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

Guardado en:

Detalles Bibliográficos
Autores principales:	Shunya Kashiwagi, Kengo Sato, Yasubumi Sakakibara
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	protein–RNA interaction RNA secondary structure structured support vector machine Science Q
Acceso en línea:	https://doaj.org/article/6bfbdfd3f4b145c8a868ca278aa2370e
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:6bfbdfd3f4b145c8a868ca278aa2370e
record_format	dspace
spelling	oai:doaj.org-article:6bfbdfd3f4b145c8a868ca278aa2370e2021-11-25T18:10:33ZA Max-Margin Model for Predicting Residue—Base Contacts in Protein–RNA Interactions10.3390/life111111352075-1729https://doaj.org/article/6bfbdfd3f4b145c8a868ca278aa2370e2021-10-01T00:00:00Zhttps://www.mdpi.com/2075-1729/11/11/1135https://doaj.org/toc/2075-1729Protein–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 <i>k</i>-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.Shunya KashiwagiKengo SatoYasubumi SakakibaraMDPI AGarticleprotein–RNA interactionRNA secondary structurestructured support vector machineScienceQENLife, Vol 11, Iss 1135, p 1135 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	protein–RNA interaction RNA secondary structure structured support vector machine Science Q
spellingShingle	protein–RNA interaction RNA secondary structure structured support vector machine Science Q Shunya Kashiwagi Kengo Sato Yasubumi Sakakibara A Max-Margin Model for Predicting Residue—Base Contacts in Protein–RNA Interactions
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 <i>k</i>-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	article
author	Shunya Kashiwagi Kengo Sato Yasubumi Sakakibara
author_facet	Shunya Kashiwagi Kengo Sato Yasubumi Sakakibara
author_sort	Shunya Kashiwagi
title	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_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_sort	max-margin model for predicting residue—base contacts in protein–rna interactions
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/6bfbdfd3f4b145c8a868ca278aa2370e
work_keys_str_mv	AT shunyakashiwagi amaxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions AT kengosato amaxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions AT yasubumisakakibara amaxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions AT shunyakashiwagi maxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions AT kengosato maxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions AT yasubumisakakibara maxmarginmodelforpredictingresiduebasecontactsinproteinrnainteractions
_version_	1718411501457375232

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

Ejemplares similares