In:
PLOS Computational Biology, Public Library of Science (PLoS), Vol. 19, No. 1 ( 2023-1-23), p. e1010859-
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
1553-7358
DOI:
10.1371/journal.pcbi.1010859
DOI:
10.1371/journal.pcbi.1010859.g001
DOI:
10.1371/journal.pcbi.1010859.g002
DOI:
10.1371/journal.pcbi.1010859.g003
DOI:
10.1371/journal.pcbi.1010859.g004
DOI:
10.1371/journal.pcbi.1010859.g005
DOI:
10.1371/journal.pcbi.1010859.g006
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10.1371/journal.pcbi.1010859.g007
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10.1371/journal.pcbi.1010859.g008
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10.1371/journal.pcbi.1010859.g009
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10.1371/journal.pcbi.1010859.g010
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10.1371/journal.pcbi.1010859.g011
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10.1371/journal.pcbi.1010859.t001
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10.1371/journal.pcbi.1010859.s001
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10.1371/journal.pcbi.1010859.s002
DOI:
10.1371/journal.pcbi.1010859.s003
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10.1371/journal.pcbi.1010859.s004
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10.1371/journal.pcbi.1010859.s005
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10.1371/journal.pcbi.1010859.s006
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10.1371/journal.pcbi.1010859.s007
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10.1371/journal.pcbi.1010859.s008
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10.1371/journal.pcbi.1010859.s009
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10.1371/journal.pcbi.1010859.s010
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10.1371/journal.pcbi.1010859.s011
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10.1371/journal.pcbi.1010859.s012
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10.1371/journal.pcbi.1010859.s013
DOI:
10.1371/journal.pcbi.1010859.s014
DOI:
10.1371/journal.pcbi.1010859.s015
DOI:
10.1371/journal.pcbi.1010859.s016
DOI:
10.1371/journal.pcbi.1010859.s017
DOI:
10.1371/journal.pcbi.1010859.s018
DOI:
10.1371/journal.pcbi.1010859.s019
DOI:
10.1371/journal.pcbi.1010859.r001
DOI:
10.1371/journal.pcbi.1010859.r002
DOI:
10.1371/journal.pcbi.1010859.r003
DOI:
10.1371/journal.pcbi.1010859.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2023
detail.hit.zdb_id:
2193340-6
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