Similarity Searching in Databases of Flexible 3D Structures Using Autocorrelation Vectors Derived from Smoothed Bounded Distance Matrices

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.