Andrew White

Assistant Professor
University of Washington, PhD, 2013

208C Gavett Hall
(585) 276-7395
Fax: (585.) 273-1348


Selected Honors & Awards

Institute for Biophysics Dynamics Yen Fellow, 2013
Runstead Fellow, 2008-2009

Recent Publications

White, AD.; Keefe, A.; Ella-Menye, J-R.; Nowinshi, AK.; Shao, Q.; Jiang, S.; "Free Energy of solvated Salt Bridges: A Simulation and Experimental Study." J. Phys. Chem. B. 2013, 117 (24), 7254-7259.

White, AD.; Keefe, AJ.; Nowinski, AK.; Shao, Q.; Caldwell, K.; Jiang, S. "Standardizing and Simplifying Analysis of Peptide Library Data."J. Chem. Inf. Model 2013, 53, 493-499.

Brault, ND.; White, AD.; Taylor, AD.; Yu, Q.; Jiang, S. "A Directly Functionalizable Surface Platform for Protein Array in Undiluted Human blood Plasma." Anal. Chem. 2013, 85,1447-1453.

Keefe, AJ.; Caldwell, K.; Nowinski, AK.; White, AD.; Thakkar, A.; Jiang, S.; "Screening Nonspecific Interactions of Peptides with Eliminated Background Interference." Biomaterials 2012, 34, 1871-1877.

White, AD.; Huang, W.; Jiang, S.; "Role of Non-specific Interactions in Molecular Chaperones through Model-based Bioinformatics." Biophys. J. 2012, 103, 2484-2491.

Research Overview

My group uses experiments, molecular simulations, and machine-learning to design new materials. Experiments answer the essential question of if and how well a material works for a particular application. Molecular simulation provides the molecular insight into why a material works. Machine-learning provides the tool to optimize a material so that it works best. Members of my group apply these three techniques to craft new materials for biomedical devices and lithium ion batteries. One of the main class of materials we study is peptides, which are derived from the constituent amino acids that make up proteins. Peptides have a great chemical diversity yet can be controlled on the near atomic scale.