Cargando…

Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity

The knowledge-based Toxtree expert system (SAR approach) was integrated with the statistically based counter propagation artificial neural network (CP ANN) model (QSAR approach) to contribute to a better mechanistic understanding of a carcinogenicity model for non-congeneric chemicals using Dragon d...

Descripción completa

Detalles Bibliográficos
Autores principales: Fjodorova, Natalja, Novič, Marjana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology (RNCSB) Organization 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3962111/
https://www.ncbi.nlm.nih.gov/pubmed/24688639
http://dx.doi.org/10.5936/csbj.201207003
_version_ 1782308384351977472
author Fjodorova, Natalja
Novič, Marjana
author_facet Fjodorova, Natalja
Novič, Marjana
author_sort Fjodorova, Natalja
collection PubMed
description The knowledge-based Toxtree expert system (SAR approach) was integrated with the statistically based counter propagation artificial neural network (CP ANN) model (QSAR approach) to contribute to a better mechanistic understanding of a carcinogenicity model for non-congeneric chemicals using Dragon descriptors and carcinogenic potency for rats as a response. The transparency of the CP ANN algorithm was demonstrated using intrinsic mapping technique specifically Kohonen maps. Chemical structures were represented by Dragon descriptors that express the structural and electronic features of molecules such as their shape and electronic surrounding related to reactivity of molecules. It was illustrated how the descriptors are correlated with particular structural alerts (SAs) for carcinogenicity with recognized mechanistic link to carcinogenic activity. Moreover, the Kohonen mapping technique enables one to examine the separation of carcinogens and non-carcinogens (for rats) within a family of chemicals with a particular SA for carcinogenicity. The mechanistic interpretation of models is important for the evaluation of safety of chemicals.
format Online
Article
Text
id pubmed-3962111
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher Research Network of Computational and Structural Biotechnology (RNCSB) Organization
record_format MEDLINE/PubMed
spelling pubmed-39621112014-03-31 Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity Fjodorova, Natalja Novič, Marjana Comput Struct Biotechnol J Research Article The knowledge-based Toxtree expert system (SAR approach) was integrated with the statistically based counter propagation artificial neural network (CP ANN) model (QSAR approach) to contribute to a better mechanistic understanding of a carcinogenicity model for non-congeneric chemicals using Dragon descriptors and carcinogenic potency for rats as a response. The transparency of the CP ANN algorithm was demonstrated using intrinsic mapping technique specifically Kohonen maps. Chemical structures were represented by Dragon descriptors that express the structural and electronic features of molecules such as their shape and electronic surrounding related to reactivity of molecules. It was illustrated how the descriptors are correlated with particular structural alerts (SAs) for carcinogenicity with recognized mechanistic link to carcinogenic activity. Moreover, the Kohonen mapping technique enables one to examine the separation of carcinogens and non-carcinogens (for rats) within a family of chemicals with a particular SA for carcinogenicity. The mechanistic interpretation of models is important for the evaluation of safety of chemicals. Research Network of Computational and Structural Biotechnology (RNCSB) Organization 2012-07-01 /pmc/articles/PMC3962111/ /pubmed/24688639 http://dx.doi.org/10.5936/csbj.201207003 Text en © Fjodorova and Novič. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited.
spellingShingle Research Article
Fjodorova, Natalja
Novič, Marjana
Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity
title Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity
title_full Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity
title_fullStr Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity
title_full_unstemmed Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity
title_short Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity
title_sort integration of qsar and sar methods for the mechanistic interpretation of predictive models for carcinogenicity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3962111/
https://www.ncbi.nlm.nih.gov/pubmed/24688639
http://dx.doi.org/10.5936/csbj.201207003
work_keys_str_mv AT fjodorovanatalja integrationofqsarandsarmethodsforthemechanisticinterpretationofpredictivemodelsforcarcinogenicity
AT novicmarjana integrationofqsarandsarmethodsforthemechanisticinterpretationofpredictivemodelsforcarcinogenicity