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Role of conservative mutations in protein multi-property adaptation

Protein physicochemical properties must undergo complex changes during evolution, as a response to modifications in the organism environment, the result of the proteins taking up new roles or because of the need to cope with the evolution of molecular interacting partners. Recent work has emphasized...

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Detalles Bibliográficos
Autores principales: Rodriguez-Larrea, David, Perez-Jimenez, Raul, Sanchez-Romero, Inmaculada, Delgado-Delgado, Asuncion, Fernandez, Julio M., Sanchez-Ruiz, Jose M.
Formato: Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2895784/
https://www.ncbi.nlm.nih.gov/pubmed/20446918
http://dx.doi.org/10.1042/BJ20100386
Descripción
Sumario:Protein physicochemical properties must undergo complex changes during evolution, as a response to modifications in the organism environment, the result of the proteins taking up new roles or because of the need to cope with the evolution of molecular interacting partners. Recent work has emphasized the role of stability and stability–function trade-offs in these protein adaptation processes. In the present study, on the other hand, we report that combinations of a few conservative, high-frequency-of-fixation mutations in the thioredoxin molecule lead to largely independent changes in both stability and the diversity of catalytic mechanisms, as revealed by single-molecule atomic force spectroscopy. Furthermore, the changes found are evolutionarily significant, as they combine typically hyperthermophilic stability enhancements with modulations in function that span the ranges defined by the quite different catalytic patterns of thioredoxins from bacterial and eukaryotic origin. These results suggest that evolutionary protein adaptation may use, in some cases at least, the potential of conservative mutations to originate a multiplicity of evolutionarily allowed mutational paths leading to a variety of protein modulation patterns. In addition the results support the feasibility of using evolutionary information to achieve protein multi-feature optimization, an important biotechnological goal.