Literature DB >> 17477948

Quantitative structure carcinogenicity relationship for detecting structural alerts in nitroso-compounds.

Aliuska Morales Helguera1, Maykel Pérez González, Maria Natália D S Cordeiro, Miguel Angel Cabrera Pérez.   

Abstract

Prevention of environmentally induced cancers is a major health problem of which solutions depend on the rapid and accurate screening of potential chemical hazards. Lately, theoretical approaches such as the one proposed here - Quantitative Structure-Activity Relationship (QSAR) - are increasingly used for assessing the risks of environmental chemicals, since they can markedly reduce costs, avoid animal testing, and speed up policy decisions. This paper reports a QSAR study based on the Topological Substructural Molecular Design (TOPS-MODE) approach, aiming at predicting the rodent carcinogenicity of a set of nitroso-compounds selected from the Carcinogenic Potency Data Base (CPDB). The set comprises nitrosoureas (14 chemicals), N-nitrosamines (18 chemicals) C-nitroso-compounds (1 chemical), nitrosourethane (1 chemical) and nitrosoguanidine (1 chemical), which have been bioassayed in male rat using gavage as the route of administration. Here we are especially concerned in gathering the role of both parameters on the carcinogenic activity of this family of compounds. First, the regression model was derived, upon removal of one identified nitrosamine outlier, and was able to account for more than 84% of the variance in the experimental activity. Second, the TOPS-MODE approach afforded the bond contributions -- expressed as fragment contributions to the carcinogenic activity -- that can be interpreted and provide tools for better understanding the mechanisms of carcinogenesis. Finally, and most importantly, we demonstrate the potentialities of this approach towards the recognition of structural alerts for carcinogenicity predictions.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 17477948     DOI: 10.1016/j.taap.2007.02.021

Source DB:  PubMed          Journal:  Toxicol Appl Pharmacol        ISSN: 0041-008X            Impact factor:   4.219


  4 in total

1.  In silico design of multi-target inhibitors for C-C chemokine receptors using substructural descriptors.

Authors:  Alejandro Speck-Planche; Valeria V Kleandrova
Journal:  Mol Divers       Date:  2011-10-22       Impact factor: 2.943

2.  QSAR modelling of carcinogenicity by balance of correlations.

Authors:  A A Toropov; A P Toropova; E Benfenati; A Manganaro
Journal:  Mol Divers       Date:  2009-02-04       Impact factor: 2.943

3.  QSAR model toward the rational design of new agrochemical fungicides with a defined resistance risk using substructural descriptors.

Authors:  Alejandro Speck-Planche; Valeria V Kleandrova; Julio A Rojas-Vargas
Journal:  Mol Divers       Date:  2011-06-02       Impact factor: 2.943

4.  Correlation between physicochemical properties of modified clinoptilolite and its performance in the removal of ammonia-nitrogen.

Authors:  Yingbo Dong; Hai Lin; Yinhai He
Journal:  Environ Monit Assess       Date:  2017-02-16       Impact factor: 2.513

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.