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Chemometric Methods and Theoretical Molecular Descriptors in Predictive QSAR Modeling of the Environmental Behavior of Organic Pollutants

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Recent Advances in QSAR Studies

Part of the book series: Challenges and Advances in Computational Chemistry and Physics ((COCH,volume 8))

Abstract

This chapter surveys the QSAR modeling approaches (developed by the author’s research group) for the validated prediction of environmental properties of organic pollutants. Various chemometric methods, based on different theoretical molecular descriptors, have been applied: explorative techniques (such as PCA for ranking, SOM for similarity analysis), modeling approaches by multiple-linear regression (MLR, in particular OLS), and classification methods (mainly k-NN, CART, CP-ANN). The focus of this review is on the main topics of environmental chemistry and ecotoxicology, related to the physico-chemical properties, the reactivity, and biological activity of chemicals of high environmental concern. Thus, the review deals with atmospheric degradation reactions of VOCs by tropospheric oxidants, persistence and long-range transport of POPs, sorption behavior of pesticides (Koc and leaching), bioconcentration, toxicity (acute aquatic toxicity, mutagenicity of PAHs, estrogen binding activity for endocrine disruptors compounds (EDCs)), and finally persistent bioaccumulative and toxic (PBT) behavior for the screening and prioritization of organic pollutants. Common to all the proposed models is the attention paid to model validation for predictive ability (not only internal, but also external for chemicals not participating in the model development) and checking of the chemical domain of applicability. Adherence to such a policy, requested also by the OECD principles, ensures the production of reliable predicted data, useful also in the new European regulation of chemicals, REACH.

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Notes

  1. 1.

    The symbol refers to the same property as log P (namely to the n-octanol/water partition coefficient). However, in many environmental studies this partition coefficient is abbreviated by “log Kow” to be consistent with the other environmentally relevant coefficients, e.g., n-octanol/air partition coefficient (Koa), air/water partition coefficient (Kaw).

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Acknowledgement

Many thanks to my collaborators who participated in the research, reviewed here, carried out over the past 15 years, particularly Ester Papa and Pamela Pilutti. Thanks are also due to Roberto Todeschini who was my teacher of chemometric QSAR.

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Authors and Affiliations

  1. QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Structural and Functional Biology, University of Insubria, Varese, Italy

    Paola Gramatica

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  1. Paola Gramatica
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Correspondence to Paola Gramatica .

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Editors and Affiliations

  1. Dept. Chemistry, University of Gdansk, ul. Jana Sobieskiego 18, Gdansk, 80-952, Poland

    Tomasz Puzyn

  2. Dept. Chemistry, Jackson State University, J. R. Lynch St. 1325, Jackson, 39217, U.S.A.

    Jerzy Leszczynski

  3. Dept. Chemistry, John Moores University, Byrom St., Liverpool, L3 3AF, United Kingdom

    Mark T. Cronin

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Gramatica, P. (2010). Chemometric Methods and Theoretical Molecular Descriptors in Predictive QSAR Modeling of the Environmental Behavior of Organic Pollutants. In: Puzyn, T., Leszczynski, J., Cronin, M. (eds) Recent Advances in QSAR Studies. Challenges and Advances in Computational Chemistry and Physics, vol 8. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9783-6_12

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