 |
|
Assistant Professor
Department of Bioengineering
5121J Engineering V
kamei@seas.ucla.edu
Kamei Lab website |
| |
B.S.,
University of California, Berkeley, 1995
M.S., Massachusetts Institute of Technology, 2000
Ph.D., Massachusetts Institute of Technology, 2001
Postdoctoral Research Fellow, Massachusetts Institute
of Technology, 2001-2003
|
| |
Research
Description
 |
My research program is in the area of
molecular cell bioengineering, where we develop and
employ quantitative design principles obtained from
a cell-level context to engineer more effective molecular
therapeutics. Specifically, experiment and computational
modeling are combined to rationally design peptides
and proteins with the goal of improving existing therapies.
Instead of optimizing merely any individual step among
the complex network of dynamic processes involved in
cell regulation, my research takes a systems approach
to analyzing cellular processes. With this quantitative
analysis, design criteria for enhancing efficacy are
identified and then achieved using a combination of
molecular modeling and site-directed mutagenesis.
One application of my research is to rationally develop
therapeutic proteins with increased half-lives. Therapeutic
proteins with increased half-lives should decrease the
frequency of injections and allow the administration
of low and potentially non-toxic concentrations of protein.
Another application of my research is to improve existing
cancer therapies. The overall framework used by my research
group to address these problems consists of the following
three parts:
1. Systems-level,
engineering analysis of cellular processes
2. Molecular modeling of ligand-receptor complexes
3. Quantitative cell biology experiments to test model
predictions
For example, in the case of designing
therapeutic proteins with longer half-lives, the systems-level,
engineering analysis involves investigating cellular
trafficking processes to identify design criteria in
terms of molecular parameters. Molecular modeling is
then performed to identify potential sites for mutations
that can satisfy the design criteria. In the modeling,
electrostatic, van der Waals, and hydrophobic interactions
between the ligand and the receptor are calculated.
Finally, quantitative binding and trafficking experiments
are performed to test the predictions from the engineering
analysis and the molecular modeling.
|