Journal ArticleDOI
Statistically validated QSARs, based on theoretical descriptors, for modeling aquatic toxicity of organic chemicals in Pimephales promelas (fathead minnow).
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TLDR
Different molecular descriptors in the development of new statistically validated QSAR models to predict the aquatic toxicity of chemicals classified according to their MOA and in a unique general model are compared.Abstract:
The use of Quantitative Structure-Activity Relationships in assessing the potential negative effects of chemicals plays an important role in ecotoxicology. (LC50)(96h) in Pimephales promelas (Duluth database) is widely modeled as an aquatic toxicity end-point. The object of this study was to compare different molecular descriptors in the development of new statistically validated QSAR models to predict the aquatic toxicity of chemicals classified according to their MOA and in a unique general model. The applied multiple linear regression approach (ordinary least squares) is based on theoretical molecular descriptor variety (1D, 2D, and 3D, from DRAGON package, and some calculated logP). The best combination of modeling descriptors was selected by the Genetic Algorithm-Variable Subset Selection procedure. The robustness and the predictive performance of the proposed models was verified using both internal (cross-validation by LOO, bootstrap, Y-scrambling) and external statistical validations (by splitting the original data set into training and validation sets by Kohonen-artificial neural networks (K-ANN)). The model applicability domain (AD) was checked by the leverage approach to verify prediction reliability.read more
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Journal ArticleDOI
Principles of QSAR models validation: internal and external
TL;DR: Evidence is presented that only models that have been validated externally, after their internal validation, can be considered reliable and applicable for both external prediction and regulatory purposes.
Journal ArticleDOI
How not to develop a quantitative structure–activity or structure–property relationship (QSAR/QSPR)
TL;DR: 21 types of error that continue to be perpetrated in the QSAR/QSPR literature are identified and each is discussed, with examples (including some of the authors' own).
Journal ArticleDOI
QSARINS-chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS.
TL;DR: A database of environmentally hazardous chemicals, collected and modeled by QSar by the Insubria group, is included in the updated version of QSARINS, software recently proposed for the development and validation ofQSAR models by the genetic algorithm‐ordinary least squares method.
Journal ArticleDOI
Can we estimate the accuracy of ADME-Tox predictions?
TL;DR: An analysis of octanol-water distribution coefficients is used to exemplify the consistency of estimated and calculated accuracy of the ALOGPS program (http://www.vcclab.org) to predict in-house and publicly available datasets.
Book
Molecular, Clinical and Environmental Toxicology
TL;DR: Molecular, clinical, and environmental toxicolog , Molecular, clinical and environmental Toxicolog, Clinical, andEnvironmental toxicolog, کتابخانه دیجیتال جندی اهواز