CompBio: A New Paradigm of Protein Threading: simultaneous backbone threading and side-chain packing prediction.

University Of Georgia Research Foundation Inc, Athens GA

Investigators

Abstract

The knowledge of the tertiary structure is essential to understanding of the biological function and functional mechanism of a protein. The importance of computational solution to protein structures is increasing owing to the rapid growth in the number of sequenced genomes, and the relatively slow growth rate in the number of experimentally determined protein structures. Here we propose to develop a new paradigm for threading-based protein structure prediction using side-chain information. While residue-based approaches have made threading computationally feasible to predict protein structures in the past decade, we clearly see an urgent need now for more accurate prediction techniques that can provide structural data at higher resolution, to meet the rapidly growing need of structural and functional genomics studies. To address this challenging issue, we will develop a novel computational framework for solving a generalized threading problem, in which backbone threading and side-chain packing are predicted simultaneously. Specifically, we will (a) develop a new energy function that combines residue-level information for backbone threading and atom-level information for side-chain packing; (b) develop a novel algorithmic framework for solving the generalized threading problem; (c) extend this algorithmic framework to deal with more general threading problems such as constrained threading problems; (d) test and evaluate the new threading energy functions and algorithms to demonstrate the feasibility and the power of using side-chain information in protein structure prediction, and (e) develop a freely accessible web-based prediction server to benefit the entire research community. To the best of our knowledge, this project probably represents the first systematic effort in generalizing the current threading paradigm to include the detailed side-chain information during the threading process. While the side-chain information should help to significantly improve the prediction accuracy and resolution of protein structures, the generalized threading problem raises some very challenging computational problems. We expect that this new threading capability, when fully developed and implemented, will significantly improve the state of the art of protein structure prediction. In addition, the new threading energy functions and the algorithmic techniques developed in this project will prove to be useful to other researchers in their own development of protein structure prediction capabilities. We believe that our new threading framework will lead the way in developing a new generation of prediction techniques for protein structures, which will not only provide much more accurate backbone structures compared to the existing threading methods but also provide a big portion of the missing structural information by the current threading techniques, i.e., the side-chains. This project provides an ideal training ground for both undergraduate and graduate students to learn bioinformatics tool development for solving complex biological problems. A new course on "Algorithms for Protein Structure Prediction and Modeling" will be developed based on the research results of this project, which will be offered to both undergraduate and graduate students.