Literature DB >> 17646316

Prediction of DNA-binding residues from sequence.

Yanay Ofran1, Venkatesh Mysore, Burkhard Rost.   

Abstract

MOTIVATION: Thousands of proteins are known to bind to DNA; for most of them the mechanism of action and the residues that bind to DNA, i.e. the binding sites, are yet unknown. Experimental identification of binding sites requires expensive and laborious methods such as mutagenesis and binding essays. Hence, such studies are not applicable on a large scale. If the 3D structure of a protein is known, it is often possible to predict DNA-binding sites in silico. However, for most proteins, such knowledge is not available.
RESULTS: It has been shown that DNA-binding residues have distinct biophysical characteristics. Here we demonstrate that these characteristics are so distinct that they enable accurate prediction of the residues that bind DNA directly from amino acid sequence, without requiring any additional experimental or structural information. In a cross-validation based on the largest non-redundant dataset of high-resolution protein-DNA complexes available today, we found that 89% of our predictions are confirmed by experimental data. Thus, it is now possible to identify DNA-binding sites on a proteomic scale even in the absence of any experimental data or 3D-structural information. AVAILABILITY: http://cubic.bioc.columbia.edu/services/disis.

Mesh:

Substances:

Year:  2007        PMID: 17646316     DOI: 10.1093/bioinformatics/btm174

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  65 in total

1.  Identification of DNA-binding proteins using structural, electrostatic and evolutionary features.

Authors:  Guy Nimrod; András Szilágyi; Christina Leslie; Nir Ben-Tal
Journal:  J Mol Biol       Date:  2009-02-20       Impact factor: 5.469

2.  Comparative Analysis of the IclR-Family of Bacterial Transcription Factors and Their DNA-Binding Motifs: Structure, Positioning, Co-Evolution, Regulon Content.

Authors:  Inna A Suvorova; Mikhail S Gelfand
Journal:  Front Microbiol       Date:  2021-06-10       Impact factor: 5.640

3.  GntR Family of Bacterial Transcription Factors and Their DNA Binding Motifs: Structure, Positioning and Co-Evolution.

Authors:  Inna A Suvorova; Yuri D Korostelev; Mikhail S Gelfand
Journal:  PLoS One       Date:  2015-07-07       Impact factor: 3.240

4.  PDA: an automatic and comprehensive analysis program for protein-DNA complex structures.

Authors:  RyangGuk Kim; Jun-tao Guo
Journal:  BMC Genomics       Date:  2009-07-07       Impact factor: 3.969

5.  svmPRAT: SVM-based protein residue annotation toolkit.

Authors:  Huzefa Rangwala; Christopher Kauffman; George Karypis
Journal:  BMC Bioinformatics       Date:  2009-12-22       Impact factor: 3.169

6.  DNABINDPROT: fluctuation-based predictor of DNA-binding residues within a network of interacting residues.

Authors:  Pemra Ozbek; Seren Soner; Burak Erman; Turkan Haliloglu
Journal:  Nucleic Acids Res       Date:  2010-05-16       Impact factor: 16.971

7.  NAPS: a residue-level nucleic acid-binding prediction server.

Authors:  Matthew B Carson; Robert Langlois; Hui Lu
Journal:  Nucleic Acids Res       Date:  2010-05-16       Impact factor: 16.971

8.  DNA-binding residues and binding mode prediction with binding-mechanism concerned models.

Authors:  Yu-Feng Huang; Chun-Chin Huang; Yu-Cheng Liu; Yen-Jen Oyang; Chien-Kang Huang
Journal:  BMC Genomics       Date:  2009-12-03       Impact factor: 3.969

9.  Prodepth: predict residue depth by support vector regression approach from protein sequences only.

Authors:  Jiangning Song; Hao Tan; Khalid Mahmood; Ruby H P Law; Ashley M Buckle; Geoffrey I Webb; Tatsuya Akutsu; James C Whisstock
Journal:  PLoS One       Date:  2009-09-17       Impact factor: 3.240

10.  A threading-based method for the prediction of DNA-binding proteins with application to the human genome.

Authors:  Mu Gao; Jeffrey Skolnick
Journal:  PLoS Comput Biol       Date:  2009-11-13       Impact factor: 4.475

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