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Professor at Chemistry
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Identified potent anti-tumor agents through the inhibition of C-Met receptor tyrosine kinase using QSAR, molecular docking, and ADMET in silico studies of novel 4,5,6,7-tetrahydrobenzo[D]-thiazol-2-Yl derivatives derived from dimedone.
Discovered potent inhibitors of NEK7 protein using a comprehensive computational approach, offering potential therapeutic avenues.
Developed new anti-Alzheimer drug candidates through combined computational approaches, including 3D-QSAR, molecular docking, and molecular dynamics studies of liquiritigenin derivatives.
Identified potential inhibitors against SARS-CoV-2 main protease using combined molecular docking and dynamics simulations studies of natural compounds.
Designed novel benzimidazole derivatives as potential α-amylase inhibitors using QSAR, pharmacokinetics, molecular docking, and molecular dynamics simulation studies.
Identified potential inhibitors from vitamins and their derivatives compounds against SARS-CoV-2 main protease using molecular docking, molecular dynamic simulation and ADMET profiling.
Developed potent avian influenza virus H5N1 inhibitors using QSAR study of N-substituted oseltamivir derivatives with quantum chemical descriptors and statistical methods.
Identified potential anti-Human African Trypanosomiasis activity for 2-phenylimidazopyridines derivatives using DFT and Lipinski's descriptors.
Samir Chtita is a leading expert in computational chemistry and drug design, focusing on the discovery of novel therapeutic agents through advanced in silico techniques and QSAR/QSPR modeling. His research significantly contributes to the development of new treatments for diseases like cancer, Alzheimer's, and viral infections.
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