Jie Liang, Ph.D. Bioengineering Primary Grant Support: National Science Foundation Career Award, National Institutes of Health R01, Office of Naval Research, and the Whitaker Foundation Protein surface matching
Problem Statement and Motivation •
The structure of proteins provide rich information about how cells work. With the success of structural genomics, soon we will have all human proteins mapped to structures.
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However, we need to develop computational tools to extract information from these structures to understand how cell works and how new diseases can be treated.
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Therefore, the development of computational tools for surface matching and for function prediction will open the door for many new development for health improvement.
Evolution of function
Key Achievements and Future Goals
Technical Approach • • •
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We use geometric models and fast algorithm to characterize surface properties of over thirty protein structures. We develop evolutionary models to understand how proteins overall evolve to acquire different functions using different combination of surface textures. Efficient search methods and statistical models allow us to identify very similar surfaces on totally different proteins Probablistc models and sampling techniques help us to understand how protein works to perform their functions.
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We have developed a web server CASTP (cast.engr.uic.edu) that identify and measures protein surfaces. It has been used by thousands of scientists world wide. We have built a protein surface library for >10,000 proteins, and have developed models to characterize cross reactivities of enzymes. We also developed methods for designing phage library for discovery of peptide drugs. We have developed methods for predicting structures of beta-barrel membrane proteins. Future: Understand how protein fold and assemble, and designing method for engineering better proteins and drugs.