461800 Accelerating Materials Design: Computer Simulations and QSAR Modeling

Sunday, November 13, 2016
Continental 4 & 5 (Hilton San Francisco Union Square)
Qing Shao, Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC

Research Interests:

My future research group will focus on designing soft materials and processes that can help us face critical health, energy and environment challenges. Computer simulations and QSAR modeling have shown their ability to accelerate materials discovery and process design by revealing critical molecular-level mechanisms, providing rational design principles, and identifying key molecular architectures. My three research projects are to design (1) zwitterionic electrolytes for Li+batteries and solar cells, (2) peptide materials for high-performance medical diagnostics and (3) amyloid-forming peptides for industrial catalysts using computer simulations and QSAR modeling.

My PhD and postdoctoral research experiences equip me with the expertise to apply/develop computer simulations/QSAR modeling in cooperation with experimentalists. My PhD research in Prof. Shaoyi Jiang’s group at the University of Washington focused on understanding and designing zwitterionic anti-biofouling materials using computer simulations and experiment. Zwitterionic materials possess cationic and anionic groups in one moiety. We developed force field parameters for zwitterionic moieties, investigated hydration, protein interaction, ion interaction, and self-association of zwitterionic materials, and prepared and characterized zwitterionic polymers. This work explained the anti-biofouling mechanisms of zwitterionic materials and developed principles for designing new zwitterionic moieties. One moiety designed in silicoby us was verified to resist biofouling in experiment.

My postdoctoral research in Prof. Carol Hall’s group focuses on understanding and predicting nanoparticle toxicity. Excitement about the applications envisioned for nanomaterials in energy, medicine and electronics is tempered by concerns about their toxicity. As the first response of a biological fluid to the intrusion of nanoparticles is the formation of a protein corona that determines the nanoparticle’s toxicity, we take a computational approach to learn the mechanisms that govern the formation of a protein corona around nanoparticles. A coarse-grained model was developed to describe protein-protein and protein-nanoparticle interactions. Combining this coarse-grained model, atomistic simulations and QSAR modeling, we (1) explore how binding to the nanoparticle affects the structure and dynamics of a key blood protein, albumin, (2) decode the common features in the binding configurations of 2315 human proteins and gold nanoparticles, and (3) develop models that can predict protein-nanoparticle interaction energies. This work deepens our understanding of protein-nanoparticle interactions, paving the way to predict and assess nanoparticle toxicity.

Teaching Interests:

I earned my bachelor and PhD degrees in chemical engineering and have been conducting research in chemical engineering for more than 10 years. I am confident of my abilities to teach all chemical engineering courses at the undergraduate and graduate levels, and I am eager to do so. I am particularly interested in teaching thermodynamics, transport processes, process design and applied mathematics.

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