Publications by authors named "Abdelali Idrissi Taourati"
Article Synopsis
- - Research focused on evaluating forty unsymmetrical aromatic disulfide derivatives as potential inhibitors of the SARS Coronavirus (SARS-CoV-1) using density functional theory (DFT) calculations for quantum chemical descriptors and various software for topological and thermodynamic analysis.
- - The study utilized a quantitative structure-activity relationship (QSAR) approach, creating robust statistical models to predict the compounds' inhibitory activity based on their structural characteristics, with the best model showing high predictive accuracy.
- - Key findings revealed that the compounds' effectiveness against the SARS-CoV main protease is influenced by specific molecular descriptors, leading to the suggestion that smaller electron-withdrawing groups could enhance inhibitory activity; new promising compound designs were proposed based on these insights.
The quantitative structure-activity relationship (QSAR) of sixty 2-phenylimidazopyridines derivatives with anti-Human African Trypanosomiasis (anti-HAT) activity has been studied by using the density functional theory (DFT) and statistical methods. Becke's three-parameter hybrid method and the Lee-Yang-Parr B3LYP functional employing 6-31G(d) basis set are used to calculate quantum chemical descriptors using Gaussian 03W software, and the five Lipinski's parameters were calculated using ChemOffice software. In order to obtain robust and reliable QSAR model, the original dataset was randomly divided into training and prediction sets comprising 48 and 12 compounds, respectively.
View Article and Find Full Text PDF