Similarity searching in databases of flexible 3D structures using autocorrelation vectors derived from smoothed bounded distance matrices.
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 hit-list and so may be a useful adjunct to other similarity searching methods.
Department of Information Studies, The University of Sheffield, Regent Court, 211 Portobello Street, Sheffield, South Yorkshire, S1 4DP, United Kingdom.
Nicholas
N
Rhodes
David E
DE
Clark
Peter
P
Willett
D003205:Computing Methodologies; D019992:Databases as Topic; D004791:Enzyme Inhibitors / Q000737:chemistry / Q000145:classification; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D015394:Molecular Structure; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D013329:Structure-Activity Relationship
D004791:Enzyme Inhibitors; D004364:Pharmaceutical Preparations