Engineering functional thermostable proteins using ancestral sequence reconstruction.

Content Provider	Europe PMC
Author	Thomson, Raine E.S. Carrera-Pacheco, Saskya E. Gillam, Elizabeth M.J.
Copyright Year	2022
Abstract	Natural proteins are often only slightly more stable in the native state than the denatured state, and an increase in environmental temperature can easily shift the balance toward unfolding. Therefore, the engineering of proteins to improve protein stability is an area of intensive research. Thermostable proteins are required to withstand industrial process conditions, for increased shelf-life of protein therapeutics, for developing robust ‘biobricks’ for synthetic biology applications, and for research purposes (e.g., structure determination). In addition, thermostability buffers the often destabilizing effects of mutations introduced to improve other properties. Rational design approaches to engineering thermostability require structural information, but even with advanced computational methods, it is challenging to predict or parameterize all the relevant structural factors with sufficient precision to anticipate the results of a given mutation. Directed evolution is an alternative when structures are unavailable but requires extensive screening of mutant libraries. Recently, however, bioinspired approaches based on phylogenetic analyses have shown great promise. Leveraging the rapid expansion in sequence data and bioinformatic tools, ancestral sequence reconstruction can generate highly stable folds for novel applications in industrial chemistry, medicine, and synthetic biology. This review provides an overview of the factors important for successful inference of thermostable proteins by ancestral sequence reconstruction and what it can reveal about the determinants of stability in proteins.
ISSN	00219258
Volume Number	298
PubMed Central reference number	PMC9525910
Issue Number	10
PubMed reference number	36041629
Journal	The Journal of Biological Chemistry [J. Biol. Chem]
e-ISSN	1083351X
DOI	10.1016/j.jbc.2022.102435
Language	English
Publisher	American Society for Biochemistry and Molecular Biology
Publisher Date	2022-08-27
Access Restriction	Open
Rights License	This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). © 2022 The Authors
Subject Keyword	ancestral sequence reconstruction thermostability directed evolution protein engineering synthetic biology biocatalysis molecular evolution cytochrome P450 precambrian ASR, ancestral sequence reconstruction BI, Bayesian inference IPMDH, 3-isopropylmalate dehydrogenase LBCA, Last Bacterial Common Ancestor ML, maximum likelihood MP, maximum parsimony MSA, multiple sequence alignment
Content Type	Text
Resource Type	Article
Subject	Cell Biology Molecular Biology Biochemistry