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How AlphaFold2 Predicts Conditionally Folding Regions Annotated in an Intrinsically Disordered Protein Database, IDEAL

SIMPLE SUMMARY: Intrinsically disordered regions (IDRs) in intrinsically disordered proteins (IDPs) play important roles in various biological processes by providing protein binding regions. The regions can adopt local structures upon binding to their interaction partners. An IDP database—IDEAL—has...

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Autores principales: Anbo, Hiroto, Sakuma, Koya, Fukuchi, Satoshi, Ota, Motonori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9952413/
https://www.ncbi.nlm.nih.gov/pubmed/36829461
http://dx.doi.org/10.3390/biology12020182
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author Anbo, Hiroto
Sakuma, Koya
Fukuchi, Satoshi
Ota, Motonori
author_facet Anbo, Hiroto
Sakuma, Koya
Fukuchi, Satoshi
Ota, Motonori
author_sort Anbo, Hiroto
collection PubMed
description SIMPLE SUMMARY: Intrinsically disordered regions (IDRs) in intrinsically disordered proteins (IDPs) play important roles in various biological processes by providing protein binding regions. The regions can adopt local structures upon binding to their interaction partners. An IDP database—IDEAL—has collected these conditionally binding regions as Protean Segments (ProSs). A recently developed program, called AlphaFold2 (AF2), accurately predicts structural domains in proteins. Because ProSs have the bilateral characteristics of IDRs and ordered regions, assessing AF2 models corresponding to ProSs is worthwhile. We classified ProSs into three classes: the excellent class agrees well with the AF2 models, the poor class agrees poorly, and the average class agrees between these two. The ProSs in the excellent class were characterized by some features similar to globular structures, whereas those in the poor class showed features of extended structures. The ProSs in the excellent class were further grouped into those with high prediction reliability (pLDDT) and those with a relatively low pLDDT and a small normalized radius of gyration. ABSTRACT: AlphaFold2 (AF2) is a protein structure prediction program which provides accurate models. In addition to predicting structural domains, AF2 assigns intrinsically disordered regions (IDRs) by identifying regions with low prediction reliability (pLDDT). Some regions in IDRs undergo disorder-to-order transition upon binding the interaction partner. Here we assessed model structures of AF2 based on the annotations in IDEAL, in which segments with disorder-to-order transition have been collected as Protean Segments (ProSs). We non-redundantly selected ProSs from IDEAL and classified them based on the root mean square deviation to the corresponding region of AF2 models. Statistical analysis identified 11 structural and sequential features, possibly contributing toward the prediction of ProS structures. These features were categorized into two groups: one that contained pLDDT and the other that contained normalized radius of gyration. The typical ProS structures in the former group comprise a long α helix or a whole or part of the structural domain and those in the latter group comprise a short α helix with terminal loops.
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spelling pubmed-99524132023-02-25 How AlphaFold2 Predicts Conditionally Folding Regions Annotated in an Intrinsically Disordered Protein Database, IDEAL Anbo, Hiroto Sakuma, Koya Fukuchi, Satoshi Ota, Motonori Biology (Basel) Article SIMPLE SUMMARY: Intrinsically disordered regions (IDRs) in intrinsically disordered proteins (IDPs) play important roles in various biological processes by providing protein binding regions. The regions can adopt local structures upon binding to their interaction partners. An IDP database—IDEAL—has collected these conditionally binding regions as Protean Segments (ProSs). A recently developed program, called AlphaFold2 (AF2), accurately predicts structural domains in proteins. Because ProSs have the bilateral characteristics of IDRs and ordered regions, assessing AF2 models corresponding to ProSs is worthwhile. We classified ProSs into three classes: the excellent class agrees well with the AF2 models, the poor class agrees poorly, and the average class agrees between these two. The ProSs in the excellent class were characterized by some features similar to globular structures, whereas those in the poor class showed features of extended structures. The ProSs in the excellent class were further grouped into those with high prediction reliability (pLDDT) and those with a relatively low pLDDT and a small normalized radius of gyration. ABSTRACT: AlphaFold2 (AF2) is a protein structure prediction program which provides accurate models. In addition to predicting structural domains, AF2 assigns intrinsically disordered regions (IDRs) by identifying regions with low prediction reliability (pLDDT). Some regions in IDRs undergo disorder-to-order transition upon binding the interaction partner. Here we assessed model structures of AF2 based on the annotations in IDEAL, in which segments with disorder-to-order transition have been collected as Protean Segments (ProSs). We non-redundantly selected ProSs from IDEAL and classified them based on the root mean square deviation to the corresponding region of AF2 models. Statistical analysis identified 11 structural and sequential features, possibly contributing toward the prediction of ProS structures. These features were categorized into two groups: one that contained pLDDT and the other that contained normalized radius of gyration. The typical ProS structures in the former group comprise a long α helix or a whole or part of the structural domain and those in the latter group comprise a short α helix with terminal loops. MDPI 2023-01-25 /pmc/articles/PMC9952413/ /pubmed/36829461 http://dx.doi.org/10.3390/biology12020182 Text en © 2023 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
Anbo, Hiroto
Sakuma, Koya
Fukuchi, Satoshi
Ota, Motonori
How AlphaFold2 Predicts Conditionally Folding Regions Annotated in an Intrinsically Disordered Protein Database, IDEAL
title How AlphaFold2 Predicts Conditionally Folding Regions Annotated in an Intrinsically Disordered Protein Database, IDEAL
title_full How AlphaFold2 Predicts Conditionally Folding Regions Annotated in an Intrinsically Disordered Protein Database, IDEAL
title_fullStr How AlphaFold2 Predicts Conditionally Folding Regions Annotated in an Intrinsically Disordered Protein Database, IDEAL
title_full_unstemmed How AlphaFold2 Predicts Conditionally Folding Regions Annotated in an Intrinsically Disordered Protein Database, IDEAL
title_short How AlphaFold2 Predicts Conditionally Folding Regions Annotated in an Intrinsically Disordered Protein Database, IDEAL
title_sort how alphafold2 predicts conditionally folding regions annotated in an intrinsically disordered protein database, ideal
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9952413/
https://www.ncbi.nlm.nih.gov/pubmed/36829461
http://dx.doi.org/10.3390/biology12020182
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