Protein Structure-Based Prediction of Functional Information

Northeastern University, Boston MA

Investigators

Abstract

One of the most important tasks in genome research is to discover the function of the many gene products whose sequences are now known. Structural genomics efforts are rapidly increasing the number of known three-dimensional structures of these gene products, but the determination of function from the structure has proved to be difficult. The goals of this project are to develop and implement a methodology for the prediction of functional sites in proteins from their three-dimensional structures alone. This method will be fast, so that it can analyze structures on a high-throughput basis. The method will also be independent of any sequence or structure alignments or comparisons, so that it is applicable to proteins with few or no homologues, to novel folds, and to engineered structures. The method will begin with the titration curve analyses that have recently been developed by this group and tested specifically for functional site identification. Now these analyses will be coupled with other structure-based calculations, to identify catalytic and binding sites with high degree of accuracy and precision. In addition, hypotheses will be tested in order to understand the basis for the success of the method. The most significant element of intellectual merit of the proposed study is the development of a unique method to aid in the analysis and interpretation of structural genomics data. The ability to predict the function of gene products has broad impact in areas beyond molecular biology, including plant science, agriculture, and counter-bioterrorism efforts. The broader impact of this project includes the training of students, including students from underrepresented groups, at the interface of the biological, physical, and computational sciences. The project will be incorporated into the PI's outreach activities, which include ongoing efforts to promote careers in the sciences to minority youth, including undergraduates and K-12 students.