University of Washington
Associate Professor, Department of Chemical Engineering
Rational design of unique solvents and surfaces holds great potential for providing new ways to use biomolecules in engineering applications, which range from biocatalysis in ionic liquids (ILs) to surface-driven self-assembly of nano/bio materials that mimic nature. Computational models such as molecular dynamics (MD) can connect the atomic scale to the mesoscale for a wide range of problems but many challenges still limit wide-ranging use of these tools to their full potential. The theme of this talk will be to share recent advances in fundamental science and engineering of interfacial phenomena of biomolecules in the context of our group’s efforts to address fundamental challenges preventing wider use of MD-based methods (e.g. timescale limitations in MD
The first part of this talk will highlight how we are using simulations to understand the dominant driving forces that lead to unique orientation and conformation of peptides at the bio/nano interface with an illustration of how the surface/peptide interface strongly dictates the dominant contributions to binding energetics. I will also discuss the challenge of accurately predicting biomolecule structure at interfaces and how a marriage of simulation and sparse experimental data can provide deep insight. Following this I will share several examples related to the formation of biosilica in two systems: peptides based on marine diatoms, and diatom mimics that use simple leucine-lysine (LK) repeat peptides.
Jim Pfaendtner is the Bindra Career Development Professor and Associate Professor of Chemical Engineering at the University of Washington. He holds a B.S. in Chemical Engineering (Georgia Tech, 2001) and a PhD in Chemical Engineering (Northwestern University, 2007). Additional appointments include Senior Scientist at the Pacific Northwest National Lab and a Senior Data Science Fellow at the UW eScience Institute. Jim’s research focus is computational molecular science and his recent teaching interests are in the area of teaching data science skills to grad students in chemical and materials science and engineering. Jim is a recipient of an NSF CAREER the University of Washington Distinguished Teaching Award. Jim is currently the director of an NSF graduate training program (NRT) at the intersection of data science and clean energy.