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由于数据集准备导致的对接成功率的变化。

Variability in docking success rates due to dataset preparation.

机构信息

Chemical Computing Group, Suite 910, 1010 Sherbrooke Street West, Montreal, QC, H3A 2R7, Canada.

出版信息

J Comput Aided Mol Des. 2012 Jun;26(6):775-86. doi: 10.1007/s10822-012-9570-1. Epub 2012 May 8.

Abstract

The results of cognate docking with the prepared Astex dataset provided by the organizers of the "Docking and Scoring: A Review of Docking Programs" session at the 241st ACS national meeting are presented. The MOE software with the newly developed GBVI/WSA dG scoring function is used throughout the study. For 80 % of the Astex targets, the MOE docker produces a top-scoring pose within 2 Å of the X-ray structure. For 91 % of the targets a pose within 2 Å of the X-ray structure is produced in the top 30 poses. Docking failures, defined as cases where the top scoring pose is greater than 2 Å from the experimental structure, are shown to be largely due to the absence of bound waters in the source dataset, highlighting the need to include these and other crucial information in future standardized sets. Docking success is shown to depend heavily on data preparation. A "dataset preparation" error of 0.5 kcal/mol is shown to cause fluctuations of over 20 % in docking success rates.

摘要

呈现了与主办方提供的已准备好的 Astex 数据集进行同源对接的结果,该数据集是在第 241 届 ACS 全国会议上的“对接和评分:对接程序综述”会议上准备的。在整个研究中使用了新开发的 GBVI/WSA dG 评分功能的 MOE 软件。对于 80%的 Astex 目标,MOE docker 在距离 X 射线结构 2 Å 内生成了得分最高的构象。对于 91%的目标,在 top 30 个构象中生成了距离 X 射线结构 2 Å 内的构象。对接失败(定义为得分最高的构象距离实验结构大于 2 Å)主要是由于源数据集缺少结合水,这突出表明需要在未来的标准化集中包含这些和其他关键信息。对接成功率很大程度上取决于数据准备。结果表明,“数据集准备”错误 0.5 kcal/mol 会导致对接成功率波动超过 20%。

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