Literature DB >> 22052502

A critical evaluation of correlated mutation algorithms and coevolution within allosteric mechanisms.

Dennis R Livesay1, Kyle E Kreth, Anthony A Fodor.   

Abstract

The notion of using the evolutionary history encoded within multiple sequence alignments to predict allosteric mechanisms is appealing. In this approach, correlated mutations are expected to reflect coordinated changes that maintain intramolecular coupling between residue pairs. Despite much early fanfare, the general suitability of correlated mutations to predict allosteric couplings has not yet been established. Lack of progress along these lines has been hindered by several algorithmic limitations including phylogenetic artifacts within alignments masking true covariance and the computational intractability of consideration of more than two correlated residues at a time. Recent progress in algorithm development, however, has been substantial with a new generation of correlated mutation algorithms that have made fundamental progress toward solving these difficult problems. Despite these encouraging results, there remains little evidence to suggest that the evolutionary constraints acting on allosteric couplings are sufficient to be recovered from multiple sequence alignments. In this review, we argue that due to the exquisite sensitivity of protein dynamics, and hence that of allosteric mechanisms, the latter vary widely within protein families. If it turns out to be generally true that even very similar homologs display a wide divergence of allosteric mechanisms, then even a perfect correlated mutation algorithm could not be reliably used as a general mechanism for discovery of allosteric pathways.

Mesh:

Substances:

Year:  2012        PMID: 22052502     DOI: 10.1007/978-1-61779-334-9_21

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  21 in total

Review 1.  The functional importance of co-evolving residues in proteins.

Authors:  Inga Sandler; Nitzan Zigdon; Efrat Levy; Amir Aharoni
Journal:  Cell Mol Life Sci       Date:  2013-09-01       Impact factor: 9.261

2.  Severing of a hydrogen bond disrupts amino acid networks in the catalytically active state of the alpha subunit of tryptophan synthase.

Authors:  Jennifer M Axe; Kathleen F O'Rourke; Nicole E Kerstetter; Eric M Yezdimer; Yan M Chan; Alexander Chasin; David D Boehr
Journal:  Protein Sci       Date:  2014-12-11       Impact factor: 6.725

3.  Pareto Optimization of Combinatorial Mutagenesis Libraries.

Authors:  Deeptak Verma; Gevorg Grigoryan; Chris Bailey-Kellogg
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2018-07-23       Impact factor: 3.710

4.  Intramolecular allosteric communication in dopamine D2 receptor revealed by evolutionary amino acid covariation.

Authors:  Yun-Min Sung; Angela D Wilkins; Gustavo J Rodriguez; Theodore G Wensel; Olivier Lichtarge
Journal:  Proc Natl Acad Sci U S A       Date:  2016-03-15       Impact factor: 11.205

Review 5.  Correlated positions in protein evolution and engineering.

Authors:  Jorick Franceus; Tom Verhaeghe; Tom Desmet
Journal:  J Ind Microbiol Biotechnol       Date:  2016-08-11       Impact factor: 3.346

Review 6.  Using Evolution to Guide Protein Engineering: The Devil IS in the Details.

Authors:  Liskin Swint-Kruse
Journal:  Biophys J       Date:  2016-07-12       Impact factor: 4.033

7.  Energetic coupling between an oxidizable cysteine and the phosphorylatable N-terminus of human liver pyruvate kinase.

Authors:  Todd Holyoak; Bing Zhang; Junpeng Deng; Qingling Tang; Charulata B Prasannan; Aron W Fenton
Journal:  Biochemistry       Date:  2013-01-11       Impact factor: 3.162

8.  Structured States of Disordered Proteins from Genomic Sequences.

Authors:  Agnes Toth-Petroczy; Perry Palmedo; John Ingraham; Thomas A Hopf; Bonnie Berger; Chris Sander; Debora S Marks
Journal:  Cell       Date:  2016-09-22       Impact factor: 41.582

9.  A case study comparing quantitative stability-flexibility relationships across five metallo-β-lactamases highlighting differences within NDM-1.

Authors:  Matthew C Brown; Deeptak Verma; Christian Russell; Donald J Jacobs; Dennis R Livesay
Journal:  Methods Mol Biol       Date:  2014

10.  Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores.

Authors:  Daniel J Parente; J Christian J Ray; Liskin Swint-Kruse
Journal:  Proteins       Date:  2015-11-17
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.