PuSH - Publikationsserver des Helmholtz Zentrums München

Roca-Martínez, J.* ; Dhondge, H.* ; Sattler, M. ; Vranken, W.F.*

Deciphering the RRM-RNA recognition code: A computational analysis.

PLoS Comput. Biol. 19:e1010859 (2023)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
RNA recognition motifs (RRM) are the most prevalent class of RNA binding domains in eukaryotes. 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.
Altmetric
Weitere Metriken?
[➜Einloggen]
Zusatzinfos bearbeiten [➜Einloggen]
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Protein Secondary Structure; Knowledge-based Potentials; Binding Proteins; Crystal-structure; Gor Method; Sequence; Motifs; Dna; Specificities; Translation
ISSN (print) / ISBN 1553-734X
e-ISSN 1553-7358
Zeitschrift PLoS Computational Biology
Quellenangaben Band: 19, Heft: 1, Seiten: , Artikelnummer: e1010859 Supplement: ,
Verlag Public Library of Science (PLoS)
Verlagsort 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Structural Biology (STB)
Förderungen European Union