Literature DB >> 12139929

Using orthologous and paralogous proteins to identify specificity-determining residues in bacterial transcription factors.

Leonid A Mirny1, Mikhail S Gelfand.   

Abstract

Concepts of orthology and paralogy are become increasingly important as whole-genome comparison allows their identification in complete genomes. Functional specificity of proteins is assumed to be conserved among orthologs and is different among paralogs. We used this assumption to identify residues which determine specificity of protein-DNA and protein-ligand recognition. Finding such residues is crucial for understanding mechanisms of molecular recognition and for rational protein and drug design. Assuming conservation of specificity among orthologs and different specificity of paralogs, we identify residues that correlate with this grouping by specificity. The method is taking advantage of complete genomes to find multiple orthologs and paralogs. The central part of this method is a procedure to compute statistical significance of the predictions. The procedure is based on a simple statistical model of protein evolution. When applied to a large family of bacterial transcription factors, our method identified 12 residues that are presumed to determine the protein-DNA and protein-ligand recognition specificity. Structural analysis of the proteins and available experimental results strongly support our predictions. Our results suggest new experiments aimed at rational re-design of specificity in bacterial transcription factors by a minimal number of mutations.

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Year:  2002        PMID: 12139929     DOI: 10.1016/s0022-2836(02)00587-9

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  56 in total

1.  Amino acids determining enzyme-substrate specificity in prokaryotic and eukaryotic protein kinases.

Authors:  Lewyn Li; Eugene I Shakhnovich; Leonid A Mirny
Journal:  Proc Natl Acad Sci U S A       Date:  2003-04-04       Impact factor: 11.205

2.  Prediction of the odorant binding site of olfactory receptor proteins by human-mouse comparisons.

Authors:  Orna Man; Yoav Gilad; Doron Lancet
Journal:  Protein Sci       Date:  2004-01       Impact factor: 6.725

3.  Automated selection of positions determining functional specificity of proteins by comparative analysis of orthologous groups in protein families.

Authors:  Olga V Kalinina; Andrey A Mironov; Mikhail S Gelfand; Aleksandra B Rakhmaninova
Journal:  Protein Sci       Date:  2004-02       Impact factor: 6.725

4.  SDPpred: a tool for prediction of amino acid residues that determine differences in functional specificity of homologous proteins.

Authors:  Olga V Kalinina; Pavel S Novichkov; Andrey A Mironov; Mikhail S Gelfand; Aleksandra B Rakhmaninova
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

5.  Surveying the manifold divergence of an entire protein class for statistical clues to underlying biochemical mechanisms.

Authors:  Andrew F Neuwald
Journal:  Stat Appl Genet Mol Biol       Date:  2011-08-04

Review 6.  Engineering the acyltransferase substrate specificity of assembly line polyketide synthases.

Authors:  Briana J Dunn; Chaitan Khosla
Journal:  J R Soc Interface       Date:  2013-05-29       Impact factor: 4.118

7.  Functional specificity lies within the properties and evolutionary changes of amino acids.

Authors:  Saikat Chakrabarti; Stephen H Bryant; Anna R Panchenko
Journal:  J Mol Biol       Date:  2007-08-22       Impact factor: 5.469

8.  Partially-supervised protein subclass discovery with simultaneous annotation of functional residues.

Authors:  Benjamin Georgi; Jörg Schultz; Alexander Schliep
Journal:  BMC Struct Biol       Date:  2009-10-26

9.  Ensemble approach to predict specificity determinants: benchmarking and validation.

Authors:  Saikat Chakrabarti; Anna R Panchenko
Journal:  BMC Bioinformatics       Date:  2009-07-02       Impact factor: 3.169

10.  Characterization and prediction of residues determining protein functional specificity.

Authors:  John A Capra; Mona Singh
Journal:  Bioinformatics       Date:  2008-05-01       Impact factor: 6.937

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