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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
QSAR: dead or alive?
1Bristol-Myers Squibb, Research and Development, CADD Group, P.O. Box 4000, Princeton, NJ 08543, USA. arthur.doweyko@bms.com
Abstract:
This perspective concerns the methods employed within the current drug discovery community to develop predictive quantitative structure-activity relationships (QSAR). Specifically, a number of cautions are provided which may circumvent misuse and misunderstanding of the technique. Ignorance of such caveats has led to a discouraging tendency of the methods to result in poorly predictive models. Among these pitfalls are the fondness with which we associate correlation with causation, the mesmerizing influence of large numbers of molecular descriptors, the incessant misuse of the leave-one-out paradigm, and finally, the QSAR enigma wherein model predictivity is not a necessary component of a model's usefulness.
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