title: Toward an atomistic model for predicting transcription-factor binding sites.
abstract: Identifying the specific DNA-binding sites of transcription-factor proteins is essential to understanding the regulation of gene expression in the cell. Bioinformatics approaches are fast compared to experiments, but require prior knowledge of multiple binding sites for each protein. Here, we present an atomistic force-field method to predict binding sites based only on the X-ray structure of a related bound complex. Specific flexible contacts between the protein and DNA are modeled by a library of amino acid side-chain rotamers. Using the example of the mouse transcription factor, Zif268, a well-studied zinc-finger protein, we show that the protein sequence alone, without the detailed experimental structure, gives a strong bias toward the consensus binding site.
authors.affiliation: Center for Computational Sciences and Computer Science & Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6164, USA. endresrg@ornl.gov
authors.forename: Robert G
authors.initials: RG
authors.lastname: Endres
authors.forename: Thomas C
authors.initials: TC
authors.lastname: Schulthess
authors.forename: Ned S
authors.initials: NS
authors.lastname: Wingreen
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods; D018360:Crystallography, X-Ray; D004247:DNA / Q000378:metabolism; D004268:DNA-Binding Proteins / Q000737:chemistry / Q000378:metabolism; D051766:Early Growth Response Protein 1; D017874:Immediate-Early Proteins / Q000737:chemistry / Q000378:metabolism; D008958:Models, Molecular; D018583:Pliability; D011237:Predictive Value of Tests; D011487:Protein Conformation; D012984:Software; D012985:Software Design; D014157:Transcription Factors / Q000737:chemistry / Q000378:metabolism*
chemical_list: D004268:DNA-Binding Proteins; D051766:Early Growth Response Protein 1; D017874:Immediate-Early Proteins; D014157:Transcription Factors; D004247:DNA