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Evolution of Protein Functional Annotation: Text Mining Study

Within the Human Proteome Project initiative framework for creating functional annotations of uPE1 proteins, the neXt-CP50 Challenge was launched in 2018. In analogy with the missing-protein challenge, each command deciphers the functional features of the proteins in the chromosome-centric mode. How...

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Autores principales: Ilgisonis, Ekaterina V., Pogodin, Pavel V., Kiseleva, Olga I., Tarbeeva, Svetlana N., Ponomarenko, Elena A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8952229/
https://www.ncbi.nlm.nih.gov/pubmed/35330478
http://dx.doi.org/10.3390/jpm12030479
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author Ilgisonis, Ekaterina V.
Pogodin, Pavel V.
Kiseleva, Olga I.
Tarbeeva, Svetlana N.
Ponomarenko, Elena A.
author_facet Ilgisonis, Ekaterina V.
Pogodin, Pavel V.
Kiseleva, Olga I.
Tarbeeva, Svetlana N.
Ponomarenko, Elena A.
author_sort Ilgisonis, Ekaterina V.
collection PubMed
description Within the Human Proteome Project initiative framework for creating functional annotations of uPE1 proteins, the neXt-CP50 Challenge was launched in 2018. In analogy with the missing-protein challenge, each command deciphers the functional features of the proteins in the chromosome-centric mode. However, the neXt-CP50 Challenge is more complicated than the missing-protein challenge: the approaches and methods for solving the problem are clear, but neither the concept of protein function nor specific experimental and/or bioinformatics protocols have been standardized to address it. We proposed using a retrospective analysis of the key HPP repository, the neXtProt database, to identify the most frequently used experimental and bioinformatic methods for analyzing protein functions, and the dynamics of accumulation of functional annotations. It has been shown that the dynamics of the increase in the number of proteins with known functions are greater than the progress made in the experimental confirmation of the existence of questionable proteins in the framework of the missing-protein challenge. At the same time, the functional annotation is based on the guilty-by-association postulate, according to which, based on large-scale experiments on API-MS and Y2H, proteins with unknown functions are most likely mapped through “handshakes” to biochemical processes.
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spelling pubmed-89522292022-03-26 Evolution of Protein Functional Annotation: Text Mining Study Ilgisonis, Ekaterina V. Pogodin, Pavel V. Kiseleva, Olga I. Tarbeeva, Svetlana N. Ponomarenko, Elena A. J Pers Med Article Within the Human Proteome Project initiative framework for creating functional annotations of uPE1 proteins, the neXt-CP50 Challenge was launched in 2018. In analogy with the missing-protein challenge, each command deciphers the functional features of the proteins in the chromosome-centric mode. However, the neXt-CP50 Challenge is more complicated than the missing-protein challenge: the approaches and methods for solving the problem are clear, but neither the concept of protein function nor specific experimental and/or bioinformatics protocols have been standardized to address it. We proposed using a retrospective analysis of the key HPP repository, the neXtProt database, to identify the most frequently used experimental and bioinformatic methods for analyzing protein functions, and the dynamics of accumulation of functional annotations. It has been shown that the dynamics of the increase in the number of proteins with known functions are greater than the progress made in the experimental confirmation of the existence of questionable proteins in the framework of the missing-protein challenge. At the same time, the functional annotation is based on the guilty-by-association postulate, according to which, based on large-scale experiments on API-MS and Y2H, proteins with unknown functions are most likely mapped through “handshakes” to biochemical processes. MDPI 2022-03-16 /pmc/articles/PMC8952229/ /pubmed/35330478 http://dx.doi.org/10.3390/jpm12030479 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ilgisonis, Ekaterina V.
Pogodin, Pavel V.
Kiseleva, Olga I.
Tarbeeva, Svetlana N.
Ponomarenko, Elena A.
Evolution of Protein Functional Annotation: Text Mining Study
title Evolution of Protein Functional Annotation: Text Mining Study
title_full Evolution of Protein Functional Annotation: Text Mining Study
title_fullStr Evolution of Protein Functional Annotation: Text Mining Study
title_full_unstemmed Evolution of Protein Functional Annotation: Text Mining Study
title_short Evolution of Protein Functional Annotation: Text Mining Study
title_sort evolution of protein functional annotation: text mining study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8952229/
https://www.ncbi.nlm.nih.gov/pubmed/35330478
http://dx.doi.org/10.3390/jpm12030479
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