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Computational tools to study RNA-protein complexes
RNA is the key player in many cellular processes such as signal transduction, replication, transport, cell division, transcription, and translation. These diverse functions are accomplished through interactions of RNA with proteins. However, protein–RNA interactions are still poorly derstood in cont...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585174/ https://www.ncbi.nlm.nih.gov/pubmed/36275618 http://dx.doi.org/10.3389/fmolb.2022.954926 |
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author | Bheemireddy, Sneha Sandhya, Sankaran Srinivasan, Narayanaswamy Sowdhamini, Ramanathan |
author_facet | Bheemireddy, Sneha Sandhya, Sankaran Srinivasan, Narayanaswamy Sowdhamini, Ramanathan |
author_sort | Bheemireddy, Sneha |
collection | PubMed |
description | RNA is the key player in many cellular processes such as signal transduction, replication, transport, cell division, transcription, and translation. These diverse functions are accomplished through interactions of RNA with proteins. However, protein–RNA interactions are still poorly derstood in contrast to protein–protein and protein–DNA interactions. This knowledge gap can be attributed to the limited availability of protein-RNA structures along with the experimental difficulties in studying these complexes. Recent progress in computational resources has expanded the number of tools available for studying protein-RNA interactions at various molecular levels. These include tools for predicting interacting residues from primary sequences, modelling of protein-RNA complexes, predicting hotspots in these complexes and insights into derstanding in the dynamics of their interactions. Each of these tools has its strengths and limitations, which makes it significant to select an optimal approach for the question of interest. Here we present a mini review of computational tools to study different aspects of protein-RNA interactions, with focus on overall application, development of the field and the future perspectives. |
format | Online Article Text |
id | pubmed-9585174 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95851742022-10-22 Computational tools to study RNA-protein complexes Bheemireddy, Sneha Sandhya, Sankaran Srinivasan, Narayanaswamy Sowdhamini, Ramanathan Front Mol Biosci Molecular Biosciences RNA is the key player in many cellular processes such as signal transduction, replication, transport, cell division, transcription, and translation. These diverse functions are accomplished through interactions of RNA with proteins. However, protein–RNA interactions are still poorly derstood in contrast to protein–protein and protein–DNA interactions. This knowledge gap can be attributed to the limited availability of protein-RNA structures along with the experimental difficulties in studying these complexes. Recent progress in computational resources has expanded the number of tools available for studying protein-RNA interactions at various molecular levels. These include tools for predicting interacting residues from primary sequences, modelling of protein-RNA complexes, predicting hotspots in these complexes and insights into derstanding in the dynamics of their interactions. Each of these tools has its strengths and limitations, which makes it significant to select an optimal approach for the question of interest. Here we present a mini review of computational tools to study different aspects of protein-RNA interactions, with focus on overall application, development of the field and the future perspectives. Frontiers Media S.A. 2022-10-07 /pmc/articles/PMC9585174/ /pubmed/36275618 http://dx.doi.org/10.3389/fmolb.2022.954926 Text en Copyright © 2022 Bheemireddy, Sandhya, Srinivasan and Sowdhamini. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed der the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Molecular Biosciences Bheemireddy, Sneha Sandhya, Sankaran Srinivasan, Narayanaswamy Sowdhamini, Ramanathan Computational tools to study RNA-protein complexes |
title | Computational tools to study RNA-protein complexes |
title_full | Computational tools to study RNA-protein complexes |
title_fullStr | Computational tools to study RNA-protein complexes |
title_full_unstemmed | Computational tools to study RNA-protein complexes |
title_short | Computational tools to study RNA-protein complexes |
title_sort | computational tools to study rna-protein complexes |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585174/ https://www.ncbi.nlm.nih.gov/pubmed/36275618 http://dx.doi.org/10.3389/fmolb.2022.954926 |
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