Carcinogenicity prediction of noncongeneric chemicals by augmented top priority fragment classification
Articolo
Data di Pubblicazione:
2016
Citazione:
Carcinogenicity prediction of noncongeneric chemicals by augmented top priority fragment classification / M. Casalegno, G. Sello. - In: COMPUTATIONAL BIOLOGY AND CHEMISTRY. - ISSN 1476-9271. - 61:(2016 Apr), pp. 145-154. [10.1016/j.compbiolchem.2016.01.011]
Abstract:
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.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
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
Elenco autori:
M. Casalegno, G. Sello
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