Literature DB >> 15023994

On evolutionary conservation of thermodynamic coupling in proteins.

Anthony A Fodor1, Richard W Aldrich.   

Abstract

The inherent complexity of thermodynamic coupling in proteins presents a major challenge in understanding and engineering protein function. Recent work has argued that the study of proteins can be simplified by the use of correlated mutations in the evolutionary record to locate a small subset of thermodynamically coupled residues that participate in functionally important, evolutionarily conserved energetic pathways. To test this hypothesis, we examined the predictions of correlated mutation algorithms for a number of proteins for which coupling between residues has been determined by analysis of double mutant cycles. We find that correlated mutation algorithms can find residue pairs that are physically close and that physically close residue pairs tend to be thermodynamically coupled. We find little evidence, however, for the hypothesis that thermodynamic coupling is limited to the subset of evolutionarily constrained residue positions.

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Year:  2004        PMID: 15023994     DOI: 10.1074/jbc.M402560200

Source DB:  PubMed          Journal:  J Biol Chem        ISSN: 0021-9258            Impact factor:   5.157


  36 in total

1.  Determination of network of residues that regulate allostery in protein families using sequence analysis.

Authors:  Ruxandra I Dima; D Thirumalai
Journal:  Protein Sci       Date:  2006-02       Impact factor: 6.725

2.  Reassessing a sparse energetic network within a single protein domain.

Authors:  Celestine N Chi; Lisa Elfström; Yao Shi; Tord Snäll; Ake Engström; Per Jemth
Journal:  Proc Natl Acad Sci U S A       Date:  2008-03-13       Impact factor: 11.205

3.  New insight into long-range nonadditivity within protein double-mutant cycles.

Authors:  Andrei Y Istomin; M Michael Gromiha; Oleg K Vorov; Donald J Jacobs; Dennis R Livesay
Journal:  Proteins       Date:  2008-02-15

4.  Toward understanding allosteric signaling mechanisms in the ATPase domain of molecular chaperones.

Authors:  Ying Liu; Ivet Bahar
Journal:  Pac Symp Biocomput       Date:  2010

5.  Validation of coevolving residue algorithms via pipeline sensitivity analysis: ELSC and OMES and ZNMI, oh my!

Authors:  Christopher A Brown; Kevin S Brown
Journal:  PLoS One       Date:  2010-06-01       Impact factor: 3.240

6.  SCHEMA recombination of a fungal cellulase uncovers a single mutation that contributes markedly to stability.

Authors:  Pete Heinzelman; Christopher D Snow; Matthew A Smith; Xinlin Yu; Arvind Kannan; Kevin Boulware; Alan Villalobos; Sridhar Govindarajan; Jeremy Minshull; Frances H Arnold
Journal:  J Biol Chem       Date:  2009-07-22       Impact factor: 5.157

7.  Protein sectors: evolutionary units of three-dimensional structure.

Authors:  Najeeb Halabi; Olivier Rivoire; Stanislas Leibler; Rama Ranganathan
Journal:  Cell       Date:  2009-08-21       Impact factor: 41.582

8.  Detecting coevolution without phylogenetic trees? Tree-ignorant metrics of coevolution perform as well as tree-aware metrics.

Authors:  J Gregory Caporaso; Sandra Smit; Brett C Easton; Lawrence Hunter; Gavin A Huttley; Rob Knight
Journal:  BMC Evol Biol       Date:  2008-12-03       Impact factor: 3.260

9.  Integration of evolutionary features for the identification of functionally important residues in major facilitator superfamily transporters.

Authors:  Jouhyun Jeon; Jae-Seong Yang; Sanguk Kim
Journal:  PLoS Comput Biol       Date:  2009-10-02       Impact factor: 4.475

10.  Disentangling direct from indirect co-evolution of residues in protein alignments.

Authors:  Lukas Burger; Erik van Nimwegen
Journal:  PLoS Comput Biol       Date:  2010-01-01       Impact factor: 4.475

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