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Computational identification of RNA functional determinants by three-dimensional quantitative structure–activity relationships
Anti-infection drugs target vital functions of infectious agents, including their ribosome and other essential non-coding RNAs. One of the reasons infectious agents become resistant to drugs is due to mutations that eliminate drug-binding affinity while maintaining vital elements. Identifying these...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4176186/ https://www.ncbi.nlm.nih.gov/pubmed/25200082 http://dx.doi.org/10.1093/nar/gku816 |
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author | Blanchet, Marc-Frédérick St-Onge, Karine Lisi, Véronique Robitaille, Julie Hamel, Sylvie Major, François |
author_facet | Blanchet, Marc-Frédérick St-Onge, Karine Lisi, Véronique Robitaille, Julie Hamel, Sylvie Major, François |
author_sort | Blanchet, Marc-Frédérick |
collection | PubMed |
description | Anti-infection drugs target vital functions of infectious agents, including their ribosome and other essential non-coding RNAs. One of the reasons infectious agents become resistant to drugs is due to mutations that eliminate drug-binding affinity while maintaining vital elements. Identifying these elements is based on the determination of viable and lethal mutants and associated structures. However, determining the structure of enough mutants at high resolution is not always possible. Here, we introduce a new computational method, MC-3DQSAR, to determine the vital elements of target RNA structure from mutagenesis and available high-resolution data. We applied the method to further characterize the structural determinants of the bacterial 23S ribosomal RNA sarcin–ricin loop (SRL), as well as those of the lead-activated and hammerhead ribozymes. The method was accurate in confirming experimentally determined essential structural elements and predicting the viability of new SRL variants, which were either observed in bacteria or validated in bacterial growth assays. Our results indicate that MC-3DQSAR could be used systematically to evaluate the drug-target potentials of any RNA sites using current high-resolution structural data. |
format | Online Article Text |
id | pubmed-4176186 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-41761862014-12-01 Computational identification of RNA functional determinants by three-dimensional quantitative structure–activity relationships Blanchet, Marc-Frédérick St-Onge, Karine Lisi, Véronique Robitaille, Julie Hamel, Sylvie Major, François Nucleic Acids Res Structural Biology Anti-infection drugs target vital functions of infectious agents, including their ribosome and other essential non-coding RNAs. One of the reasons infectious agents become resistant to drugs is due to mutations that eliminate drug-binding affinity while maintaining vital elements. Identifying these elements is based on the determination of viable and lethal mutants and associated structures. However, determining the structure of enough mutants at high resolution is not always possible. Here, we introduce a new computational method, MC-3DQSAR, to determine the vital elements of target RNA structure from mutagenesis and available high-resolution data. We applied the method to further characterize the structural determinants of the bacterial 23S ribosomal RNA sarcin–ricin loop (SRL), as well as those of the lead-activated and hammerhead ribozymes. The method was accurate in confirming experimentally determined essential structural elements and predicting the viability of new SRL variants, which were either observed in bacteria or validated in bacterial growth assays. Our results indicate that MC-3DQSAR could be used systematically to evaluate the drug-target potentials of any RNA sites using current high-resolution structural data. Oxford University Press 2014-09-29 2014-09-08 /pmc/articles/PMC4176186/ /pubmed/25200082 http://dx.doi.org/10.1093/nar/gku816 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Structural Biology Blanchet, Marc-Frédérick St-Onge, Karine Lisi, Véronique Robitaille, Julie Hamel, Sylvie Major, François Computational identification of RNA functional determinants by three-dimensional quantitative structure–activity relationships |
title | Computational identification of RNA functional determinants by three-dimensional quantitative structure–activity relationships |
title_full | Computational identification of RNA functional determinants by three-dimensional quantitative structure–activity relationships |
title_fullStr | Computational identification of RNA functional determinants by three-dimensional quantitative structure–activity relationships |
title_full_unstemmed | Computational identification of RNA functional determinants by three-dimensional quantitative structure–activity relationships |
title_short | Computational identification of RNA functional determinants by three-dimensional quantitative structure–activity relationships |
title_sort | computational identification of rna functional determinants by three-dimensional quantitative structure–activity relationships |
topic | Structural Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4176186/ https://www.ncbi.nlm.nih.gov/pubmed/25200082 http://dx.doi.org/10.1093/nar/gku816 |
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