Constructing Structural Model of Protein Functional Domains using ab initio Structure Prediction
Date Issued
2008
Date
2008
Author(s)
Liao, Min-Hung
Abstract
The basic units of all kinds of organisms are proteins. In order to learn more about the protein function, scientists try to understand proteins from different points of view, including protein sequence, protein structure, location of functional residues, and so forth. In the fields of computational biology, the prediction of protein structure has always been the core issue that researchers indefatigably focus on. It has never been easy to tell the protein structure merely through protein sequence; hence methods for predicting the structures are being developed one after another, including approaches based on homology modeling, fold recognition, and ab initio. The issue of determining protein structure is equivalent to the identification of protein folding. Protein structure can be derived from experimental methods such as X-ray crystallography and NMR spectroscopy. Although the accuracy of the experimental methods is higher, their cost is relatively higher and more time consuming as well; researchers therefore come up with the idea of employing theoretical simulation to predict protein structure. The results of computational approaches may not be as precise as that of experimental methods, but some of them are fairly acceptable. For example, the accuracy of secondary structure prediction is about 80%, which provides valuable clues for biologists. This dissertation focuses mainly on how to determine the structure model of a protein functional domain. In the process of biological evolution, important regions are usually conserved. Our method is based on the information derived from three predictors, including the prediction of conserved residues, ordered regions, and domain boundaries. These characteristics of protein sequences are used as the basis for selecting initial functional regions for structure prediction. Furthermore, a structure comparison program is incorporated to evaluate the quality of the estimated region boundary, in order to increase the accuracy of the structure prediction. Results conducted in this thesis show that the proposed method is effectively in identifying the functional regions and delivering satisfied structure model for the proteins of interest.
Subjects
ab initio,Functional Domains, Protein Structure Prediction
Type
thesis
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