Public Health Sciences Division, Fred Hutch
Interim Program Head
Herbold Computational Biology Program, Fred Hutch
Dr. Phil Bradley is a computational biologist who studies the 3-D structures of proteins, the nano-sized molecular machines that power nearly all of life’s processes. He develops software to visualize and predict how one kind of protein will interact with another protein or with molecules such as RNA and DNA, which carry genetic information. He is a leading figure in the new field of de novo protein design, in which scientists envision and build proteins unlike anything found in nature. He and colleagues at Fred Hutch and the Institute for Protein Design at the University of Washington have designed proteins that close in on themselves, forming rings that resemble tiny donuts. Their elegant, symmetrical structure may serve a host of medical applications. Dr. Bradley and colleague Dr. Barry Stoddard are working with Hutch immunotherapy researcher Dr. Stanley Riddell and vaccine expert Dr. Larry Corey to explore the use of these donut proteins as molecular backbones for therapeutics. Their experiments will test whether the modular structure of donut proteins can support and deliver multiple copies of the active biochemicals that make drugs or vaccines work, improving their performance. He continues research he began as a postdoctoral fellow at UW developing Rosetta, a world-leading software tool for designing protein structures and predicting protein interactions. Dr. Bradley is currently working on computer programs to predict how selectively and precisely proteins will bind with DNA and with protein snippets called peptides. These molecular interactions are essential for life and occur continually inside every one of the trillions of cells in our bodies.
Ph.D., Mathematics, Massachusetts Institute of Technology, 2001
B.S., Mathematics, Rice University, 1995
Dr. Bradley’s current research interests include prediction of protein-DNA and protein-peptide interaction specificity, design of novel tandem repeat architectures, and development of accurate and efficient potential functions for use in structure prediction and design. He is also one of the leaders of the development and application of new algorithms for molecular modeling within the framework of the Rosetta software package, a set of tools for the prediction and design of protein structures and interactions.
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