An SVM-based method for assessment of transcription factor-DNA complex models.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Atomic details of protein-DNA complexes can provide insightful information for better understanding of the function and binding specificity of DNA binding proteins. In addition to experimental methods for solving protein-DNA complex structures, protein-DNA docking can be used to predict native or near-native complex models. A docking program typically generates a large number of complex conformations and predicts the complex model(s) based on interaction energies between protein and DNA. However, the prediction accuracy is hampered by current approaches to model assessment, especially when docking simulations fail to produce any near-native models.

Authors

  • Rosario I Corona
    Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA.
  • Sanjana Sudarshan
    Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA.
  • Srinivas Aluru
    School of Computational Science and Engineering, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, GA, 30332, USA.
  • Jun-Tao Guo
    Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA. jguo4@uncc.edu.