Predicting allergic contact dermatitis: a hierarchical structure-activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors.
J Comput Aided Mol Des
; 22(6-7): 339-43, 2008.
Article
en En
| MEDLINE
| ID: mdl-18338224
ABSTRACT
A hierarchical classification study was carried out based on a set of 70 chemicals-35 which produce allergic contact dermatitis (ACD) and 35 which do not. This approach was implemented using a regular ridge regression computer code, followed by conversion of regression output to binary data values. The hierarchical descriptor classes used in the modeling include topostructural (TS), topochemical (TC), and quantum chemical (QC), all of which are based solely on chemical structure. The concordance, sensitivity, and specificity are reported. The model based on the TC descriptors was found to be the best, while the TS model was extremely poor.
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Teoría Cuántica
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
J Comput Aided Mol Des
Asunto de la revista:
BIOLOGIA MOLECULAR
/
ENGENHARIA BIOMEDICA
Año:
2008
Tipo del documento:
Article
País de afiliación:
Estados Unidos