Literature DB >> 12001270

Is there a code for protein-DNA recognition? Probab(ilistical)ly. . .

Panayiotis V Benos1, Alan S Lapedes, Gary D Stormo.   

Abstract

Transcriptional regulation of all genes is initiated by the specific binding of regulatory proteins called transcription factors to specific sites on DNA called promoter regions. Transcription factors employ a variety of mechanisms to recognise their DNA target sites. In the last few decades, attempts have been made to describe these mechanisms by general sets of rules and associated models. We give an overview of these models, starting with a historical review of the somewhat controversial issue of a "recognition code" governing protein-DNA interaction. We then present a probabilistic framework in which advantages and disadvantages of various models can be discussed. Finally, we conclude that simplifying assumptions about additivity of interactions are sufficiently justified in many situations (and can be suitably extended in other situations) to allow a unifying concept of a "probabilistic code" for protein-DNA recognition to be defined. Copyright 2002 Wiley Periodicals, Inc.

Mesh:

Substances:

Year:  2002        PMID: 12001270     DOI: 10.1002/bies.10073

Source DB:  PubMed          Journal:  Bioessays        ISSN: 0265-9247            Impact factor:   4.345


  45 in total

1.  Additivity in protein-DNA interactions: how good an approximation is it?

Authors:  Panayiotis V Benos; Martha L Bulyk; Gary D Stormo
Journal:  Nucleic Acids Res       Date:  2002-10-15       Impact factor: 16.971

2.  Comprehensive quantitative analyses of the effects of promoter sequence elements on mRNA transcription.

Authors:  Michal Lapidot; Yitzhak Pilpel
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

3.  Quantitative modeling of DNA-protein interactions: effects of amino acid substitutions on binding specificity of the Mnt repressor.

Authors:  Tsz-Kwong Man; Joshua SungWoo Yang; Gary D Stormo
Journal:  Nucleic Acids Res       Date:  2004-08-02       Impact factor: 16.971

4.  Quantitative high-throughput analysis of transcription factor binding specificities.

Authors:  Jane Linnell; Richard Mott; Simon Field; Dominic P Kwiatkowski; Jiannis Ragoussis; Irina A Udalova
Journal:  Nucleic Acids Res       Date:  2004-02-27       Impact factor: 16.971

5.  Percolation of the phd repressor-operator interface.

Authors:  Xueyan Zhao; Roy David Magnuson
Journal:  J Bacteriol       Date:  2005-03       Impact factor: 3.490

6.  A quantitative study of lambda-phage SWITCH and its components.

Authors:  Chunbo Lou; Xiaojing Yang; Xili Liu; Bin He; Qi Ouyang
Journal:  Biophys J       Date:  2007-01-26       Impact factor: 4.033

7.  Design of compact, universal DNA microarrays for protein binding microarray experiments.

Authors:  Anthony A Philippakis; Aaron M Qureshi; Michael F Berger; Martha L Bulyk
Journal:  J Comput Biol       Date:  2008-09       Impact factor: 1.479

8.  Maximally efficient modeling of DNA sequence motifs at all levels of complexity.

Authors:  Gary D Stormo
Journal:  Genetics       Date:  2011-02-07       Impact factor: 4.562

9.  Diversity and complexity in DNA recognition by transcription factors.

Authors:  Gwenael Badis; Michael F Berger; Anthony A Philippakis; Shaheynoor Talukder; Andrew R Gehrke; Savina A Jaeger; Esther T Chan; Genita Metzler; Anastasia Vedenko; Xiaoyu Chen; Hanna Kuznetsov; Chi-Fong Wang; David Coburn; Daniel E Newburger; Quaid Morris; Timothy R Hughes; Martha L Bulyk
Journal:  Science       Date:  2009-05-14       Impact factor: 47.728

10.  Modeling the quantitative specificity of DNA-binding proteins from example binding sites.

Authors:  Dana S F Homsi; Vineet Gupta; Gary D Stormo
Journal:  PLoS One       Date:  2009-08-25       Impact factor: 3.240

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