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Deciphering the RRM-RNA recognition code: A computational analysis
RNA recognition motifs (RRM) are the most prevalent class of RNA binding domains in eucaryotes. Their RNA binding preferences have been investigated for almost two decades, and even though some RRM domains are now very well described, their RNA recognition code has remained elusive. An increasing nu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894542/ https://www.ncbi.nlm.nih.gov/pubmed/36689472 http://dx.doi.org/10.1371/journal.pcbi.1010859 |
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author | Roca-Martínez, Joel Dhondge, Hrishikesh Sattler, Michael Vranken, Wim F. |
author_facet | Roca-Martínez, Joel Dhondge, Hrishikesh Sattler, Michael Vranken, Wim F. |
author_sort | Roca-Martínez, Joel |
collection | PubMed |
description | RNA recognition motifs (RRM) are the most prevalent class of RNA binding domains in eucaryotes. Their RNA binding preferences have been investigated for almost two decades, and even though some RRM domains are now very well described, their RNA recognition code has remained elusive. An increasing number of experimental structures of RRM-RNA complexes has become available in recent years. Here, we perform an in-depth computational analysis to derive an RNA recognition code for canonical RRMs. We present and validate a computational scoring method to estimate the binding between an RRM and a single stranded RNA, based on structural data from a carefully curated multiple sequence alignment, which can predict RRM binding RNA sequence motifs based on the RRM protein sequence. Given the importance and prevalence of RRMs in humans and other species, this tool could help design RNA binding motifs with uses in medical or synthetic biology applications, leading towards the de novo design of RRMs with specific RNA recognition. |
format | Online Article Text |
id | pubmed-9894542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-98945422023-02-03 Deciphering the RRM-RNA recognition code: A computational analysis Roca-Martínez, Joel Dhondge, Hrishikesh Sattler, Michael Vranken, Wim F. PLoS Comput Biol Research Article RNA recognition motifs (RRM) are the most prevalent class of RNA binding domains in eucaryotes. Their RNA binding preferences have been investigated for almost two decades, and even though some RRM domains are now very well described, their RNA recognition code has remained elusive. An increasing number of experimental structures of RRM-RNA complexes has become available in recent years. Here, we perform an in-depth computational analysis to derive an RNA recognition code for canonical RRMs. We present and validate a computational scoring method to estimate the binding between an RRM and a single stranded RNA, based on structural data from a carefully curated multiple sequence alignment, which can predict RRM binding RNA sequence motifs based on the RRM protein sequence. Given the importance and prevalence of RRMs in humans and other species, this tool could help design RNA binding motifs with uses in medical or synthetic biology applications, leading towards the de novo design of RRMs with specific RNA recognition. Public Library of Science 2023-01-23 /pmc/articles/PMC9894542/ /pubmed/36689472 http://dx.doi.org/10.1371/journal.pcbi.1010859 Text en © 2023 Roca-Martínez et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Roca-Martínez, Joel Dhondge, Hrishikesh Sattler, Michael Vranken, Wim F. Deciphering the RRM-RNA recognition code: A computational analysis |
title | Deciphering the RRM-RNA recognition code: A computational analysis |
title_full | Deciphering the RRM-RNA recognition code: A computational analysis |
title_fullStr | Deciphering the RRM-RNA recognition code: A computational analysis |
title_full_unstemmed | Deciphering the RRM-RNA recognition code: A computational analysis |
title_short | Deciphering the RRM-RNA recognition code: A computational analysis |
title_sort | deciphering the rrm-rna recognition code: a computational analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894542/ https://www.ncbi.nlm.nih.gov/pubmed/36689472 http://dx.doi.org/10.1371/journal.pcbi.1010859 |
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