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Mathematical approaches for solvation, binding and drug design

Banff International Research Station for Mathematical Innovation and Discovery

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 Laplacian, uncertainty quantification, and machine learning. Extensive comparison with experimental data confirms the superiority of mathematical methodologies.

Mathematics; Partial differential equations; Biology and other natural sciences; Applied analysis / inverse problems

video/mp4

Author affiliation: Michigan State University

2017-01-27

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/59838

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/4.0/