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Protein Structural Information and Evolutionary Landscape by In Vitro Evolution
Protein structure is tightly intertwined with function according to the laws of evolution. Understanding how structure determines function has been the aim of structural biology for decades. Here, we have wondered instead whether it is possible to exploit the function for which a protein was evoluti...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7086169/ https://www.ncbi.nlm.nih.gov/pubmed/31670785 http://dx.doi.org/10.1093/molbev/msz256 |
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author | Fantini, Marco Lisi, Simonetta De Los Rios, Paolo Cattaneo, Antonino Pastore, Annalisa |
author_facet | Fantini, Marco Lisi, Simonetta De Los Rios, Paolo Cattaneo, Antonino Pastore, Annalisa |
author_sort | Fantini, Marco |
collection | PubMed |
description | Protein structure is tightly intertwined with function according to the laws of evolution. Understanding how structure determines function has been the aim of structural biology for decades. Here, we have wondered instead whether it is possible to exploit the function for which a protein was evolutionary selected to gain information on protein structure and on the landscape explored during the early stages of molecular and natural evolution. To answer to this question, we developed a new methodology, which we named CAMELS (Coupling Analysis by Molecular Evolution Library Sequencing), that is able to obtain the in vitro evolution of a protein from an artificial selection based on function. We were able to observe with CAMELS many features of the TEM-1 beta-lactamase local fold exclusively by generating and sequencing large libraries of mutational variants. We demonstrated that we can, whenever a functional phenotypic selection of a protein is available, sketch the structural and evolutionary landscape of a protein without utilizing purified proteins, collecting physical measurements, or relying on the pool of natural protein variants. |
format | Online Article Text |
id | pubmed-7086169 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-70861692020-03-26 Protein Structural Information and Evolutionary Landscape by In Vitro Evolution Fantini, Marco Lisi, Simonetta De Los Rios, Paolo Cattaneo, Antonino Pastore, Annalisa Mol Biol Evol Methods Protein structure is tightly intertwined with function according to the laws of evolution. Understanding how structure determines function has been the aim of structural biology for decades. Here, we have wondered instead whether it is possible to exploit the function for which a protein was evolutionary selected to gain information on protein structure and on the landscape explored during the early stages of molecular and natural evolution. To answer to this question, we developed a new methodology, which we named CAMELS (Coupling Analysis by Molecular Evolution Library Sequencing), that is able to obtain the in vitro evolution of a protein from an artificial selection based on function. We were able to observe with CAMELS many features of the TEM-1 beta-lactamase local fold exclusively by generating and sequencing large libraries of mutational variants. We demonstrated that we can, whenever a functional phenotypic selection of a protein is available, sketch the structural and evolutionary landscape of a protein without utilizing purified proteins, collecting physical measurements, or relying on the pool of natural protein variants. Oxford University Press 2020-04 2019-10-31 /pmc/articles/PMC7086169/ /pubmed/31670785 http://dx.doi.org/10.1093/molbev/msz256 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Fantini, Marco Lisi, Simonetta De Los Rios, Paolo Cattaneo, Antonino Pastore, Annalisa Protein Structural Information and Evolutionary Landscape by In Vitro Evolution |
title | Protein Structural Information and Evolutionary Landscape by In Vitro Evolution |
title_full | Protein Structural Information and Evolutionary Landscape by In Vitro Evolution |
title_fullStr | Protein Structural Information and Evolutionary Landscape by In Vitro Evolution |
title_full_unstemmed | Protein Structural Information and Evolutionary Landscape by In Vitro Evolution |
title_short | Protein Structural Information and Evolutionary Landscape by In Vitro Evolution |
title_sort | protein structural information and evolutionary landscape by in vitro evolution |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7086169/ https://www.ncbi.nlm.nih.gov/pubmed/31670785 http://dx.doi.org/10.1093/molbev/msz256 |
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