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配体分子对接方法:属性加权向量的对准。

Ligand aligning method for molecular docking: alignment of property-weighted vectors.

机构信息

Department of Biotechnology, Yonsei University, Seoul 120-749, Republic of Korea.

出版信息

J Chem Inf Model. 2012 Apr 23;52(4):984-95. doi: 10.1021/ci200501p. Epub 2012 Apr 13.

Abstract

To reduce searching effort in conformational space of ligand docking positions, we propose an algorithm that generates initial binding positions of the ligand in a target protein, based on the property-weighted vector (P-weiV), the three-dimensional orthogonal vector determined by the molecular property of hydration-free energy density. The alignment of individual P-weiVs calculated separately for the ligand and the protein gives the initial orientation of a given ligand conformation relative to an active site; these initial orientations are then ranked by simple energy functions, including solvation. Because we are using three-dimensional orthogonal vectors to be aligned, only four orientations of ligand positions are possible for each ligand conformation, which reduces the search space dramatically. We found that the performance of P-weiV compared favorably to the use of principle moment of inertia (PMI) as implemented in LigandFit when we tested the abilities of the two approaches to correctly predict 205 protein-ligand complex data sets from the PDBBind database. P-weiV correctly predicted the alignment of ligands (within rmsd of 2.5 Å) with 57.6% reliability (118/205) for the top 10 ranked conformations and with 74.1% reliability (152/205) for the top 50 ranked conformations of Catalyst-generated conformers, as compared to 22.9% (47/205) and 31.2% (64/205), respectively, in the case of PMI with the same conformer set.

摘要

为了减少配体对接位置构象空间搜索的工作量,我们提出了一种算法,该算法基于无水化自由能密度分子特性确定的三维正交向量(P-weiV),生成配体在靶蛋白中的初始结合位置。为配体和蛋白质分别计算的单个 P-weiV 的对齐给出了给定配体构象相对于活性位点的初始取向;然后通过简单的能量函数(包括溶剂化)对这些初始取向进行排序。由于我们使用三维正交向量进行对齐,因此每个配体构象的配体位置只有四个可能的方向,这大大减少了搜索空间。当我们测试这两种方法正确预测 PDBBind 数据库中 205 个蛋白质-配体复合物数据集的能力时,我们发现 P-weiV 的性能优于 LigandFit 中实施的惯性矩主分量(PMI)的使用。P-weiV 正确预测了配体的对齐(在 2.5Å 的 RMSD 内),对于排名前 10 的构象,可靠性为 57.6%(118/205),对于排名前 50 的 Catalyst 生成构象的构象,可靠性为 74.1%(152/205),而 PMI 的可靠性分别为 22.9%(47/205)和 31.2%(64/205)。

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