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蛋白质-配体相对和整体分子运动结合熵的计算。

Calculations of protein-ligand binding entropy of relative and overall molecular motions.

作者信息

Ruvinsky Anatoly M

机构信息

Center for Bioinformatics, The University of Kansas, 2030 Becker Drive, Lawrence, KS 66047, USA.

出版信息

J Comput Aided Mol Des. 2007 Jul;21(7):361-70. doi: 10.1007/s10822-007-9116-0. Epub 2007 May 15.

Abstract

In the context of virtual database screening, calculations of protein-ligand binding entropy of relative and overall molecular motions are challenging, owing to the inherent structural complexity of the ligand binding well in the energy landscape of protein-ligand interactions and computing time limitations. We describe a fast statistical thermodynamic method for estimation the binding entropy to address the challenges. The method is based on the integration of the configurational integral over clusters obtained from multiple docked positions. We apply the method in conjunction with 11 popular scoring functions (AutoDock, ChemScore, DrugScore, D-Score, F-Score, G-Score, LigScore, LUDI, PLP, PMF, X-Score) to evaluate the binding entropy of 100 protein-ligand complexes. The averaged values of binding entropy contribution vary from 6.2 to 9.1 kcal/mol, showing good agreement with literature. We calculate positional sizes and the angular volume of the native ligand wells. The averaged geometric mean of positional sizes in principal directions varies from 0.8 to 1.4 A. The calculated range of angular volumes is 3.3-11.8 rad(2). Then we demonstrate that the averaged six-dimensional volume of the native well is larger than the volume of the most populated non-native well in energy landscapes described by all of 11 scoring functions.

摘要

在虚拟数据库筛选的背景下,由于蛋白质-配体相互作用能量景观中配体结合口袋固有的结构复杂性以及计算时间限制,计算相对和整体分子运动的蛋白质-配体结合熵具有挑战性。我们描述了一种快速统计热力学方法来估计结合熵以应对这些挑战。该方法基于对从多个对接位置获得的簇的构型积分进行积分。我们将该方法与11种常用评分函数(AutoDock、ChemScore、DrugScore、D-Score、F-Score、G-Score、LigScore、LUDI、PLP、PMF、X-Score)结合使用,以评估100个蛋白质-配体复合物的结合熵。结合熵贡献的平均值在6.2至9.1千卡/摩尔之间变化,与文献显示出良好的一致性。我们计算了天然配体口袋的位置大小和角体积。主要方向上位置大小的平均几何平均值在0.8至1.4埃之间变化。计算出的角体积范围为3.3 - 11.8弧度²。然后我们证明,在由所有11种评分函数描述的能量景观中,天然口袋的平均六维体积大于最密集的非天然口袋的体积。

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