(7dv) Nano Material Based Protein Sensor Design for Complex Cellular Environments By a Fast Integrated Simulation System.
AIChE Annual Meeting
2017
2017 Annual Meeting
Meet the Faculty Candidate Poster Session - Sponsored by the Education Division
Meet the Faculty Candidate Poster Session
Sunday, October 29, 2017 - 1:00pm to 3:30pm
1) Nanoparticle based protein-sensor design.
Nanoparticle (2D or 3D) based materials are emerging as key components in many techniques in biological applications, whereas their effects on surrounding proteins are not accurately predictable. I am interested in understanding and predicting protein-NP interactions by developing an integrated molecular dynamics simulation system, which will function in predicting protein structural conformation, thermal or denaturant stability, protein-NP binding affinity, and protein orientations with a variety of novel NP biosensor materials.
2) Protein folding in vivo.
How a protein would fold/misfold/aggregate in the cellular environments compared to the traditional in vitro experimental solvent condition recently attracts attentions from researchers. Both experimental methods and simulation methods were recently developed to mimic such complexity. I am particularly interested in the method development that could accurately simulate protein behavior in any mixture of co-solvents and thus have potential scalability leading to the “whole-cell†simulation.
3) Transmembrane proteins: folding, insertion, and signaling.
Transmembrane proteins, such as the G protein-coupled receptors (GPCRs), are a major group of drug-targeting proteins. They could regulate cell responses to its environments by sensing molecules (e.g. drugs) outside of the cell membrane. Therefore, more and more studies have been performed to understand the folding behavior of transmembrane proteins near or in cell membranes both experimentally and computationally. To disentangle the complex effects of the cell membrane environments on protein folding, an important expansion of the co-solvent method leads to the development of a very fast simulation tool for studying protein folding in membranes. I will focus on the computationally understanding of the biophysics of GPCRs such as folding, transportation, and allosteric regulations in cell membranes, which facilitate the drug discovery targeting GPCRs.
Teaching Interests:
I would like to teach general engineering classes that are currently given by the department on undergraduate or graduate levels, such as Engineering Mathematics, Thermodynamics, Kinetics, and Transport Phenomena. Also, I will contribute classes such as Bioinformatics, Computational Biology, Molecular Simulation and Statistical Mechanics for chemical engineers, which are directly related to my research experiences and interests.