related chemical structures.

摘要

一种基于氢键(Hbond)网络分析的构象选择方法已被设计出来,以便使通过分子动力学(MD)采样得到的构型合理化。分子动力学常用于通过MM/GBSA或MM/PBSA方法估计配体与大分子的相对结合自由能。这种方法利用了从X射线晶体学数据以及分子对接计算中获得的蛋白质-配体复合物。几种计算方法的结合,如对蛋白质-配体复合物进行长时间的分子动力学模拟、通过脚本技术进行基于氢键网络的选择以及最终的MM/GBSA,与之前报道的类似研究相比,能提供与实验结合数据更好的统计相关性。这种方法已成功应用于几种蛋白激酶抑制剂(CDK2、Aurora A和p38)的排序,这些抑制剂具有多样且相关的化学结构。

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