Cargando…

A Max-Margin Model for Predicting Residue—Base Contacts in Protein–RNA Interactions

Protein–RNA interactions (PRIs) are essential for many biological processes, so understanding aspects of the sequences and structures involved in PRIs is important for unraveling such processes. Because of the expensive and time-consuming techniques required for experimental determination of complex...

Descripción completa

Detalles Bibliográficos
Autores principales: Kashiwagi, Shunya, Sato, Kengo, Sakakibara, Yasubumi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8624843/
https://www.ncbi.nlm.nih.gov/pubmed/34833011
http://dx.doi.org/10.3390/life11111135
_version_ 1784606273386315776
author Kashiwagi, Shunya
Sato, Kengo
Sakakibara, Yasubumi
author_facet Kashiwagi, Shunya
Sato, Kengo
Sakakibara, Yasubumi
author_sort Kashiwagi, Shunya
collection PubMed
description Protein–RNA interactions (PRIs) are essential for many biological processes, so understanding aspects of the sequences and structures involved in PRIs is important for unraveling such processes. Because of the expensive and time-consuming techniques required for experimental determination of complex protein–RNA structures, various computational methods have been developed to predict PRIs. However, most of these methods focus on predicting only RNA-binding regions in proteins or only protein-binding motifs in RNA. Methods for predicting entire residue–base contacts in PRIs have not yet achieved sufficient accuracy. Furthermore, some of these methods require the identification of 3D structures or homologous sequences, which are not available for all protein and RNA sequences. Here, we propose a prediction method for predicting residue–base contacts between proteins and RNAs using only sequence information and structural information predicted from sequences. The method can be applied to any protein–RNA pair, even when rich information such as its 3D structure, is not available. In this method, residue–base contact prediction is formalized as an integer programming problem. We predict a residue–base contact map that maximizes a scoring function based on sequence-based features such as k-mers of sequences and the predicted secondary structure. The scoring function is trained using a max-margin framework from known PRIs with 3D structures. To verify our method, we conducted several computational experiments. The results suggest that our method, which is based on only sequence information, is comparable with RNA-binding residue prediction methods based on known binding data.
format Online
Article
Text
id pubmed-8624843
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-86248432021-11-27 A Max-Margin Model for Predicting Residue—Base Contacts in Protein–RNA Interactions Kashiwagi, Shunya Sato, Kengo Sakakibara, Yasubumi Life (Basel) Article Protein–RNA interactions (PRIs) are essential for many biological processes, so understanding aspects of the sequences and structures involved in PRIs is important for unraveling such processes. Because of the expensive and time-consuming techniques required for experimental determination of complex protein–RNA structures, various computational methods have been developed to predict PRIs. However, most of these methods focus on predicting only RNA-binding regions in proteins or only protein-binding motifs in RNA. Methods for predicting entire residue–base contacts in PRIs have not yet achieved sufficient accuracy. Furthermore, some of these methods require the identification of 3D structures or homologous sequences, which are not available for all protein and RNA sequences. Here, we propose a prediction method for predicting residue–base contacts between proteins and RNAs using only sequence information and structural information predicted from sequences. The method can be applied to any protein–RNA pair, even when rich information such as its 3D structure, is not available. In this method, residue–base contact prediction is formalized as an integer programming problem. We predict a residue–base contact map that maximizes a scoring function based on sequence-based features such as k-mers of sequences and the predicted secondary structure. The scoring function is trained using a max-margin framework from known PRIs with 3D structures. To verify our method, we conducted several computational experiments. The results suggest that our method, which is based on only sequence information, is comparable with RNA-binding residue prediction methods based on known binding data. MDPI 2021-10-25 /pmc/articles/PMC8624843/ /pubmed/34833011 http://dx.doi.org/10.3390/life11111135 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kashiwagi, Shunya
Sato, Kengo
Sakakibara, Yasubumi
A Max-Margin Model for Predicting Residue—Base Contacts in Protein–RNA Interactions
title A Max-Margin Model for Predicting Residue—Base Contacts in Protein–RNA Interactions
title_full A Max-Margin Model for Predicting Residue—Base Contacts in Protein–RNA Interactions
title_fullStr A Max-Margin Model for Predicting Residue—Base Contacts in Protein–RNA Interactions
title_full_unstemmed A Max-Margin Model for Predicting Residue—Base Contacts in Protein–RNA Interactions
title_short A Max-Margin Model for Predicting Residue—Base Contacts in Protein–RNA Interactions
title_sort max-margin model for predicting residue—base contacts in protein–rna interactions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8624843/
https://www.ncbi.nlm.nih.gov/pubmed/34833011
http://dx.doi.org/10.3390/life11111135
work_keys_str_mv AT kashiwagishunya amaxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions
AT satokengo amaxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions
AT sakakibarayasubumi amaxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions
AT kashiwagishunya maxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions
AT satokengo maxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions
AT sakakibarayasubumi maxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions