Cargando…

Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study

The RNA recognition motif (RRM) is the most common RNA binding domain across eukaryotic proteins. It is therefore of great value to engineer its specificity to target RNAs of arbitrary sequence. This was recently achieved for the RRM in Rbfox protein, where four mutations R118D, E147R, N151S, and E1...

Descripción completa

Detalles Bibliográficos
Autores principales: Bochicchio, Anna, Krepl, Miroslav, Yang, Fan, Varani, Gabriele, Sponer, Jiri, Carloni, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6307825/
https://www.ncbi.nlm.nih.gov/pubmed/30521520
http://dx.doi.org/10.1371/journal.pcbi.1006642
_version_ 1783383077257478144
author Bochicchio, Anna
Krepl, Miroslav
Yang, Fan
Varani, Gabriele
Sponer, Jiri
Carloni, Paolo
author_facet Bochicchio, Anna
Krepl, Miroslav
Yang, Fan
Varani, Gabriele
Sponer, Jiri
Carloni, Paolo
author_sort Bochicchio, Anna
collection PubMed
description The RNA recognition motif (RRM) is the most common RNA binding domain across eukaryotic proteins. It is therefore of great value to engineer its specificity to target RNAs of arbitrary sequence. This was recently achieved for the RRM in Rbfox protein, where four mutations R118D, E147R, N151S, and E152T were designed to target the precursor to the oncogenic miRNA 21. Here, we used a variety of molecular dynamics-based approaches to predict specific interactions at the binding interface. Overall, we have run approximately 50 microseconds of enhanced sampling and plain molecular dynamics simulations on the engineered complex as well as on the wild-type Rbfox·pre-miRNA 20b from which the mutated systems were designed. Comparison with the available NMR data on the wild type molecules (protein, RNA, and their complex) served to establish the accuracy of the calculations. Free energy calculations suggest that further improvements in affinity and selectivity are achieved by the S151T replacement.
format Online
Article
Text
id pubmed-6307825
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-63078252019-01-08 Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study Bochicchio, Anna Krepl, Miroslav Yang, Fan Varani, Gabriele Sponer, Jiri Carloni, Paolo PLoS Comput Biol Research Article The RNA recognition motif (RRM) is the most common RNA binding domain across eukaryotic proteins. It is therefore of great value to engineer its specificity to target RNAs of arbitrary sequence. This was recently achieved for the RRM in Rbfox protein, where four mutations R118D, E147R, N151S, and E152T were designed to target the precursor to the oncogenic miRNA 21. Here, we used a variety of molecular dynamics-based approaches to predict specific interactions at the binding interface. Overall, we have run approximately 50 microseconds of enhanced sampling and plain molecular dynamics simulations on the engineered complex as well as on the wild-type Rbfox·pre-miRNA 20b from which the mutated systems were designed. Comparison with the available NMR data on the wild type molecules (protein, RNA, and their complex) served to establish the accuracy of the calculations. Free energy calculations suggest that further improvements in affinity and selectivity are achieved by the S151T replacement. Public Library of Science 2018-12-06 /pmc/articles/PMC6307825/ /pubmed/30521520 http://dx.doi.org/10.1371/journal.pcbi.1006642 Text en © 2018 Bochicchio et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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
Bochicchio, Anna
Krepl, Miroslav
Yang, Fan
Varani, Gabriele
Sponer, Jiri
Carloni, Paolo
Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study
title Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study
title_full Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study
title_fullStr Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study
title_full_unstemmed Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study
title_short Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study
title_sort molecular basis for the increased affinity of an rna recognition motif with re-engineered specificity: a molecular dynamics and enhanced sampling simulations study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6307825/
https://www.ncbi.nlm.nih.gov/pubmed/30521520
http://dx.doi.org/10.1371/journal.pcbi.1006642
work_keys_str_mv AT bochicchioanna molecularbasisfortheincreasedaffinityofanrnarecognitionmotifwithreengineeredspecificityamoleculardynamicsandenhancedsamplingsimulationsstudy
AT kreplmiroslav molecularbasisfortheincreasedaffinityofanrnarecognitionmotifwithreengineeredspecificityamoleculardynamicsandenhancedsamplingsimulationsstudy
AT yangfan molecularbasisfortheincreasedaffinityofanrnarecognitionmotifwithreengineeredspecificityamoleculardynamicsandenhancedsamplingsimulationsstudy
AT varanigabriele molecularbasisfortheincreasedaffinityofanrnarecognitionmotifwithreengineeredspecificityamoleculardynamicsandenhancedsamplingsimulationsstudy
AT sponerjiri molecularbasisfortheincreasedaffinityofanrnarecognitionmotifwithreengineeredspecificityamoleculardynamicsandenhancedsamplingsimulationsstudy
AT carlonipaolo molecularbasisfortheincreasedaffinityofanrnarecognitionmotifwithreengineeredspecificityamoleculardynamicsandenhancedsamplingsimulationsstudy