| Summary: | 碩士 === 國立交通大學 === 生物資訊研究所 === 93 === The prediction of the three-dimensional structure from its sequence is probably one of the most important goals of modern biology. The accurate prediction of protein relative solvent accessibility is useful for the prediction of tertiary structure of a protein. Amino acid solvent accessibility is the degree to which a residue in a protein is accessible to a solvent molecule. Because the binding sites of a protein are usually located on its surface, accurately predicting the surface residues can be regarded as an important step toward determining its function. On the other hand, it has been observed that the distribution of surface residues of a protein is correlated with its subcellular environments; consequently, information of surface residues may improve the prediction of protein subcellular localization.
Presently, out best method is based on the support vector machines using as the input feature vectors, the sliding window that includes the local environment descriptors such as PSSM, secondary structure profile and hydropathy indexes. In my work, relative solvent accessibility based on a 2-state model, for 25%, 16%, 5%, and 0% accessibility are predicted at 77.2%, 77.1%, 80.4%, and 88.4% accuracy, respectively. Furthermore, solvent accessibility prediction methods have in recent years reached accuracy in the range of 75.0-78.3% at 25% threshold. And the results based in a 10-state model can reach 15.2% mean absolute error and 0.51 correlations.
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