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Researcher at Research Department
Ask questions about Rahul D. Jawarkar's research, publications, and ongoing work
Utilized QSAR modeling, molecular docking, and molecular dynamics simulations to identify a novel hit as a SARS CoV-2 3CLpro inhibitor, contributing to potential COVID-19 treatment.
Employed QSAR, molecular docking, MD simulation, and MMGBSA calculations to identify key pharmacophoric features for optimizing ALK tyrosine kinase inhibitors as potential anticancer drugs.
Examined the influence of tautomerism on the outcomes of QSAR modeling, providing insights into the accuracy of predictive models in drug design.
Synthesized novel quinolinyl Schiff bases and azetidinones and evaluated their potential as enoyl ACP-reductase inhibitors, contributing to antibacterial drug development.
Explored the potential of repurposing food molecules as BACE1 inhibitors, offering a novel approach to Alzheimer's disease treatment.
Utilized QSAR and CoMFA analyses to optimize the antimalarial activity of synthetic prodiginines, contributing to the development of new antimalarial drugs.
Used QSAR based virtual screening, molecular docking, MD simulation and MMGBSA approaches to identify potent aldose reductase inhibitors as antidiabetic agents.
Dr. Rahul D. Jawarkar is a leading researcher in computational drug discovery, specializing in the application of QSAR, molecular docking, and molecular dynamics simulations for identifying and optimizing drug candidates for various diseases, including cancer, HIV/AIDS, and malaria.
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