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Discrete Fourier Transform-Based Multivariate Image Analysis: Application to Modeling of Aromatase Inhibitory Activity

We recently generalized the formerly alignment-dependent multivariate image analysis applied to quantitative structure–activity relationships (MIA-QSAR) method through the application of the discrete Fourier transform (DFT), allowing for its application to noncongruent and structurally diverse chemical compound data sets. Here we report the first practical application of this method in the screening of molecular entities of therapeutic interest, with human aromatase inhibitory activity as the case study. We developed an ensemble classification model based on the two-dimensional (2D) DFT MIA-QSAR descriptors, with which we screened the NCI Diversity Set V (1593 compounds) and obtained 34 chemical compounds with possible aromatase inhibitory activity. These compounds were docked into the aromatase active site, and the 10 most promising compounds were selected for in vitro experimental validation. Of these compounds, 7419 (nonsteroidal) and 89 201 (steroidal) demonstrated satisfactory antiproliferative and a...

Authors:   Stephen J. Barigye; Matheus P. Freitas; Priscila Ausina; Patricia Zancan; Mauro Sola-Penna; Juan A. Castillo-Garit
Journal:   Journal of Combinatorial Chemistry
Year:   2018
DOI:   10.1021/acscombsci.7b00155
Publication date:   22-Jan-2018
Facts, background information, dossiers
  • image analysis
  • validation
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