Carcinogenicity prediction is an important process that can be performed to cut down experimental costs and save animal lives. The current reliability of the results is however disputed. Here, a blind exercise in carcinogenicity category assessment is performed using augmented top priority fragment classification. The procedure analyses the applicability domain of the dataset, allocates in clusters the compounds using a leading molecular fragment, and a similarity measure. The exercise is applied to three compound datasets derived from the Lois Gold Carcinogenic Database. The results, showing good agreement with experimental data, are compared with published ones. A final discussion on our viewpoint on the possibilities that the carcinogenicity modelling of chemical compounds offers is presented.
|Titolo:||Carcinogenicity prediction of noncongeneric chemicals by augmented top priority fragment classification|
SELLO, GUIDO GIOVANNI (Ultimo) (Corresponding)
|Parole Chiave:||carcinogen classes; carcinogenicity prediction; functional groups; molecular fragments; structural alerts; structure-activity relationships; carcinogenicity tests; carcinogens; structure-activity relationship; structural biology; biochemistry; organic chemistry; computational mathematics|
|Settore Scientifico Disciplinare:||Settore CHIM/06 - Chimica Organica|
|Data di pubblicazione:||apr-2016|
|Digital Object Identifier (DOI):||10.1016/j.compbiolchem.2016.01.011|
|Appare nelle tipologie:||01 - Articolo su periodico|