Dimension related distance and its application in QSAR/QSPR model error estimation

被引：11

作者：

Xu, YJ

Gao, H

机构：

[1] Pharm Corp, Struct & Computat Chem, Creve Coeur, MO 63147 USA

[2] Pharm Corp, Struct & Computat Chem, Kalamazoo, MI 49007 USA

来源：

QSAR & COMBINATORIAL SCIENCE | 2003年 / 22卷 / 04期

关键词：

dimension related distance; QSPR; error estimation; molecular similarity; Euclidean distance;

D O I：

10.1002/qsar.200390032

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

In this paper, the concept of dimension related distance (DRD) is introduced to measure the position of a test compound in the descriptor space of training set compounds in a QSAR/QSPR model. DRD can be used to perform similarity comparison between one compound and a group of compounds. In a QSAR/QSPR model, we find that prediction error is related to the similarity between a test compound and the model training set compounds. DRD seems able to capture this similarity and make it possible to estimate prediction error range of a test compound from calculated DRD.

引用

页码：422 / 429

页数：8

共 10 条

[1]

[Anonymous], 1966, MULTIVARIATE ANAL P

[2]

[Anonymous], 2001, Matrix Analysis and Applied Linear Algebra

[3] Subcellular pharmacokinetics and its potential for library focusing [J].