Institute of Information Science, Academia Sinica

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Seminar

TIGP--DNA-binding Residues and Binding Mode Prediction with Binding-Mechanism Concerned Models

  • LecturerDr. Yu-Feng Huang (PostDoc, Department of Computer Science and Information Engineering, National Taiwan University)
    Host: Miss Elsa Pan
  • Time2010-03-11 (Thu.) 14:00 – 15:00
  • LocationAuditorium 106 at new IIS Building
Abstract
Abstract: Background Protein-DNA interactions are essential for fundamental biological activities including DNA transcription, replication, packaging, repair and rearrangement. Proteins interacting with DNA can be classified into two categories of binding mechanisms – sequence-specific and non-specific binding. Protein-DNA specific binding provides a mechanism to recognize correct nucleotide base pairs for sequence-specific identification. Protein-DNA non-specific binding shows sequence independent interaction for accelerated targeting by interacting with DNA backbone. Both sequence-specific and non-specific binding residues contribute to their roles for interaction. Results The proposed framework has two stage predictors: DNA-binding residues prediction and binding mode prediction. In the first stage – 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. While combining prediction results of sequence-specific and non-specific binding residues with OR operation, 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, protein-DNA binding mode prediction achieves 75.83% accuracy while using support vector machine with multi-class prediction. Conclusion This article presents the design of a sequence based predictor aiming to identify sequence-specific and non-specific binding residues in a transcription factor with DNA binding-mechanism concerned. The protein-DNA binding mode prediction was introduced to help improve DNA-binding residues prediction. In addition, the results of this study will help with the design of binding-mechanism concerned predictors for other families of proteins interacting with DNA. Keywords: DNA-binding residues prediction, sequence-specific binding (specific binding), non-specific binding, support vector machine, binding specificity