2D-Discrete Fourier Transform: generalization of the MIA-QSAR strategy in molecular modeling

Abstract

Adequate alignment of chemical structure images with respect to the basic scaffold in a series of chemical compounds constitutes an indispensable requirement for constructing multivariate images (MVIs) and subsequent molecular modeling using the Multivariate Image Analysis applied to Quantitative Structure–Activity Relationship (MIA-QSAR) approach. However, up to the moment, this alignment procedure has been manually performed, based on subjective ocular precision. The 2D-Discrete Fourier Transform (2D-DFT) is introduced as a strategy for creating a common base to construct MVIs for chemical structures using their magnitude spectra. The utility of magnitude spectra in QSAR studies has been evaluated through models for the antimalarial, anticancer and trichomonicidal activity of a series of 2, 5-diaminobenzophenone, 4-phenylpyrrolocarbazole and benzimidazole derivatives, respectively, yielding satisfactory results comparable to superior to those reported in the literature. It is anticipated that this strategy should enable the application of the MIA-QSAR approach to structurally diverse datasets other than a series of congeneric datasets.