Computational approaches to drug discovery for brain diseases
Research focuses on computational chemistry and biochemistry, informatics, and computer-aided drug discovery. Our lab is at the forefront of computational science and drug discovery. We use state-of-the art design methods including FEP calculations in conjunction with Monte Carlo and molecular dynamics simulations. The designed molecules are synthesized in our laboratory; we then perform enzymatic assays and protein crystallography. For cell assays, we work with collaborators in YSM and FAS, especially Karen Anderson, Yossi Schlessinger, and David Spiegel. We have discovered potent inhibitors or binding molecules for many molecular targets including HIV-1 reverse transcriptase, SARS-CoV-2, MIF, and JAK kinases. Our technology is directly applicable to targeting neurological processes and disorders. We are particularly interested in neurodegenerative diseases and cancers such as glioblastoma. The PI is also an expert on pharmacological properties including blood/brain barrier penetration; he is the author of the widely-used QikProp program for predicting ADME properties by AI and ML methods. It is expected that interactions in the Wu Tsai Institute would lead to collaborations in which we would supply molecular entities to address brain function and to develop drugs; we could also pursue AI/ML modeling of data obtained by others in the WTI.
Potent Non-covalent Inhibitors of the Main Protease of SARS-CoV-2 from Molecular Sculpting of the Drug Perampanel Guided by Free Energy Perturbation CalculationsAmerican Chemical Society (2021)
Journal of Medicinal Chemistry (2022)
American Chemical Society (2021)
Journal of Medicinal Chemistry (2018)