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  Daniel T. Kamei, Ph.D.
 
 
 

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.

 

 

   

 

 

 

 

 

 

 

 

 

 

 

 

 

 
 
  420 Westwood Plaza, Room 5121 Engineering V,
PO Box 951600, Los Angeles, California 90095-1600
phone 310.267.4985
fax 310.794.5956