Xiaoran Fu

Education

2004, Ph.D. in Physical Chemistry, from the Department of Chemistry, University of Pennsylvania, Philadelphia, PA
Thesis advisor: Professor Jeffery G. Saven

1997, B.S. in Polymer Science and Engineering from the University of Science and Technology of China (USTC), Hefei, Anhui, P.R.China
Thesis advisor: Professor Dezhu Ma

CDP research

The goal of my research is to combine computational and experimental methods to study interaction specificities among Bcl-2 proteins. Protein-protein interactions are involved in many biological processes, and many diseases are caused by alteration of binding specificities. The Bcl-2 family proteins regulate programmed cell-death (apoptosis) through different binding specificities among the family members. Although extensive experimental studies have been reported regarding how binding behavior affects apoptosis, the physico-chemical principles that determine binding specificity still remain unclear. To study the Bcl-2 protein interactions, the current computational protein-design method needs to be further implemented to address the binding specificity problem. Both explicit implementations of backbone flexibility and direct negative design methods will be developed. Biophysical characterization methods, such as microarray assay and fluorescence polarization assay, will be used to test the computational design and provide feedbacks to refine the computational models.

This work will establish a way of studying protein-protein interactions by combining theoretical calculations and experiments. Computational design is used as a fast and systematic method to explore the key mutations involved in binding interactions. The outcome of this study will be peptide reagents that can help to dissect the complex interaction specificities and cross-talk that occur among the Bcl-2 family proteins. The long-term objectives of this research are to develop peptides reagents that can perturb Bcl-2-induced apoptosis pathways, to be used for research and potentially for therapy, and to establish a model for systematically studying protein-protein interaction-networks using a combination of computation and experiment.