title: Context-dependent DNA recognition code for C2H2 zinc-finger transcription factors.
abstract: BACKGROUND
  Modeling and identifying the DNA-protein recognition code is one of the most challenging problems in computational biology. Several quantitative methods have been developed to model DNA-protein interactions with specific focus on the C(2)H(2) zinc-finger proteins, the largest transcription factor family in eukaryotic genomes. In many cases, they performed well. But the overall the predictive accuracy of these methods is still limited. One of the major reasons is all these methods used weight matrix models to represent DNA-protein interactions, assuming all base-amino acid contacts contribute independently to the total free energy of binding.
  
  
  RESULTS
  We present a context-dependent model for DNA-zinc-finger protein interactions that allows us to identify inter-positional dependencies in the DNA recognition code for C(2)H(2) zinc-finger proteins. The degree of non-independence was detected by comparing the linear perceptron model with the non-linear neural net (NN) model for their predictions of DNA-zinc-finger protein interactions. This dependency is supported by the complex base-amino acid contacts observed in DNA-zinc-finger interactions from structural analyses. Using extensive published qualitative and quantitative experimental data, we demonstrated that the context-dependent model developed in this study can significantly improves predictions of DNA binding profiles and free energies of binding for both individual zinc fingers and proteins with multiple zinc fingers when comparing to previous positional-independent models. This approach can be extended to other protein families with complex base-amino acid residue interactions that would help to further understand the transcriptional regulation in eukaryotic genomes.
  
  
  BACKGROUND
  The software implemented as c programs and are available by request. http://ural.wustl.edu/softwares.html
authors.affiliation: Department of Genetics, Washington University School of Medicine, 660 S Euclid, Box 8232, St. Louis, MO 63110, USA.
authors.forename: Jiajian
authors.initials: J
authors.lastname: Liu
authors.forename: Gary D
authors.initials: GD
authors.lastname: Stormo
mesh_terms: D001483:Base Sequence; D001665:Binding Sites; D003198:Computer Simulation; D004247:DNA / Q000737:chemistry / Q000235:genetics*; D004268:DNA-Binding Proteins / Q000737:chemistry / Q000235:genetics*; D008957:Models, Genetic; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods*; D011485:Protein Binding; D014157:Transcription Factors / Q000737:chemistry / Q000235:genetics*; D016335:Zinc Fingers / Q000235:genetics*
chemical_list: D004268:DNA-Binding Proteins; D014157:Transcription Factors; D004247:DNA