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  4. Categorical QSAR models for skin sensitization based upon local lymph node assay classification measures Part 2: 4D-Fingerprint three-State and Two-2-State logistic regression models
 
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Categorical QSAR models for skin sensitization based upon local lymph node assay classification measures Part 2: 4D-Fingerprint three-State and Two-2-State logistic regression models

Journal
Toxicological Sciences
Journal Volume
99
Journal Issue
2
Pages
532-544
Date Issued
2007
Author(s)
Li Y
Pan D
Liu J
Kern P.S
Gerberick G.F
Hopfinger A.J
YUFENG JANE TSENG  
DOI
10.1093/toxsci/kfm185
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-38449115068&doi=10.1093%2ftoxsci%2fkfm185&partnerID=40&md5=f3e509f2828043e63def7a77cfc8c87b
https://scholars.lib.ntu.edu.tw/handle/123456789/632251
Abstract
Three and four state categorical quantitative structure-activity relationship (QSAR) models for skin sensitization have been constructed using data from the murine Local Lymph Node Assay studies. These are the same data we previously used to build two-state (sensitizer, nonsensitizer) QSAR models (Li et al., 2007, Chem. Res. Toxicol. 20, 114-128). 4D-fingerprint descriptors derived from the 4D-molecular similarity paradigm are used to generate these models. A training set of 196 and a test set of 22 structurally diverse compounds were used in this study. Logistic regression, and partial least square coupled logistic regression were used to build the models. The three-state QSAR model gives a classification accuracy of 73.4% for the training set and 63.6% for the test set, while the random average value of classification accuracy for any three-state data set is 33.3%. The two-2-state [four categories in total] QSAR model gives a classification accuracy of 83.2% for the training set and 54.6% for the test set, while the random average value of classification accuracy for any two-2-state data set is 25%. An analysis of the skin-sensitization models developed in this study, as well as the two-state QSAR models developed in our previous analysis, suggests that the "moderate" sensitizers may be the main source of limited model accuracy. © The Author 2007. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved.
Subjects
4D-fingerprints; Categorical models; QSAR, logistic regression; Skin sensitization
Other Subjects
1 (para methoxyphenyl) 1 penten 3 one; 1 iodononane; 1 iodooctadecane; 1 iodotetradecane; 1 naphthol; 1 phenyl 1,2 propanedione; 1 phenyl 2 methylbutane 1,3 dione; 1,2 benzisothiazolin 3 one; 1,2,4 benzenetricarboxylic anhydride (trimellitic anhydride); 12 bromo decanol; 12 bromododecanoic acid; 2 acetylcyclohexanenone; 2 amino 6 chloro 4 nitrophenol; 2 aminophenol; 2 bromo 2 bromomethylglutaronitrile; 2 bromotetradecanoic acid; 2 ethylbutaldehyde; 2 hydroxyethylacrylate; 2 hydroxypropylmethacrylate; 2 mercaptobenzothiazole; 2 methyl 4 isothiazolin 3 one; 2 methyl 5 hydroxyethylaminophenol; 2 nitro 1,4 phenylenediamine; 2,2,6,6 tetramethylheptane 3,5 dione; 2,3 butanedione; butanol; chemical compound; creosol; methylnitronitrosoguanidine; accuracy; animal model; article; classification algorithm; controlled study; data extraction; finger dermatoglyphics; local lymph node assay; logistic regression analysis; molecular dynamics; molecular systematics; mouse; nonhuman; quantitative structure property relation; skin sensitization; statistical model; toxicity testing; animal; drug effect; guinea pig; lymph node; quantitative structure activity relation; skin; toxicity testing; Murinae; Animals; Guinea Pigs; Logistic Models; Lymph Nodes; Quantitative Structure-Activity Relationship; Skin; Toxicity Tests
Type
journal article

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