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Researcher at Research Department
Ask questions about Assia Belhassan's research, publications, and ongoing work
Developed a computational approach to identify potential inhibitors against the SARS-CoV-2 main protease using molecular docking and virtual screening of approved antiviral drugs.
Utilized QSAR methods to study the structure-activity relationship of antiviral compounds, providing insights into their inhibitory potential against influenza viruses.
Employed 3D-QSAR, drug-likeness studies, ADMET prediction, and molecular docking to design novel pyrazole derivatives as potential anti-cancer agents.
Conducted a QSAR study to evaluate the anti-Human African Trypanosomiasis activity of 2-phenylimidazopyridines derivatives using DFT and Lipinski's descriptors.
Performed molecular docking and molecular dynamics simulations to study the interactions of potential SARS-CoV-2 inhibitors, including Crocin, Digitoxigenin, Beta-Eudesmol and Favipiravir.
Conducted QSAR, ADMET, molecular docking, and molecular dynamics studies of novel bicyclo (aryl methyl) benzamides as potent GlyT1 inhibitors for the treatment of Schizophrenia.
Compared the antioxidant power of eugenol to Vitamin C using computational methods.
Assia Belhassan is a researcher specializing in computational drug discovery and in silico approaches to identify potential drug candidates, particularly for viral infections and cancer. Her work focuses on QSAR modeling, molecular docking, and molecular dynamics simulations to understand drug-target interactions and predict drug properties.
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