Department of Mathematics
Topic: Mathematical approaches for solvation and binding free energy predictions
Date: Friday, September 30
Time: 9 to 10 a.m.
Place: B448 Life Science Bldg
Abstract: Solvation is an elementary process in nature and its understanding is a prerequisite for the study of more complex processes, such as ion channel transport, protein specification, protein-drug binding, and signal transduction. Although there has been much advance in solvation analysis in the past decade, protein-ligand binding prediction, which is at the heart of drug design, remains a grand challenge. We discuss a number of mathematical techniques for automatic and blind prediction of molecular solvation and protein-ligand binding free energies. Our approaches include multiscale modeling, variation PDE, differential geometry, graph theory, uncertainty quantification, and machine learning. Extensive comparison with experimental data confirms the superiority of mathematical methodologies