Literature DB >> 23710908

QSAR prediction of the competitive interaction of emerging halogenated pollutants with human transthyretin.

E Papa1, S Kovarich, P Gramatica.   

Abstract

The determination of the potential endocrine disruption (ED) activity of chemicals such as poly/perfluorinated compounds (PFCs) and brominated flame retardants (BFRs) is still hindered by a limited availability of experimental data. Quantitative structure-activity relationship (QSAR) strategies can be applied to fill this data gap, help in the characterization of the ED potential, and screen PFCs and BFRs with a hazardous toxicological profile. This paper proposes the modelling of T4-TTR (thyroxin-transthyretin) competing potency and relative binding potency toward T4 (logT4-REP) of PFCs and BFRs by regression and classification QSAR models. This study is a follow up of a former work, which analysed separately the interaction of BFRs and PFCs with the carrier TTR. The new results demonstrate the possibility of developing robust and predictive QSARs, which include both BFRs and PFCs in the training set, obtaining larger applicability domains than the existing models developed separately for BFRs and PFCs. The selection of modelling molecular descriptors confirms the importance of structural features, such as the aromatic OH or the molecular length, to increase the binding of the studied chemicals to TTR. Additionally, the need of experimental tests for some chemicals, and in particular for some of the BFRs, is highlighted.

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Year:  2013        PMID: 23710908     DOI: 10.1080/1062936X.2013.773374

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  4 in total

1.  Predictive models for identifying the binding activity of structurally diverse chemicals to human pregnane X receptor.

Authors:  Cen Yin; Xianhai Yang; Mengbi Wei; Huihui Liu
Journal:  Environ Sci Pollut Res Int       Date:  2017-07-12       Impact factor: 4.223

2.  MOA-based linear and nonlinear QSAR models for predicting the toxicity of organic chemicals to Vibrio fischeri.

Authors:  Shengnan Zhang; Ning Wang; Limin Su; Xiaoyan Xu; Chao Li; Weichao Qin; Yuanhui Zhao
Journal:  Environ Sci Pollut Res Int       Date:  2020-01-08       Impact factor: 4.223

3.  Update of the risk assessment of hexabromocyclododecanes (HBCDDs) in food.

Authors:  Dieter Schrenk; Margherita Bignami; Laurent Bodin; James Kevin Chipman; Jesús Del Mazo; Bettina Grasl-Kraupp; Christer Hogstrand; Laurentius Ron Hoogenboom; Jean-Charles Leblanc; Carlo Stefano Nebbia; Elsa Nielsen; Evangelia Ntzani; Annette Petersen; Salomon Sand; Tanja Schwerdtle; Heather Wallace; Diane Benford; Peter Fürst; Martin Rose; Sofia Ioannidou; Marina Nikolič; Luisa Ramos Bordajandi; Christiane Vleminckx
Journal:  EFSA J       Date:  2021-03-08

Review 4.  In silico models for predicting vector control chemicals targeting Aedes aegypti.

Authors:  J Devillers; C Lagneau; A Lattes; J C Garrigues; M M Clémenté; A Yébakima
Journal:  SAR QSAR Environ Res       Date:  2014-10-02       Impact factor: 3.000

  4 in total

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