Literature DB >> 11262935

A structure-based approach for prediction of protein binding sites in gene upstream regions.

Y Mandel-Gutfreund1, A Baron, H Margalit.   

Abstract

The challenge of identifying DNA regulatory sequences based on sequence information only has been emphasized in view of the fast accumulation of new genes in the databases. While most predictive algorithms are based on multiple alignments of already known binding sites, here we examine the usefulness of a novel approach that is based on structural information of the protein-DNA complex. It has already been shown that specific recognition between a protein and its DNA target is achieved by stereo-chemical complementarity between the protein amino acids and the DNA bases. The proposed computational scheme uses crystallographic information to define the set of amino acid-base contacts between the proteins of a given DNA-binding protein family and their DNA targets. The compatibility of a given protein to bind to putative regulatory DNA sequences is then evaluated by knowledge-based parameters for amino acid-base interactions. By this procedure gene upstream regions may be screened for potential binding sites for regulatory proteins. Predictions are demonstrated for the E. coli cyclic AMP receptor protein (CRP) which recognizes the DNA via the helix-turn-helix motif, and for various Zif268-like proteins which belong to the Cys2His2 zinc finger family. The advantages and limitations of this approach are discussed.

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Year:  2001        PMID: 11262935     DOI: 10.1142/9789814447362_0015

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  19 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.  rSNP_Guide, a database system for analysis of transcription factor binding to DNA with variations: application to genome annotation.

Authors:  Julia V Ponomarenko; Tatyana I Merkulova; Galina V Orlova; Oleg N Fokin; Elena V Gorshkova; Anatoly S Frolov; Vadim P Valuev; Mikhail P Ponomarenko
Journal:  Nucleic Acids Res       Date:  2003-01-01       Impact factor: 16.971

3.  Re-programming DNA-binding specificity in zinc finger proteins for targeting unique address in a genome.

Authors:  Abhinav Grover; Akshay Pande; Krishna Choudhary; Kriti Gupta; Durai Sundar
Journal:  Syst Synth Biol       Date:  2011-02-19

4.  Prediction of DNA-binding specificity in zinc finger proteins.

Authors:  Sumedha Roy; Shayoni Dutta; Kanika Khanna; Shruti Singla; Durai Sundar
Journal:  J Biosci       Date:  2012-07       Impact factor: 1.826

Review 5.  Protein binding microarrays for the characterization of DNA-protein interactions.

Authors:  Martha L Bulyk
Journal:  Adv Biochem Eng Biotechnol       Date:  2007       Impact factor: 2.635

6.  Targeted editing of goat genome with modular-assembly zinc finger nucleases based on activity prediction by computational molecular modeling.

Authors:  Kai Xiong; Shanshan Li; Hongxiao Zhang; Ye Cui; Debing Yu; Yan Li; Wenxing Sun; Yingying Fu; Yun Teng; Zhi Liu; Xiaolong Zhou; Peng Xiao; Juan Li; Honglin Liu; Jie Chen
Journal:  Mol Biol Rep       Date:  2013-05-05       Impact factor: 2.316

7.  PiDNA: Predicting protein-DNA interactions with structural models.

Authors:  Chih-Kang Lin; Chien-Yu Chen
Journal:  Nucleic Acids Res       Date:  2013-05-22       Impact factor: 16.971

8.  A structural-based strategy for recognition of transcription factor binding sites.

Authors:  Beisi Xu; Dustin E Schones; Yongmei Wang; Haojun Liang; Guohui Li
Journal:  PLoS One       Date:  2013-01-08       Impact factor: 3.240

9.  Engineering transcription factors with novel DNA-binding specificity using comparative genomics.

Authors:  Tasha A Desai; Dmitry A Rodionov; Mikhail S Gelfand; Eric J Alm; Christopher V Rao
Journal:  Nucleic Acids Res       Date:  2009-03-05       Impact factor: 16.971

10.  Prediction of mono- and di-nucleotide-specific DNA-binding sites in proteins using neural networks.

Authors:  Munazah Andrabi; Kenji Mizuguchi; Akinori Sarai; Shandar Ahmad
Journal:  BMC Struct Biol       Date:  2009-05-13
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