Additive SMILES-based optimal descriptors in QSAR modelling bee toxicity: Using rare SMILES attributes to define the applicability domain

被引：45
作者：
Toropov, A. A. [1 ]
Benfenati, E. [2 ]
机构：
[1] Inst Geol & Geophys, Tashkent 100041, Uzbekistan
[2] Ist Ric Farmacol Mario Negri, I-20156 Milan, Italy
来源：
BIOORGANIC & MEDICINAL CHEMISTRY | 2008年 / 16卷 / 09期
关键词：
QSAR; SMILES; toxicity towards bee; applicability domain;
D O I：
10.1016/j.bmc.2008.03.048
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
The additive SMILES-based optimal descriptors have been used for modelling the bee toxicity. The influence of relative prevalence of the SMILES attributes in a training and test sets to the models for bee toxicity has been analysed. Avoiding the use of rare attributes improves statistical characteristics of the model on the external test set. The possibility of using the probability of the presence of SMILES attributes in training and test sets for rational definition of the applicability domain is discussed. (c) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码：4801 / 4809
页数：9
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