My primary focus is the investigation of the safety and activity of natural products by computational methods. I also utilize artificial intelligence and machine learning to streamline data mining of big data involving natural products.
Research Interests
My research interests include molecular docking (ligand-receptor and protein-protein), molecular dynamics, quantitative structure-activity relationships, ADMET prediction, artificial intelligence, and machine learning.
Biography
Michael Neal received his Ph.D. in pharmaceutical sciences from the University of Mississippi in 2024. Currently, he investigates the safety and efficacy relationships of natural products through computational techniques, including molecular docking, molecular dynamics, and QSAR. He also computationally probes the pharmacology of GPCRs (such as cannabinoid receptor 1 and mu opioid receptor) as they relate to modulation by Cannabis constituents.
Education
Ph.D. Pharmaceutical Science, The University of Mississippi (2024)