PMID- 17226934
OWN - NLM
STAT- MEDLINE
DCOM- 20070320
LR  - 20220311
IS  - 0893-228X (Print)
IS  - 1520-5010 (Electronic)
IS  - 0893-228X (Linking)
VI  - 20
IP  - 1
DP  - 2007 Jan
TI  - 4D-fingerprint categorical QSAR models for skin sensitization based on the 
      classification of local lymph node assay measures.
PG  - 114-28
AB  - Currently, the only validated methods to identify skin sensitization effects are 
      in vivo models, such as the local lymph node assay (LLNA) and guinea pig studies. 
      There is a tremendous need, in particular due to novel legislation, to develop 
      animal alternatives, for eaxample, quantitative structure-activity relationship 
      (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been 
      constructed. The descriptors used to generate these models are derived from the 
      4D-molecular similarity paradigm and are referred to as universal 
      4D-fingerprints. A training set of 132 structurally diverse compounds and a test 
      set of 15 structurally diverse compounds were used in this study. The statistical 
      methodologies used to build the models are logistic regression (LR) and partial 
      least-square coupled logistic regression (PLS-LR), which prove to be effective 
      tools for studying skin sensitization measures expressed in the two categorical 
      terms of sensitizer and non-sensitizer. QSAR models with low values of the 
      Hosmer-Lemeshow goodness-of-fit statistic, X(2)HL, are significant and 
      predictive. For the training set, the cross-validated prediction accuracy of the 
      logistic regression models ranges from 77.3% to 78.0%, whereas that of the 
      PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the 
      prediction accuracy of logistic regression models ranges from 80.0% to 86.7%, 
      whereas that of the PLS-logistic regression models ranges from 73.3% to 80.0%. 
      The QSAR models are made up of 4D-fingerprints related to aromatic atoms, 
      hydrogen bond acceptors, and negatively partially charged atoms.
FAU - Li, Yi
AU  - Li Y
AD  - Laboratory of Molecular Modeling and Design (MC 781), College of Pharmacy, 
      University of Illinois at Chicago, 833 South Wood Street, Chicago, Illinois 
      60612-7231, USA.
FAU - Tseng, Yufeng J
AU  - Tseng YJ
FAU - Pan, Dahua
AU  - Pan D
FAU - Liu, Jianzhong
AU  - Liu J
FAU - Kern, Petra S
AU  - Kern PS
FAU - Gerberick, G Frank
AU  - Gerberick GF
FAU - Hopfinger, Anton J
AU  - Hopfinger AJ
LA  - eng
GR  - 1 R21 GM075775-01/GM/NIGMS NIH HHS/United States
GR  - R21 GM075775/GM/NIGMS NIH HHS/United States
GR  - R21 GM075775-02/GM/NIGMS NIH HHS/United States
GR  - R21 GM075775-03/GM/NIGMS NIH HHS/United States
GR  - R21 GM075775-01/GM/NIGMS NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - Chem Res Toxicol
JT  - Chemical research in toxicology
JID - 8807448
SB  - IM
MH  - Animals
MH  - Guinea Pigs
MH  - Least-Squares Analysis
MH  - Logistic Models
MH  - Lymph Nodes/*drug effects
MH  - Quantitative Structure-Activity Relationship
MH  - Skin/*drug effects
MH  - *Toxicity Tests
PMC - PMC2553001
MID - NIHMS63276
EDAT- 2007/01/18 09:00
MHDA- 2007/03/21 09:00
PMCR- 2008/09/24
CRDT- 2007/01/18 09:00
PHST- 2007/01/18 09:00 [pubmed]
PHST- 2007/03/21 09:00 [medline]
PHST- 2007/01/18 09:00 [entrez]
PHST- 2008/09/24 00:00 [pmc-release]
AID - 10.1021/tx6002535 [doi]
PST - ppublish
SO  - Chem Res Toxicol. 2007 Jan;20(1):114-28. doi: 10.1021/tx6002535.