Daniel T. Kamei, Ph.D.

Awards and Recognitions

• Early Career Award, Wallace H. Coulter Foundation, 2007-2009

• Northrop Grumman Teaching Award, Henry Samueli School of Engineering and Applied Science, 2007

• Professor of the Year Award, Engineering Society of UCLA (ESUC), 2007

• Kimmel Scholar Award, Sidney Kimmel Foundation for Cancer Research, 2004-2006

• Sloan Foundation/D.O.E. Postdoctoral Fellowship in Computational Molecular Biology, 2003-2003

• NIH Interdepartmental Biotechnology Training Program Grant, 1999-2001

• D.O.D. National Defense Science and Engineering Graduate Fellowship, 1995-1999

Research interests

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