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使用GOLD改进蛋白质-配体对接

Improved protein-ligand docking using GOLD.

作者信息

Verdonk Marcel L, Cole Jason C, Hartshorn Michael J, Murray Christopher W, Taylor Richard D

机构信息

Astex Technology, Ltd., Cambridge, United Kingdom.

出版信息

Proteins. 2003 Sep 1;52(4):609-23. doi: 10.1002/prot.10465.

Abstract

The Chemscore function was implemented as a scoring function for the protein-ligand docking program GOLD, and its performance compared to the original Goldscore function and two consensus docking protocols, "Goldscore-CS" and "Chemscore-GS," in terms of docking accuracy, prediction of binding affinities, and speed. In the "Goldscore-CS" protocol, dockings produced with the Goldscore function are scored and ranked with the Chemscore function; in the "Chemscore-GS" protocol, dockings produced with the Chemscore function are scored and ranked with the Goldscore function. Comparisons were made for a "clean" set of 224 protein-ligand complexes, and for two subsets of this set, one for which the ligands are "drug-like," the other for which they are "fragment-like." For "drug-like" and "fragment-like" ligands, the docking accuracies obtained with Chemscore and Goldscore functions are similar. For larger ligands, Goldscore gives superior results. Docking with the Chemscore function is up to three times faster than docking with the Goldscore function. Both combined docking protocols give significant improvements in docking accuracy over the use of the Goldscore or Chemscore function alone. "Goldscore-CS" gives success rates of up to 81% (top-ranked GOLD solution within 2.0 A of the experimental binding mode) for the "clean list," but at the cost of long search times. For most virtual screening applications, "Chemscore-GS" seems optimal; search settings that give docking speeds of around 0.25-1.3 min/compound have success rates of about 78% for "drug-like" compounds and 85% for "fragment-like" compounds. In terms of producing binding energy estimates, the Goldscore function appears to perform better than the Chemscore function and the two consensus protocols, particularly for faster search settings. Even at docking speeds of around 1-2 min/compound, the Goldscore function predicts binding energies with a standard deviation of approximately 10.5 kJ/mol.

摘要

Chemscore函数被用作蛋白质-配体对接程序GOLD的评分函数,并在对接准确性、结合亲和力预测和速度方面,将其性能与原始的Goldscore函数以及两种一致性对接协议“Goldscore-CS”和“Chemscore-GS”进行了比较。在“Goldscore-CS”协议中,用Goldscore函数生成的对接结果用Chemscore函数进行评分和排序;在“Chemscore-GS”协议中,用Chemscore函数生成的对接结果用Goldscore函数进行评分和排序。对一组224个蛋白质-配体复合物的“纯净”数据集进行了比较,并对该数据集的两个子集进行了比较,一个子集中的配体是“类药物”的,另一个子集中的配体是“类片段”的。对于“类药物”和“类片段”配体,Chemscore函数和Goldscore函数获得的对接准确性相似。对于较大的配体,Goldscore函数给出了更好的结果。使用Chemscore函数进行对接的速度比使用Goldscore函数快三倍。与单独使用Goldscore函数或Chemscore函数相比,两种组合对接协议在对接准确性方面都有显著提高。对于“纯净列表”,“Goldscore-CS”的成功率高达81%(实验结合模式2.0 Å范围内排名第一的GOLD解决方案),但代价是搜索时间长。对于大多数虚拟筛选应用,“Chemscore-GS”似乎是最佳选择;对于“类药物”化合物,对接速度约为0.25 - 1.3分钟/化合物的搜索设置成功率约为78%,对于“类片段”化合物成功率约为85%。在生成结合能估计方面,Goldscore函数似乎比Chemscore函数和两种一致性协议表现更好,特别是对于更快的搜索设置。即使对接速度约为1 - 2分钟/化合物,Goldscore函数预测结合能的标准偏差约为10.5 kJ/mol。

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