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Updated: Jun 28, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Simple and highly predictive QSAR method: application to a series of
Matheus P Freitas1, José A Martins
1EMS Sigma Pharma - R&D, Rodovia SP 101 Km 08, Hortolândia SP 13186-401, Brazil.
Abstract:
A simple quantitative structure-activity relationship (QSAR) method of analysis used to predict biological activity for congeneric series of compounds is reported. This method is based on the application of bilinear or multilinear partial least squares regression to a data set, which is a binary matrix representing the substituents of a framework. It is appraised here to a series of (S)-N-[(1-ethyl-2-pyrrolidinyl)methyl]-6-methoxybenzamides, compounds with affinity towards the dopamine D(2) receptor subtype and showed high predictive ability, even when compared to a refined three-dimensional (3D) approach.
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