Revenant: a database of resurrected proteins.


Journal

Database : the journal of biological databases and curation
ISSN: 1758-0463
Titre abrégé: Database (Oxford)
Pays: England
ID NLM: 101517697

Informations de publication

Date de publication:
01 01 2020
Historique:
received: 03 07 2019
revised: 06 03 2020
accepted: 31 03 2020
entrez: 14 5 2020
pubmed: 14 5 2020
medline: 6 7 2021
Statut: ppublish

Résumé

Revenant is a database of resurrected proteins coming from extinct organisms. Currently, it contains a manually curated collection of 84 resurrected proteins derived from bibliographic data. Each protein is extensively annotated, including structural, biochemical and biophysical information. Revenant contains a browse capability designed as a timeline from where the different proteins can be accessed. The oldest Revenant entries are between 4200 and 3500 million years ago, while the younger entries are between 8.8 and 6.3 million years ago. These proteins have been resurrected using computational tools called ancestral sequence reconstruction techniques combined with wet-laboratory synthesis and expression. Resurrected proteins are commonly used, with a noticeable increase during the past years, to explore and test different evolutionary hypotheses such as protein stability, to explore the origin of new functions, to get biochemical insights into past metabolisms and to explore specificity and promiscuous behaviour of ancient proteins.

Identifiants

pubmed: 32400867
pii: 5828294
doi: 10.1093/database/baaa031
pmc: PMC7218706
pii:
doi:

Substances chimiques

Proteins 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press.

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Auteurs

Matias Sebastian Carletti (MS)

Departamento de Ciencia y Tecnología, CONICET, Universidad Nacional de Quilmes, Roque Saenz Peña 182, Bernal, B1876BXD, Buenos Aires, Argentina.

Alexander Miguel Monzon (AM)

Departamento de Ciencia y Tecnología, CONICET, Universidad Nacional de Quilmes, Roque Saenz Peña 182, Bernal, B1876BXD, Buenos Aires, Argentina.
Department of Biomedical Sciences, University of Padova, Viale G. Colombo 3, Padova, I-35131, Padova, Italy.

Emilio Garcia-Rios (E)

Departamento de Ingeniería, Pontificia Universidad Católica del Perú, Lima, Perú.

Guillermo Benitez (G)

Departamento de Ciencia y Tecnología, CONICET, Universidad Nacional de Quilmes, Roque Saenz Peña 182, Bernal, B1876BXD, Buenos Aires, Argentina.

Layla Hirsh (L)

Departamento de Ingeniería, Pontificia Universidad Católica del Perú, Lima, Perú.

Maria Silvina Fornasari (MS)

Departamento de Ciencia y Tecnología, CONICET, Universidad Nacional de Quilmes, Roque Saenz Peña 182, Bernal, B1876BXD, Buenos Aires, Argentina.

Gustavo Parisi (G)

Departamento de Ciencia y Tecnología, CONICET, Universidad Nacional de Quilmes, Roque Saenz Peña 182, Bernal, B1876BXD, Buenos Aires, Argentina.

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Classifications MeSH