Literature DB >> 15326602

Predicting interactions of winged-helix transcription factors with DNA.

Victoria A Roberts1, David A Case, Vickie Tsui.   

Abstract

Determining protein-DNA interactions is important for understanding gene regulation, DNA repair and chromatin structure. Unfortunately, the structures of DNA-bound complexes are often difficult to obtain experimentally, so the development of computational methods that provide good models of these complexes would be valuable. Here, we present a rigid-body docking approach using the computer program DOT. DOT performs a complete, six-dimensional search of all orientations for two rigid molecules and calculates the interaction energy as the sum of electrostatic and van der Waals terms. DOT was applied to three winged-helix transcription factors that share similar DNA-binding structural motifs but bind DNA in different ways. Docking with linear B-form DNA models accomplished several objectives; it (1) distinguished the different ways the transcription factors bind DNA, (2) identified each protein's DNA-binding site and the DNA orientation at the site and (3) gave at least one solution among the three best-ranked that shows the protein side chain-DNA base interactions responsible for recognition. Furthermore, the ensemble of top-ranked, docked linear B-DNA fragments indicated the DNA bending induced upon protein binding. Docking linear B-DNA to structures of the transcription factor FadR suggests that the allosteric, conformational change induced upon effector binding results in loss of the ability to bend DNA as well as loss of sequence-specific interactions with DNA. The electrostatic energy term calculated by DOT is comparable to the electrostatic binding energy calculated by Poisson-Boltzmann methods. Our results show rigid-body docking that includes a rigorous treatment of the electrostatic interaction energy can be effective in predicting protein-DNA interactions. Copyright 2004 Wiley-Liss, Inc.

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Year:  2004        PMID: 15326602     DOI: 10.1002/prot.20193

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  13 in total

1.  Complex of linker histone H5 with the nucleosome and its implications for chromatin packing.

Authors:  Li Fan; Victoria A Roberts
Journal:  Proc Natl Acad Sci U S A       Date:  2006-05-22       Impact factor: 11.205

2.  Transcriptional interference and repression modulate the conjugative ability of the symbiotic plasmid of Rhizobium etli.

Authors:  Edgardo Sepúlveda; Daniel Pérez-Mendoza; Miguel A Ramírez-Romero; María J Soto; Isabel M López-Lara; Otto Geiger; Juan Sanjuán; Susana Brom; David Romero
Journal:  J Bacteriol       Date:  2008-04-18       Impact factor: 3.490

3.  Solvated protein-DNA docking using HADDOCK.

Authors:  Marc van Dijk; Koen M Visscher; Panagiotis L Kastritis; Alexandre M J J Bonvin
Journal:  J Biomol NMR       Date:  2013-04-30       Impact factor: 2.835

4.  Identification of the rctA gene, which is required for repression of conjugative transfer of rhizobial symbiotic megaplasmids.

Authors:  Daniel Pérez-Mendoza; Edgardo Sepúlveda; Victoria Pando; Socorro Muñoz; Joaquina Nogales; José Olivares; Maria J Soto; José A Herrera-Cervera; David Romero; Susana Brom; Juan Sanjuán
Journal:  J Bacteriol       Date:  2005-11       Impact factor: 3.490

5.  C-Terminal Domain of Integrase Binds between the Two Active Sites.

Authors:  Victoria A Roberts
Journal:  J Chem Theory Comput       Date:  2015-08-06       Impact factor: 6.006

6.  Predicting protein-DNA interactions by full search computational docking.

Authors:  Victoria A Roberts; Michael E Pique; Lynn F Ten Eyck; Sheng Li
Journal:  Proteins       Date:  2013-10-18

7.  DOT2: Macromolecular docking with improved biophysical models.

Authors:  Victoria A Roberts; Elaine E Thompson; Michael E Pique; Martin S Perez; L F Ten Eyck
Journal:  J Comput Chem       Date:  2013-05-21       Impact factor: 3.376

8.  Combining H/D exchange mass spectroscopy and computational docking reveals extended DNA-binding surface on uracil-DNA glycosylase.

Authors:  Victoria A Roberts; Michael E Pique; Simon Hsu; Sheng Li; Geir Slupphaug; Robert P Rambo; Jonathan W Jamison; Tong Liu; Jun H Lee; John A Tainer; Lynn F Ten Eyck; Virgil L Woods
Journal:  Nucleic Acids Res       Date:  2012-04-06       Impact factor: 16.971

9.  Pushing the limits of what is achievable in protein-DNA docking: benchmarking HADDOCK's performance.

Authors:  Marc van Dijk; Alexandre M J J Bonvin
Journal:  Nucleic Acids Res       Date:  2010-05-13       Impact factor: 16.971

10.  Predicting DNA-binding locations and orientation on proteins using knowledge-based learning of geometric properties.

Authors:  Chien-Chih Wang; Chien-Yu Chen
Journal:  Proteome Sci       Date:  2011-10-14       Impact factor: 2.480

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