Abstract

2D QSAR Study of Imidazothiazole-Propenones Derivatives as Potential Anticancer Agents by DFT-QSAR Models

Author(s): Lafridi Hind, Hanane Zaki, Hsaine Zgou, Mohammed Bouachrine

A series of Imidazo-propenones were evaluated for their cytotoxic effects against human cancer cell lines A549 (lung adenocarcinoma epithelial cell line). Quantitative Structure-Activity Relationship (QSAR) has been investigated in a series of 23 imidazothiazole-prop-2-en-1-one derivatives to correlate the activities and structures, using DFT and 2D-QSAR. The compounds were obtained by molecular descriptors encoding a small part of the whole chemical information of the molecule. The principal component analysis PCA; linear (Multiple linear regressions (MLR)); nonlinear (artificial neural network); and the regression partial least squares (PLS) models were used to relate the structural features to their reported activities. The ANN model was tested by leave-one-out-cross-validation reliably and unbiasedly estimates prediction errors, also to assess the significance of the model and to predict biological activities of other novel compounds. In this work, the results obtained indicate that our proposed models constituted of relevant descriptors. It is worth noting that such combination of several calculated parameters for the drugs structures obtained could be useful for the development of newer chemotherapeutic agents.

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