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SilentMutations (SIM): A tool for analyzing long-range RNA–RNA interactions in viral genomes and structured RNAs
A single nucleotide change in the coding region can alter the amino acid sequence of a protein. In consequence, natural or artificial sequence changes in viral RNAs may have various effects not only on protein stability, function and structure but also on viral replication. In recent decades, severa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier B.V.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7172452/ https://www.ncbi.nlm.nih.gov/pubmed/30439394 http://dx.doi.org/10.1016/j.virusres.2018.11.005 |
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author | Desirò, Daniel Hölzer, Martin Ibrahim, Bashar Marz, Manja |
author_facet | Desirò, Daniel Hölzer, Martin Ibrahim, Bashar Marz, Manja |
author_sort | Desirò, Daniel |
collection | PubMed |
description | A single nucleotide change in the coding region can alter the amino acid sequence of a protein. In consequence, natural or artificial sequence changes in viral RNAs may have various effects not only on protein stability, function and structure but also on viral replication. In recent decades, several tools have been developed to predict the effect of mutations in structured RNAs such as viral genomes or non-coding RNAs. Some tools use multiple point mutations and also take coding regions into account. However, none of these tools was designed to specifically simulate the effect of mutations on viral long-range interactions. Here, we developed SilentMutations (SIM), an easy-to-use tool to analyze the effect of multiple point mutations on the secondary structures of two interacting viral RNAs. The tool can simulate disruptive and compensatory mutants of two interacting single-stranded RNAs. This allows a fast and accurate assessment of key regions potentially involved in functional long-range RNA–RNA interactions and will eventually help virologists and RNA-experts to design appropriate experiments. SIM only requires two interacting single-stranded RNA regions as input. The output is a plain text file containing the most promising mutants and a graphical representation of all interactions. We applied our tool on two experimentally validated influenza A virus and hepatitis C virus interactions and we were able to predict potential double mutants for in vitro validation experiments. The source code and documentation of SIM are freely available at github.com/desiro/silentMutations. |
format | Online Article Text |
id | pubmed-7172452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71724522020-04-22 SilentMutations (SIM): A tool for analyzing long-range RNA–RNA interactions in viral genomes and structured RNAs Desirò, Daniel Hölzer, Martin Ibrahim, Bashar Marz, Manja Virus Res Article A single nucleotide change in the coding region can alter the amino acid sequence of a protein. In consequence, natural or artificial sequence changes in viral RNAs may have various effects not only on protein stability, function and structure but also on viral replication. In recent decades, several tools have been developed to predict the effect of mutations in structured RNAs such as viral genomes or non-coding RNAs. Some tools use multiple point mutations and also take coding regions into account. However, none of these tools was designed to specifically simulate the effect of mutations on viral long-range interactions. Here, we developed SilentMutations (SIM), an easy-to-use tool to analyze the effect of multiple point mutations on the secondary structures of two interacting viral RNAs. The tool can simulate disruptive and compensatory mutants of two interacting single-stranded RNAs. This allows a fast and accurate assessment of key regions potentially involved in functional long-range RNA–RNA interactions and will eventually help virologists and RNA-experts to design appropriate experiments. SIM only requires two interacting single-stranded RNA regions as input. The output is a plain text file containing the most promising mutants and a graphical representation of all interactions. We applied our tool on two experimentally validated influenza A virus and hepatitis C virus interactions and we were able to predict potential double mutants for in vitro validation experiments. The source code and documentation of SIM are freely available at github.com/desiro/silentMutations. Published by Elsevier B.V. 2019-01-15 2018-11-12 /pmc/articles/PMC7172452/ /pubmed/30439394 http://dx.doi.org/10.1016/j.virusres.2018.11.005 Text en © 2018 Published by Elsevier B.V. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Desirò, Daniel Hölzer, Martin Ibrahim, Bashar Marz, Manja SilentMutations (SIM): A tool for analyzing long-range RNA–RNA interactions in viral genomes and structured RNAs |
title | SilentMutations (SIM): A tool for analyzing long-range RNA–RNA interactions in viral genomes and structured RNAs |
title_full | SilentMutations (SIM): A tool for analyzing long-range RNA–RNA interactions in viral genomes and structured RNAs |
title_fullStr | SilentMutations (SIM): A tool for analyzing long-range RNA–RNA interactions in viral genomes and structured RNAs |
title_full_unstemmed | SilentMutations (SIM): A tool for analyzing long-range RNA–RNA interactions in viral genomes and structured RNAs |
title_short | SilentMutations (SIM): A tool for analyzing long-range RNA–RNA interactions in viral genomes and structured RNAs |
title_sort | silentmutations (sim): a tool for analyzing long-range rna–rna interactions in viral genomes and structured rnas |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7172452/ https://www.ncbi.nlm.nih.gov/pubmed/30439394 http://dx.doi.org/10.1016/j.virusres.2018.11.005 |
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