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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology (RNCSB) Organization
2012
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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 |
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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 |