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Associate
Professor
Department of Bioengineering
5121J Engineering V
kamei@seas.ucla.edu
Kamei Lab website |
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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
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Research
Description
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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.
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