REPOSITORY QDB RESOURCES NEWS CONTACTS

Gramatica, P.; Papa, E. Screening and Ranking of POPs for Global Half-Life: QSAR Approaches for Prioritization Based on Molecular Structure. Environ. Sci. Technol. 2007, 41, 8, 2833–2839.

QsarDB Repository

Gramatica, P.; Papa, E. Screening and Ranking of POPs for Global Half-Life: QSAR Approaches for Prioritization Based on Molecular Structure. Environ. Sci. Technol. 2007, 41, 8, 2833–2839.

QDB archive DOI: 10.15152/QDB.113   DOWNLOAD

QsarDB content

Property GHLI: Global half-life index

Compounds: 250 | Models: 1 | Predictions: 2

1: General validated correlation (2007)

Regression model (regression)

Open in:QDB Explorer QDB Predictor

Name Type n

R2

σ

Training set training 125 0.831 0.747
Validation set external validation 125 0.793 0.785

Citing

When using this data, please cite the original article and this QDB archive:

Metadata

Show full item record

Title: Gramatica, P.; Papa, E. Screening and Ranking of POPs for Global Half-Life: QSAR Approaches for Prioritization Based on Molecular Structure. Environ. Sci. Technol. 2007, 41, 8, 2833–2839.
Abstract: Persistence in the environment is an important criterion in prioritizing hazardous chemicals and in identifying new persistent organic pollutants (POPs). Degradation half-life in various compartments is among the more commonly used criteria for studying environmental persistence, but the limited availability of experimental data or reliable estimates is a serious problem. Available half-life data for degradation in air, water, sediment, and soil, for a set of 250 organic POP-type chemicals, were combined in a multivariate approach by principal component analysis to obtain a ranking of the studied organic pollutants according to their relative overall half-life. A global half-life index (GHLI) applicable for POP screening purposes is proposed. The reliability of this index was verified in comparison with multimedia model results. This global index was then modeled as a cumulative end-point using a QSAR approach based on few theoretical molecular descriptors, and a simple and robust regression model externally validated for its predictive ability was derived. The application of this model could allow a fast preliminary identification and prioritization of not yet known POPs, just from the knowledge of their molecular structure. This model can be applied a priori also in the chemical design of safer and alternative non-POP compounds.
URI: http://hdl.handle.net/10967/113
http://dx.doi.org/10.15152/QDB.113
Date: 2014-04-07


Files in this item

Name Description Format Size View
2007EST2833.qdb.zip Validated multilinear model application/x-zip 182.1Kb View/Open
Q7-17-11-112_qmrf_jrc.pdf QMRF PDF 80.61Kb View/Open
Files associated with this item are distributed
under Creative Commons license.

This item appears in the following Collection(s)

Show full item record