Wavelet Approximation of GRID Fields: Application to Quantitative Structure-Activity Relationships

被引:3
|
作者
Martin, Richard L. [1 ]
Gardiner, Eleanor [1 ]
Gillet, Valerie J. [1 ]
Munoz-Muriedas, Jordi [2 ]
Senger, Stefan [2 ]
机构
[1] Univ Sheffield, Informat Sch, Sheffield S1 4DP, S Yorkshire, England
[2] GlaxoSmithKline Res & Dev Ltd, Computat & Struct Chem, Stevenage SG1 2NY, Herts, England
基金
英国生物技术与生命科学研究理事会;
关键词
Chemoinformatics; GRID fields; Molecular similarity; Structure-activity relationships; Wavelets; IMAGE COMPRESSION; PREDICTION; BINDING; METABOLISM; INHIBITORS; MOLECULES; PROTEINS; DESIGN; SITE; TOOL;
D O I
10.1002/minf.201000066
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Molecular interaction fields such as those computed by the GRID program are widely used in applications such as virtual screening, molecular docking and 3D-QSAR modelling. They characterise molecules according to their favourable interaction sites and therefore enable predictions to be made on how molecules might interact. The fields are, however, comprised of a very large number of data points which presents difficulties for many applications. For example, there are likely to be high degrees of correlation between the variables which can lead to misleading results in 3D-QSAR. We describe the use of wavelet methods for approximating such data into a much smaller number of variables. We present a number of validation experiments, including use of the approximated GRIDs in 3D-QSAR, and demonstrate that wavelet approximation at high levels of data compression preserves the information content in GRID fields while significantly reducing computational requirements.
引用
收藏
页码:603 / 620
页数:18
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