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RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families
MOTIVATION: The 3D structures of RNA play a critical role in understanding their functionalities. There exist several computational methods to study RNA 3D structures by identifying structural motifs and categorizing them into several motif families based on their structures. Although the number of...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10311341/ https://www.ncbi.nlm.nih.gov/pubmed/37387191 http://dx.doi.org/10.1093/bioinformatics/btad223 |
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author | Rahaman, Md Mahfuzur Khan, Nabila Shahnaz Zhang, Shaojie |
author_facet | Rahaman, Md Mahfuzur Khan, Nabila Shahnaz Zhang, Shaojie |
author_sort | Rahaman, Md Mahfuzur |
collection | PubMed |
description | MOTIVATION: The 3D structures of RNA play a critical role in understanding their functionalities. There exist several computational methods to study RNA 3D structures by identifying structural motifs and categorizing them into several motif families based on their structures. Although the number of such motif families is not limited, a few of them are well-studied. Out of these structural motif families, there exist several families that are visually similar or very close in structure, even with different base interactions. Alternatively, some motif families share a set of base interactions but maintain variation in their 3D formations. These similarities among different motif families, if known, can provide a better insight into the RNA 3D structural motifs as well as their characteristic functions in cell biology. RESULTS: In this work, we proposed a method, RNAMotifComp, that analyzes the instances of well-known structural motif families and establishes a relational graph among them. We also have designed a method to visualize the relational graph where the families are shown as nodes and their similarity information is represented as edges. We validated our discovered correlations of the motif families using RNAMotifContrast. Additionally, we used a basic Naïve Bayes classifier to show the importance of RNAMotifComp. The relational analysis explains the functional analogies of divergent motif families and illustrates the situations where the motifs of disparate families are predicted to be of the same family. AVAILABILITY AND IMPLEMENTATION: Source code publicly available at https://github.com/ucfcbb/RNAMotifFamilySimilarity. |
format | Online Article Text |
id | pubmed-10311341 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-103113412023-07-01 RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families Rahaman, Md Mahfuzur Khan, Nabila Shahnaz Zhang, Shaojie Bioinformatics Macromolecular Sequence, Structure, and Function MOTIVATION: The 3D structures of RNA play a critical role in understanding their functionalities. There exist several computational methods to study RNA 3D structures by identifying structural motifs and categorizing them into several motif families based on their structures. Although the number of such motif families is not limited, a few of them are well-studied. Out of these structural motif families, there exist several families that are visually similar or very close in structure, even with different base interactions. Alternatively, some motif families share a set of base interactions but maintain variation in their 3D formations. These similarities among different motif families, if known, can provide a better insight into the RNA 3D structural motifs as well as their characteristic functions in cell biology. RESULTS: In this work, we proposed a method, RNAMotifComp, that analyzes the instances of well-known structural motif families and establishes a relational graph among them. We also have designed a method to visualize the relational graph where the families are shown as nodes and their similarity information is represented as edges. We validated our discovered correlations of the motif families using RNAMotifContrast. Additionally, we used a basic Naïve Bayes classifier to show the importance of RNAMotifComp. The relational analysis explains the functional analogies of divergent motif families and illustrates the situations where the motifs of disparate families are predicted to be of the same family. AVAILABILITY AND IMPLEMENTATION: Source code publicly available at https://github.com/ucfcbb/RNAMotifFamilySimilarity. Oxford University Press 2023-06-30 /pmc/articles/PMC10311341/ /pubmed/37387191 http://dx.doi.org/10.1093/bioinformatics/btad223 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Macromolecular Sequence, Structure, and Function Rahaman, Md Mahfuzur Khan, Nabila Shahnaz Zhang, Shaojie RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families |
title | RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families |
title_full | RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families |
title_fullStr | RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families |
title_full_unstemmed | RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families |
title_short | RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families |
title_sort | rnamotifcomp: a comprehensive method to analyze and identify structurally similar rna motif families |
topic | Macromolecular Sequence, Structure, and Function |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10311341/ https://www.ncbi.nlm.nih.gov/pubmed/37387191 http://dx.doi.org/10.1093/bioinformatics/btad223 |
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