CBE Seminar: Reid Van Lehn, University of Wisconsin-Madison

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Location: Link to join webinar: https://notredame.zoom.us/j/98221278706?pwd=WFpZNGpjMGo2NEZoWVN5RERmUTBsZz09

The University of Notre Dame Department of Chemical and Biomolecular Engineering presents Reid C. Van Lehn, Conway Assistant Professor, Department of Chemical and Biological Engineering, University of Wisconsin-Madison.
 
Molecular and Data-Centric Modeling of the Nano-Bio Interface
 
Tuesday, April 13; 12:45 p.m. via Zoom Webinar (log into Zoom before joining webinar)
 
 
Abstract:
Gold nanoparticles (GNPs) coated with small-molecule ligands are versatile materials for biological applications, such as drug delivery, biosensing, and photothermal therapy, because their physicochemical properties and corresponding interactions with biological materials can be tailored by selecting ligands from a large available design space. Unfortunately, a central challenge inhibiting GNP design is that subtle differences in GNP composition (e.g., ligand selection and core size) can trigger large changes in macroscopic behavior that are difficult to predict a priori. In this talk, I will discuss my group’s efforts to combine molecular simulations and data-centric techniques to characterize and predict interactions at the nano-bio interface. In the first part of my talk, I will discuss how systematic variations to the properties of ligands protecting small (<10 nm in diameter) GNPs impact interactions with model cell membranes. Using atomistic and coarse-grained simulations, we show that the free energy of membrane adsorption depends on the hydrophobicity of charged ligand end groups in agreement with experimental measurements. We then parameterize quantitative structure-activity relationship models to predict cell uptake based on high-throughput simulations. In the second part of my talk, I will discuss our efforts to predict hydrophobicity as the key surface property relevant to both bilayer interactions and interactions with biomacromolecules. We parameterize convolutional neural networks and descriptor-based regression models to predict interfacial hydration free energies at ligand-functionalized interfaces with spatially varying chemical properties. This work highlights our approach to derive chemically specific design guidelines for GNPs with tailored nano-bio interactions.

Bio:
Reid is the Conway Assistant Professor in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison. He received his Ph.D. in Materials Science and Engineering from MIT under the supervision of Prof. Alfredo Alexander-Katz, then performed research as a NIH Ruth-Kirschtein postdoctoral fellow with Prof. Tom F. Miller III at Caltech. He joined UW-Madison in May 2016, where his group develops and applies molecular simulation methods to characterize, predict, and engineer the physicochemical properties of synthetic and biological soft materials. He has recently been recognized with the 3M Non-Tenured Faculty Award, the UW-Madison Vilas Associate award, and an NSF CAREER award.