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Domain of EPI suite biotransformation models.

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TLDR
The present work was undertaken to characterize the AD of EPI Suite™ biotransformation models and evaluate the performance of selected AD assessment methods, and found structure-based and descriptor-based AD methods were not useful in identifying misclassified chemicals.
Abstract
Knowledge of the interpolative region or applicability domain (AD) of structure–activity relationships is believed to improve predictive accuracy. The present work was undertaken to characterize the AD of EPI Suite™ biotransformation models and evaluate the performance of selected AD assessment methods. AD methods were applied to the training sets of four models representing different end-points, and the predictive accuracy was then evaluated using six independent validation sets. Two of the models estimated a continuous variable (log half-life) from fragment descriptors. For biotransformation in fish (BCFBAF™) and hydrocarbon biodegradation (BioHCwin), the approach using ranges, with preprocessing by analysis of principal components, worked reasonably well in identifying subsets of validation chemicals that have higher root mean squared error than for all validation chemicals. AD methods were also applied to two classification models, Biowin3 (which predicts the time required to achieve complete aerobic ...

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Citations
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Classification of cytochrome P450 inhibitors and noninhibitors using combined classifiers.

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Prediction of the fate of organic compounds in the environment from their molecular properties: a review.

TL;DR: A comprehensive review of quantitative structure-activity relationships (QSAR) allowing the prediction of the fate of organic compounds in the environment from their molecular properties was done, and the combination of descriptors belonging to different categories led to improve QSAR performances.
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Modeling and predicting aquatic aerobic biodegradation – a review from a user's perspective

TL;DR: Some fundamental problems in modeling biodegradation are discussed, as well as more general issues in modeling of compound properties by quantitative structure–property/activity relationships (QSPR/Activity relationships).
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Trends in predictive biodegradation for sustainable mitigation of environmental pollutants: Recent progress and future outlook

TL;DR: The feasibility of in-silico techniques, together with the computational framework, has been applied to predictive bioremediation aiming to clean-up contaminants, toxicity evaluation, and possibilities for the degradation of complex recalcitrant compounds as discussed by the authors.
References
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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

Atom/fragment contribution method for estimating octanol-water partition coefficients

TL;DR: Atom/fragment contribution values, used to estimate the log octanol-water partition coefficient (log P) of organic compounds, have been determined for 130 simple chemical substructures by a multiple linear regression of 1120 compounds with measured log P values.
Journal ArticleDOI

QSAR Applicability Domain Estimation by Projection of the Training Set in Descriptor Space: A Review:

TL;DR: Methods and criteria for estimating AD through training set interpolation in descriptor space and response space are reviewed and it is proposed that response space should be included in the training set representation.
Journal ArticleDOI

Approaches to Measure Chemical Similarity ± a Review

TL;DR: The review provides analysis of potential pitfalls of descriptor based similarity analysis – loss of information in the representations of molecular structures – the relevance of a particular representation and chosen similarity measure to the activity.
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