Jiajian Liu1, Gary D Stormo. 1. Department of Genetics, Washington University School of Medicine, St, Louis, MO 63110, USA. jjliu@ural.wustl.edu
Abstract
BACKGROUND: Recognition codes for protein-DNA interactions typically assume that the interacting positions contribute additively to the binding energy. While this is known to not be precisely true, an additive model over the DNA positions can be a good approximation, at least for some proteins. Much less information is available about whether the protein positions contribute additively to the interaction. RESULTS: Using EGR zinc finger proteins, we measure the binding affinity of six different variants of the protein to each of six different variants of the consensus binding site. Both the protein and binding site variants include single and double mutations that allow us to assess how well additive models can account for the data. For each protein and DNA alone we find that additive models are good approximations, but over the combined set of data there are context effects that limit their accuracy. However, a small modification to the purely additive model, with only three additional parameters, improves the fit significantly. CONCLUSION: The additive model holds very well for every DNA site and every protein included in this study, but clear context dependence in the interactions was detected. A simple modification to the independent model provides a better fit to the complete data.
BACKGROUND: Recognition codes for protein-DNA interactions typically assume that the interacting positions contribute additively to the binding energy. While this is known to not be precisely true, an additive model over the DNA positions can be a good approximation, at least for some proteins. Much less information is available about whether the protein positions contribute additively to the interaction. RESULTS: Using EGR zinc finger proteins, we measure the binding affinity of six different variants of the protein to each of six different variants of the consensus binding site. Both the protein and binding site variants include single and double mutations that allow us to assess how well additive models can account for the data. For each protein and DNA alone we find that additive models are good approximations, but over the combined set of data there are context effects that limit their accuracy. However, a small modification to the purely additive model, with only three additional parameters, improves the fit significantly. CONCLUSION: The additive model holds very well for every DNA site and every protein included in this study, but clear context dependence in the interactions was detected. A simple modification to the independent model provides a better fit to the complete data.
Authors: Michael F Berger; Anthony A Philippakis; Aaron M Qureshi; Fangxue S He; Preston W Estep; Martha L Bulyk Journal: Nat Biotechnol Date: 2006-09-24 Impact factor: 54.908
Authors: Irena Voráčková; Sárka Suchanová; Pavel Ulbrich; William E Diehl; Tomáš Ruml Journal: Protein Expr Purif Date: 2011-05-10 Impact factor: 1.650