A New Method for Protein Tertiary Structure Prediction

Y. Shang, R. Bondugula, D. Xu, and Q. Wang (USA)


Protein tertiary structure prediction, protein fragment retrieval, multidimensional scaling, local refinement


In this paper, we propose a new method for protein structure prediction based on the mini-threading approach. It has two main components, relevant protein fragment retrieval and protein 3-D structure construction. First, we develop new computational techniques to identify useful fragments in Protein Data Bank (PDB) for a given query protein. Then, different from the angular restraints used in most existing mini-threading methods, we formulate spatial restraints derived from the alignments between a query sequence and its fragment hits of known structures in Cartesian coordinates. We include additional information for the scoring function, such as pair-wise contact potential and apply classical multidimensional scaling method for 3-D structure construction. The structure is further refined by local optimization algorithms. The new method represents a novel framework that can utilize the information in the known protein structure database more effectively and efficiently than existing methods.

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