Faculty Candidate Seminar

Talk Title: “Accelerated Molecular Simulations and Drug Discovery”

Remarkable advances of supercomputing and artificial intelligence (AI) are transforming computational chemistry, biology and medicine in studies of molecules to cells. However, large gaps remain between the time scales of supercomputer simulations (typically microseconds) and those of biological processes (milliseconds or even longer). It has proven challenging to achieve sufficient sampling and compute thermodynamics and kinetics of biological systems, hindering effective drug design. I will present our efforts to address these challenges and make use of simulations for drug discovery. First, we have developed novel theoretical and computational algorithms and AI techniques. They have enabled unprecedented simulations on repetitive dissociation and binding of small molecules, peptides and proteins, thereby allowing for highly efficient and accurate calculations of their binding free energies and kinetics. These parameters are critical for therapeutic design of drugs, peptides and antibodies. Furthermore, we have combined complementary accelerated molecular simulations and cutting-edge experimental techniques to uncover functional mechanisms of important biomolecules and design novel drug molecules through successful collaborations with leading experimental groups. Our studied systems include G-protein-coupled receptors (GPCRs) that serve as primary targets of ~1/3 of currently marketed drugs, γ-secretase (a key membrane-embedded protease implicated in Alzheimer’s disease), RNA-binding proteins and RNA. Future outlooks will be provided for AI-driven drug discovery and multiscale modeling of cellular signaling pathways.

Brief Biography: Dr. Yinglong Miao is an Associate Professor in the Department of Molecular Biosciences and Center for Computational Biology at the University of Kansas. Yinglong obtained Ph.D. in Computational Chemistry in the Peter Ortoleva lab at Indiana University. He then received training in Biophysics and Pharmacology through postdoctoral studies, first with Jeremy Smith and Jerome Baudry at Oak Ridge National Laboratory/University of Tennessee, and then with Andy McCammon at the Howard Hughes Medical Institute/the University of California San Diego. Yinglong develops novel accelerated simulation methods and applies these methods in advanced simulations of biomolecules and drug discovery. His lab currently focuses on simulations and drug discovery of G-protein-coupled receptors (GPCRs), membrane-embedded proteases, RNA-binding proteins, and RNA. Yinglong received the Scientist Development Award from American Heart Association in 2017 and OpenEye Outstanding Junior Faculty Award from ACS Computational Chemistry in 2021. He has been productive in research with >80 published papers and 37 H-index so far. He has received funding from American Heart Association, NIH and NSF.