Similarity searching in databases of flexible 3D structures using autocorrelation vectors derived from smoothed bounded distance matrices

被引：7

作者：

Rhodes, N

Clark, DE

Willett, P

机构：

[1] Argenta Discovery Ltd, Spire Green Ctr 8 9, Harlow CM19 5TR, Essex, England

[2] Univ Sheffield, Dept Informat Studies, Sheffield S1 4DP, S Yorkshire, England

来源：

JOURNAL OF CHEMICAL INFORMATION AND MODELING | 2006年 / 46卷 / 02期

关键词：

D O I：

10.1021/ci0503863

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

This paper presents an exploratory study of a novel method for flexible 3-D similarity searching based on autocorrelation vectors and smoothed bounded distance matrices. Although the new approach is unable to outperform an existing 2-D similarity searching in terms of enrichment factors, it is able to retrieve different compounds at a given percentage of the hitlist and so may be a useful adjunct to other similarity searching methods.

引用

收藏

页码：615 / 619

页数：5

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