Correlated positions in protein evolution and engineering
- PMID: 27514664
- DOI: 10.1007/s10295-016-1811-1
Correlated positions in protein evolution and engineering
Abstract
Statistical analysis of a protein multiple sequence alignment can reveal groups of positions that undergo interdependent mutations throughout evolution. At these so-called correlated positions, only certain combinations of amino acids appear to be viable for maintaining proper folding, stability, catalytic activity or specificity. Therefore, it is often speculated that they could be interesting guides for semi-rational protein engineering purposes. Because they are a fingerprint from protein evolution, their analysis may provide valuable insight into a protein's structure or function and furthermore, they may also be suitable target positions for mutagenesis. Unfortunately, little is currently known about the properties of these correlation networks and how they should be used in practice. This review summarises the recent findings, opportunities and pitfalls of the concept.
Keywords: Coevolution; Correlated mutation analysis; Correlated positions; Protein engineering.
Similar articles
-
Rheostats, toggles, and neutrals, Oh my! A new framework for understanding how amino acid changes modulate protein function.J Biol Chem. 2024 Mar;300(3):105736. doi: 10.1016/j.jbc.2024.105736. Epub 2024 Feb 8. J Biol Chem. 2024. PMID: 38336297 Free PMC article. Review.
-
Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores.Proteins. 2015 Dec;83(12):2293-306. doi: 10.1002/prot.24948. Epub 2015 Nov 17. Proteins. 2015. PMID: 26503808 Free PMC article.
-
Protein and cellular engineering with unnatural amino acids.Biotechnol Prog. 2007 Jan-Feb;23(1):28-31. doi: 10.1021/bp060369d. Biotechnol Prog. 2007. PMID: 17269666 Review.
-
Folding alphabets.Nat Struct Biol. 1999 Nov;6(11):994-6. doi: 10.1038/14876. Nat Struct Biol. 1999. PMID: 10542084
-
Using Evolution to Guide Protein Engineering: The Devil IS in the Details.Biophys J. 2016 Jul 12;111(1):10-8. doi: 10.1016/j.bpj.2016.05.030. Biophys J. 2016. PMID: 27410729 Free PMC article. Review.
Cited by
-
Ancestral sequence reconstruction as a tool for structural analysis of modular polyketide synthases.Nat Commun. 2025 Jul 25;16(1):6847. doi: 10.1038/s41467-025-62168-0. Nat Commun. 2025. PMID: 40715098 Free PMC article.
-
Engineering of a Thermostable Biocatalyst for the Synthesis of 2-O-Glucosylglycerol.Chembiochem. 2021 Sep 14;22(18):2777-2782. doi: 10.1002/cbic.202100192. Epub 2021 Jun 2. Chembiochem. 2021. PMID: 33991026 Free PMC article.
-
Recent advances in user-friendly computational tools to engineer protein function.Brief Bioinform. 2021 May 20;22(3):bbaa150. doi: 10.1093/bib/bbaa150. Brief Bioinform. 2021. PMID: 32743637 Free PMC article. Review.
-
A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes.Sci Rep. 2018 Nov 13;8(1):16757. doi: 10.1038/s41598-018-35033-y. Sci Rep. 2018. PMID: 30425279 Free PMC article.
-
The many functions of carbohydrate-active enzymes in family GH65: diversity and application.Appl Microbiol Biotechnol. 2024 Sep 30;108(1):476. doi: 10.1007/s00253-024-13301-4. Appl Microbiol Biotechnol. 2024. PMID: 39348028 Free PMC article. Review.
References
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Other Literature Sources