Reference : Prediction of TF target sites based on atomistic models of protein-DNA complexes.
Scientific journals : Article
Life sciences : Biochemistry, biophysics & molecular biology
http://hdl.handle.net/10993/16681
Prediction of TF target sites based on atomistic models of protein-DNA complexes.
English
Espinosa Angarica, Vladimir mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Perez, Abel Gonzalez [> >]
Vasconcelos, Ana T. [> >]
Collado-Vides, Julio [> >]
Contreras-Moreira, Bruno [> >]
2008
BMC bioinformatics
9
436
Yes (verified by ORBilu)
International
1471-2105
1471-2105
England
[en] TF-binding-sites prediction ; TF-DNA structural models ; direct and indirect readout ; TF-DNA binding specificity
[en] BACKGROUND: The specific recognition of genomic cis-regulatory elements by transcription factors (TFs) plays an essential role in the regulation of coordinated gene expression. Studying the mechanisms determining binding specificity in protein-DNA interactions is thus an important goal. Most current approaches for modeling TF specific recognition rely on the knowledge of large sets of cognate target sites and consider only the information contained in their primary sequence. RESULTS: Here we describe a structure-based methodology for predicting sequence motifs starting from the coordinates of a TF-DNA complex. Our algorithm combines information regarding the direct and indirect readout of DNA into an atomistic statistical model, which is used to estimate the interaction potential. We first measure the ability of our method to correctly estimate the binding specificities of eight prokaryotic and eukaryotic TFs that belong to different structural superfamilies. Secondly, the method is applied to two homology models, finding that sampling of interface side-chain rotamers remarkably improves the results. Thirdly, the algorithm is compared with a reference structural method based on contact counts, obtaining comparable predictions for the experimental complexes and more accurate sequence motifs for the homology models. CONCLUSION: Our results demonstrate that atomic-detail structural information can be feasibly used to predict TF binding sites. The computational method presented here is universal and might be applied to other systems involving protein-DNA recognition.
http://hdl.handle.net/10993/16681
10.1186/1471-2105-9-436
http://www.biomedcentral.com/1471-2105/9/436

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