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Computation of enzyme cold adaptation
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.ORCID iD: 0000-0003-2091-0610
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Univ Tromso, Dept Chem, Ctr Theoret & Computat Chem, N-9037 Tromso, Norway..
Univ Tromso, Dept Chem, Ctr Theoret & Computat Chem, N-9037 Tromso, Norway..
2017 (English)In: Nature Reviews Chemistry, E-ISSN 2397-3358, Vol. 1, no 7, article id UNSP 0051Article, review/survey (Refereed) Published
Abstract [en]

Earth has several environments that are potentially hostile to life. The survival of organisms has required the expression of proteins that are adapted to function under extreme temperature, pH, pressure or ionic strength. However, the origin of such adaptations remains, in most cases, an open question. This Review presents a detailed analysis of the specialized enzymes that are able to maintain high catalytic rates at low temperatures and highlights the important role that computational studies have in uncovering the evolutionary principles behind the cold adaptation of enzymes. Although often highly homologous to their mesophilic counterparts, these cold-adapted enzymes have characteristic and universal properties that reflect their evolutionary optimization. In addition to exhibiting maximum reaction rates at lower temperatures, cold-adapted enzymes are more heat-labile and their catalytic mechanisms have distinct signatures in terms of the thermodynamic activation parameters. The structural origins of these properties have been elusive but are hypothesized to be related to protein flexibility.

Place, publisher, year, edition, pages
2017. Vol. 1, no 7, article id UNSP 0051
National Category
Biochemistry and Molecular Biology
Identifiers
URN: urn:nbn:se:uu:diva-345837DOI: 10.1038/s41570-017-0051ISI: 000415236400001OAI: oai:DiVA.org:uu-345837DiVA, id: diva2:1189869
Funder
Knut and Alice Wallenberg FoundationSwedish Research CouncilAvailable from: 2018-03-13 Created: 2018-03-13 Last updated: 2018-03-19Bibliographically approved

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Åqvist, Johan

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