University of Insubria

University of Insubria

The Insubria University is an University, founded in 1998, in Northen Italy (Lombardia Region). With four academic schools (Economics, Law, Medicine, and Sciences) the University of Insubria offers over fifty different courses of study at the undergraduate, as well as at the graduate and postgraduate level.

Researches in different fields are performed in eighteen Departments. The QSAR Research Unit in Environmental Chemistry and Ecotoxicology of the Department of Structural and Functional Biology of Insubria University (Varese, Italy) is headed by Prof. Dr. Paola Gramatica, full professor of Environmental Chemistry and Director of the Department. The group has a 13 years experience in the development and validation of QSAR models, based on theoretical molecular descriptors and various modelling methods (Regression and Classification).

The principal area of interest is the QSAR modelling and prediction of physico-chemical properties and biological activities of environmental pollutants (POPs and PBTs: PAHs, PCBs, pesticides; VOCs, EDCs, etc.). The group has been involved in two previous EU Projects (PREDICT and BEAM) on aquatic toxicity and mixture toxicity. More than 60 papers on QSAR modelling have been published in international journals, peer reviewed and more than 140 presentations to international meetings. Paola Gramatica is a member of the Editorial Board of Chemosphere, SAR & QSAR in Environmental Research and Open Applied Informatics Journal, and referee of many scientific journals in chemical modelling environmental field. She has worked as QSAR expert for the European Joint Research Centre (Ispra) and for OECD (Organisation for Economic Cooperation and Development) in the validation of QSAR models for regulatory acceptance.

The OECD principles for regulatory applicability of the QSAR models, particularly for predictivity and applicability domain, will be applied within CADASTER for validation of existing QSARs for the studied classes. Moreover, QSAR models of regression (MLR, particularly OLS) for quantitative responses and of classification (CART, k-NN, DA) for qualitative responses, in addition to Neural Networks (Self Organizing Maps, SOM), will be developed by applying different splitting methods for statistical external validation during the model development. The models developed in WP3, headed by Paola Gramatica, will be applied in WP4 for risk assessment and in WP5 for the dissemination tool. The used theoretical molecular descriptors (1D, 2D, 3D) will be calculated by the DRAGON software and selected by Genetic Algorithms-Variable Selection procedure. Finally, chemical similarity analysis and ranking methods will be applied by using different chemometric methods, in order to prioritize chemicals for additional experimental testing to be performed in WP2.

Scientific personnel:

Dr Ester Papa, PhD (post-doc fellowship): QSAR model developer

Selected Publication List:

1) P. Gramatica, Principles of QSAR models validation: internal and external, QSAR& Comb.Sci. 2007, 26, 694-701

2) P. Gramatica, E. Giani, E. Papa. Statistical external validation and consensus modeling: A QSPR case study for Koc prediction, J. Mol.Graph. Model., 2007, 25, 755-766.

3) P. Gramatica, E.Papa, Screening and ranking of POPs for Global Half-Life: a QSAR approach for prioritization, Environ. Sci. Technol., 2007, 4, 2833-2839.

4) E. Papa, J. Dearden, P. Gramatica Linear QSAR regression models for the prediction of bioconcentration factors by physicochemical properties and structural theoretical molecular descriptors. Chemosphere, 2007, 67, 351-358.

5) H. Liu, E. Papa, P. Gramatica QSAR Prediction of Estrogen Activity for a Large Set of Diverse Chemicals under the Guidance of OECD Principles. Chem. Res. Toxicol., 2006, 19, 1540-1548.

6) T.I. Netzeva, A.P. Worth, T. Aldenberg, R. Benigni, M. T.D.Cronin, P.Gramatica, J. S. Jaworska, S.Kahn, G. Klopman, C. A. Marchant, G. Myatt, N. Nikolova-Jeliazkova, Current Status of Methods for Defining the Applicability Domain of (Quantitative) Structure–Activity Relationships, ATLA, 2005, 33, 155–173.

7) E.Papa, F.Villa, P.Gramatica, Statistically validated QSARs and theoretical descriptors for the modelling of the aquatic toxicity of organic chemicals in Pimephales promelas (Fathead Minnow) J.Chem.Inf.Model., 2005, 45,1256-1266.

8) E.Papa, F.Battaini and P.Gramatica. Ranking of Esters’ Aquatic Toxicity modelled by QSAR. Chemosphere 2005, 58/5, 559-570.

9) A. Tropsha, P. Gramatica, V.K. Gombar, The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models QSAR &Comb. Sci., 2003, 22, 69-77.

10) L. Eriksson, J. Jaworska, A. Worth, M. Cronin, R.M. McDowell, P. Gramatica. Methods for reliability, uncertainty assessment, and applicability evaluations of regression based and classification QSARs. Environ. Health Perspect., 2003, 111, 1361-1375.