Coral: QSAR models for acute toxicity in fathead minnow (Pimephales promelas)
โ Scribed by A. P. Toropova; A. A. Toropov; A. Lombardo; A. Roncaglioni; E. Benfenati; G. Gini
- Publisher
- John Wiley and Sons
- Year
- 2012
- Tongue
- English
- Weight
- 988 KB
- Volume
- 33
- Category
- Article
- ISSN
- 0192-8651
No coin nor oath required. For personal study only.
โฆ Synopsis
Abstract
CORrelation And Logic (CORAL) is a software that generates quantitative structure activity relationships (QSAR) for different endpoints. This study is dedicated to the QSAR analysis of acute toxicity in Fathead minnow (Pimephales promelas). Statistical quality for the external test set is a complex function of the split (into training and test subsets), the number of epochs of the Monte Carlo optimization, and the threshold that is a criterion for dividing the correlation weights into two classes rare (blocked) and not rare (active). Computational experiments with three random splits (data on 568 compounds) indicated that this approach can satisfactorily predict the desired endpoint (the negative decimal logarithm of the 50% lethal concentration, in mmol/L, pLC~50~). The average correlation coefficients (r^2^) are 0.675 ยฑ 0.0053, 0.824 ยฑ 0.0242, 0.787 ยฑ 0.0101 for subtraining, calibration, and test set, respectively. The average standard errors of estimation (s) are 0.837 ยฑ 0.021, 0.555 ยฑ 0.047, 0.606 ยฑ 0.049 for subtraining, calibration, and test set, respectively. The CORAL software together with three random splits into subtraining, calibration, and test sets can be downloaded on the Internet (http://www.insilico.eu/coral/). ยฉ 2012 Wiley Periodicals, Inc.
๐ SIMILAR VOLUMES
In the field of aquatic toxicology, quantitative structure-activity relationships (QSARs) have developed as scientifically credible models for predicting the toxicity of chemicals when little or no empirical data are available. In recent years, there has been an evolution of QSAR development and app