Various proteins with specific properties and functions exist in organisms, they perform all important biochemical activities. The biochemical functions of proteins are determined by their structures. One of the most important issues in the life science is to predict the three-dimensional structures with protein sequences, and then to deduce their biochemical functions. To predict protein structure precisely will accelerate biochemical research. However, it is a challenge task to obtain the real structure of a protein. The objective of this study is to develop a protein structure prediction methodology based on a structure-known protein (such as the proteins in the PDB database), where the two protein sequences are extremely similar. Some folding algorithms, such as U-fold and S-fold, have been developed to predict protein structures. However, the folding algorithms work on a grid lattice, which is very different from the real structure of a protein. Here we use the curve fitting technique, such as B-splines, to convert the lattice model and a real structure to the same domain, that is, the curve. We therefore perform curve (structure) alignment on them. The curve alignment can also be used to evaluate the similarity between two structures. By the experimental results, our protein structure prediction method performs well when we get two protein sequences with similarity that is not too high.

Thesis (M.S.)--University of Wyoming, 2008. / Title from PDF title page (viewed on August 3, 2009). Includes bibliographical references (p. 65-68).

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