A Study on Sequence Based Prediction of Protein B-factors
Date Issued
2010
Date
2010
Author(s)
Liu, Yu-Cheng
Abstract
A novel dual model sequence based protein B-factors predictor has been achieved in this thesis. To perform functions proteins would change their conformations or be triggered by binding ligand or molecular. Therefore, some protein regions should be flexible (adaptive) to adapt interaction with other molecular and some residues should be rigid to accept molecular single. Predicting protein functions from protein sequence could help us to understand functions of proteins, which would be synthesized to possess certain functions or would not be solved structures by tedious experiments. Protein B-factors, generated from X-ray crystallography, are used to be the protein flexibility index in this study. Protein B-factors reflect the thermal-dynamics of protein solid state and then used to presume the movability of proteins in solution.
In this study, the dual model sequence based protein B-factors predictor perform a superior performance in correlation coefficient 0.5283, generated from independent test, which compare with other two works. The correlation coefficient measures between experimental B-factors and predicted B-factors, comparing with two other works. Moreover, the fitness of prediction is improved in high B-factor regions and low B-factor regions. In this study, the protein flexibility gradient feature is conducted to improve the prediction performance.
There are many different protein sequence based flexibility predictors on variant protein flexibility definitions. Combining information of different protein flexibility predictors may help us to presume protein dynamics.
Key works : Protein flexibility, B-factors, Dual model, The flexibility gradient feature
Subjects
protein flexibility
B-factors
Dual model
Flexibility gradient feature
Type
thesis
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