QSAR model as a random event: A case of rat toxicity

Alla P Toropova; Andrey A Toropov; Emilio Benfenati; Danuta Leszczynska; Jerzy Leszczynski

doi:10.1016/j.bmc.2015.01.055

QSAR model as a random event: A case of rat toxicity

Bioorg Med Chem. 2015 Mar 15;23(6):1223-30. doi: 10.1016/j.bmc.2015.01.055. Epub 2015 Feb 7.

Authors

Alla P Toropova¹, Andrey A Toropov², Emilio Benfenati¹, Danuta Leszczynska³, Jerzy Leszczynski⁴

Affiliations

¹ IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, 20156, Via La Masa 19, Milano, Italy.
² IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, 20156, Via La Masa 19, Milano, Italy. Electronic address: andrey.toropov@marionegri.it.
³ Interdisciplinary Nanotoxicity Center, Department of Civil and Environmental Engineering, Jackson State University, 1325 Lynch St, Jackson, MS 39217-0510, USA.
⁴ Interdisciplinary Nanotoxicity Center, Department of Chemistry and Biochemistry, Jackson State University, 1400 J.R. Lynch Street, PO Box 17910, Jackson, MS 39217, USA.

PMID: 25703247
DOI: 10.1016/j.bmc.2015.01.055

Abstract

Quantitative structure-property/activity relationships (QSPRs/QSARs) can be used to predict physicochemical and/or biochemical behavior of substances which were not studied experimentally. Typically predicted values for chemicals in the training set are accurate since they were used to build the model. QSPR/QSAR models must be validated before they are used in practice. Unfortunately, the majority of the suggested approaches of the validation of QSPR/QSAR models are based on consideration of geometrical features of clusters of data points in the plot of experimental versus calculated values of an endpoint. We believe these geometrical criteria can be more useful if they are analyzed for several splits into the training and test sets. In this way, one can estimate the reproducibility of the model with various splits and better evaluate model reliability. The probability of the correct prediction of an endpoint for external validation set (in the series of the above-mentioned splits) can provide an useful way to evaluate the domain of applicability of the model.

Keywords: CORAL software; Domain of applicability; Oral rat toxicity; QSAR; Validation.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Lethal Dose 50
Models, Molecular
Organic Chemicals / chemistry
Organic Chemicals / toxicity*
Quantitative Structure-Activity Relationship*
Rats
Reproducibility of Results
Software

Substances

Organic Chemicals