Prediction of Transcription Factor Domain based on Analysis of Specific and non-Specific DNA-Binding Residues on the Protein Sequence
Date Issued
2009
Date
2009
Author(s)
Huang, Chun-Chin
Abstract
Protein-DNA interactions are essential for fundamental biochemical activities including DNA transcription, replication, packaging, repair and rearrangement. Proteins interacting with DNA can be classified into two modes distinguished by sequence-specific and non-specific binding respectively. Protein-DNA specific binding provides a mechanism to recognize correct nucleotide base pairs namely sequence-specific identification. On the other hand, protein-DNA non-specific binding shows relatively little base-sequence preference and interacts with DNA backbone.n this thesis, we present a two stage Protein-DNA binding prediction. In the first stage of DNA-binding residues prediction, the predictor for DNA specific binding residues achieves 96.45% accuracy with 50.14% sensitivity, 99.31% specificity, 81.70% precision, and 62.15% F-measure. The predictor for DNA non-specific binding residues achieves 89.14% accuracy with 53.06% sensitivity, 95.25% specificity, 65.47% precision, and 58.62% F-measure. In addition, we combine the results of sequence-specific and non-specific binding residues predicted in previous stage with OR operation, and the predictor achieves 89.26% accuracy with 56.86% sensitivity, 95.63% specificity, 71.92% precision, and 63.51% F-measure. In the second stage, a protein-DNA interaction mode predictor is proposed. It can achieve 75.83% accuracy while using support vector machine with multi-class prediction.his article presents the design of a sequence-based predictor aiming to identify the sequence-specific and non-specific DNA-binding residues in a transcription factor with DNA binding-mechanism concerned. The protein-DNA interaction mode prediction was introduced to provide biochemist more structural hint and help improve previous DNA-binding residues prediction. In addition, we will exploit the experiences learned in this study to design binding-mechanism concerned predictors for other types of DNA-contacted proteins.
Subjects
DNA-binding residues prediction
sequence-specific binding
non-specific binding
support vector machine
transcription factor
Type
thesis
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