Literature DB >> 28622828

The index of ideality of correlation: A criterion of predictive potential of QSPR/QSAR models?

Andrey A Toropov1, Alla P Toropova2.   

Abstract

The index of ideality of correlation (IIC) is a new criterion of the predictive potential of quantitative structure-property/activity relationships (QSPRs/QSARs). This IIC is calculated with using of the correlation coefficient between experimental and calculated values of endpoint for the calibration set, with taking into account the positive and negative dispersions between experimental and calculated values. The mutagenicity is well-known important characteristic of substances from ecological point of view. Consequently, the estimation of the IIC for mutagenicity is well motivated. It is confirmed that the utilization of this criterion significantly improves the predictive potential of QSAR models of mutagenicity. The new criterion can be used for other endpoints.
Copyright © 2017 Elsevier B.V. All rights reserved.

Keywords:  CORAL software; Index of ideality of correlation; Mutagenicity; Predictive potential; QSAR; Salmonella typhimurium

Mesh:

Substances:

Year:  2017        PMID: 28622828     DOI: 10.1016/j.mrgentox.2017.05.008

Source DB:  PubMed          Journal:  Mutat Res        ISSN: 0027-5107            Impact factor:   2.433


  3 in total

1.  Use of the index of ideality of correlation to improve models of eco-toxicity.

Authors:  Alla P Toropova; Andrey A Toropov
Journal:  Environ Sci Pollut Res Int       Date:  2018-09-25       Impact factor: 4.223

2.  A regression-based QSAR-model to predict acute toxicity of aromatic chemicals in tadpoles of the Japanese brown frog (Rana japonica): Calibration, validation, and future developments to support risk assessment of chemicals in amphibians.

Authors:  Andrey A Toropov; Matteo R Di Nicola; Alla P Toropova; Alessandra Roncaglioni; Edoardo Carnesecchi; Nynke I Kramer; Antony J Williams; Manuel E Ortiz-Santaliestra; Emilio Benfenati; Jean-Lou C M Dorne
Journal:  Sci Total Environ       Date:  2022-03-25       Impact factor: 10.753

3.  Setting the stage for next-generation risk assessment with non-animal approaches: the EU-ToxRisk project experience.

Authors:  M J Moné; G Pallocca; S E Escher; T Exner; M Herzler; S Hougaard Bennekou; H Kamp; E D Kroese; Marcel Leist; T Steger-Hartmann; B van de Water
Journal:  Arch Toxicol       Date:  2020-09-04       Impact factor: 5.153

  3 in total

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