Formation of Mechanistic Categories and Local Models to Facilitate the Prediction of Toxicity

被引:7
作者
Cronin, Mark T. D. [1 ]
Enoch, Steven J. [1 ]
Hewitt, Mark [1 ]
Madden, Judith C. [1 ]
机构
[1] Liverpool John Moores Univ, Sch Pharm & Chem, Liverpool L3 3AF, Merseyside, England
关键词
in silico; QSAR; toxicity; chemical category; read-across; SKIN SENSITIZATION; READ-ACROSS; IN-VITRO; CHEMICALS; SELECTION; POTENCY; ALLOW;
D O I
10.14573/altex.2011.1.045
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
There is a range of in silico techniques that can be applied to predict the toxicity of chemicals. This paper discusses the use of methods to create "local" models, particularly based around category formation and read-across, to predict toxicity. Specifically, this is illustrated with regard to categories for predicting skin sensitisation and teratogenicity. These were formed using mechanistic and structural similarity techniques to group chemicals. Local QSAR models based on grouping chemicals have the advantage that they are transparent, simple and mechanistically derived. In addition, there are a number of freely available software tools to assist in their derivation. The disadvantages include that they are labour-intensive to develop and restricted to local areas of chemistry.
引用
收藏
页码:45 / 49
页数:5
相关论文
共 33 条
[1]   Strategic selection of chemicals for testing. Part I. Functionalities and performance of basic selection methods [J].
Aladjov, H. ;
Todorov, M. ;
Schmieder, P. ;
Serafimova, R. ;
Mekenyan, O. ;
Veith, G. .
SAR AND QSAR IN ENVIRONMENTAL RESEARCH, 2009, 20 (1-2) :159-183
[2]   Skin sensitization: Reaction mechanistic applicability domains for structure-activity relationships [J].
Aptula, AO ;
Patlewicz, G ;
Roberts, DW .
CHEMICAL RESEARCH IN TOXICOLOGY, 2005, 18 (09) :1420-1426
[3]   The utility of structure-activity relationship (SAR) models for prediction and covariate selection in developmental toxicity: Comparative analysis of logistic regression and decision tree models [J].
Arena, VC ;
Sussman, NB ;
Mazumdar, S ;
Yu, S ;
Macina, OT .
SAR AND QSAR IN ENVIRONMENTAL RESEARCH, 2004, 15 (01) :1-18
[4]   Skin sensitization: strategies for the assessment and management of risk [J].
Basketter, D. A. .
BRITISH JOURNAL OF DERMATOLOGY, 2008, 159 (02) :267-273
[5]   The integrated use of models for the properties and effects of chemicals by means of a structured workflow [J].
Bassan, Arianna ;
Worth, Andrew P. .
QSAR & COMBINATORIAL SCIENCE, 2008, 27 (01) :6-20
[6]  
Briggs GG., 2002, Drugs in pregnancy and lactation: a reference guide to fetal and neonatal risk, V6th
[7]   Identification of mechanisms of toxic action for skin sensitisation using a SMARTS pattern based approach [J].
Enoch, S. J. ;
Madden, J. C. ;
Cronin, M. T. D. .
SAR AND QSAR IN ENVIRONMENTAL RESEARCH, 2008, 19 (5-6) :555-578
[8]   An evaluation of global QSAR models for the prediction of the toxicity of phenols to Tetrahymena pyriformis [J].
Enoch, S. J. ;
Cronin, M. T. D. ;
Schultz, T. W. ;
Madden, J. C. .
CHEMOSPHERE, 2008, 71 (07) :1225-1232
[9]  
Enoch SJ, 2010, CHALL ADV COMPUT CHE, V8, P209, DOI 10.1007/978-1-4020-9783-6_7
[10]   Electrophilic Reaction Chemistry of Low Molecular Weight Respiratory Sensitizers [J].
Enoch, Steven J. ;
Roberts, David W. ;
Cronin, Mark T. D. .
CHEMICAL RESEARCH IN TOXICOLOGY, 2009, 22 (08) :1447-1453