ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information

Abstract The formation of a stable complex between proteins lies at the core of a wide variety of biological processes and has been the focus of countless experiments. The huge amount of information contained in the protein structural interactome in the Protein Data Bank can now be used to character...

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Published in:Communications Biology
Main Authors: Marco Giulini, Rodrigo V. Honorato, Jesús L. Rivera, Alexandre M. J. J. Bonvin
Format: Article in Journal/Newspaper
Language:English
Published: Nature Portfolio 2024
Subjects:
Online Access:https://doi.org/10.1038/s42003-023-05718-w
https://doaj.org/article/c0e738ae06f14b90a8e16af6ae031f55
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spelling ftdoajarticles:oai:doaj.org/article:c0e738ae06f14b90a8e16af6ae031f55 2024-02-11T10:00:41+01:00 ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information Marco Giulini Rodrigo V. Honorato Jesús L. Rivera Alexandre M. J. J. Bonvin 2024-01-01T00:00:00Z https://doi.org/10.1038/s42003-023-05718-w https://doaj.org/article/c0e738ae06f14b90a8e16af6ae031f55 EN eng Nature Portfolio https://doi.org/10.1038/s42003-023-05718-w https://doaj.org/toc/2399-3642 doi:10.1038/s42003-023-05718-w 2399-3642 https://doaj.org/article/c0e738ae06f14b90a8e16af6ae031f55 Communications Biology, Vol 7, Iss 1, Pp 1-9 (2024) Biology (General) QH301-705.5 article 2024 ftdoajarticles https://doi.org/10.1038/s42003-023-05718-w 2024-01-14T01:51:52Z Abstract The formation of a stable complex between proteins lies at the core of a wide variety of biological processes and has been the focus of countless experiments. The huge amount of information contained in the protein structural interactome in the Protein Data Bank can now be used to characterise and classify the existing biological interfaces. We here introduce ARCTIC-3D, a fast and user-friendly data mining and clustering software to retrieve data and rationalise the interface information associated with the protein input data. We demonstrate its use by various examples ranging from showing the increased interaction complexity of eukaryotic proteins, 20% of which on average have more than 3 different interfaces compared to only 10% for prokaryotes, to associating different functions to different interfaces. In the context of modelling biomolecular assemblies, we introduce the concept of “recognition entropy”, related to the number of possible interfaces of the components of a protein-protein complex, which we demonstrate to correlate with the modelling difficulty in classical docking approaches. The identified interface clusters can also be used to generate various combinations of interface-specific restraints for integrative modelling. The ARCTIC-3D software is freely available at github.com/haddocking/arctic3d and can be accessed as a web-service at wenmr.science.uu.nl/arctic3d. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Communications Biology 7 1
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Biology (General)
QH301-705.5
spellingShingle Biology (General)
QH301-705.5
Marco Giulini
Rodrigo V. Honorato
Jesús L. Rivera
Alexandre M. J. J. Bonvin
ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information
topic_facet Biology (General)
QH301-705.5
description Abstract The formation of a stable complex between proteins lies at the core of a wide variety of biological processes and has been the focus of countless experiments. The huge amount of information contained in the protein structural interactome in the Protein Data Bank can now be used to characterise and classify the existing biological interfaces. We here introduce ARCTIC-3D, a fast and user-friendly data mining and clustering software to retrieve data and rationalise the interface information associated with the protein input data. We demonstrate its use by various examples ranging from showing the increased interaction complexity of eukaryotic proteins, 20% of which on average have more than 3 different interfaces compared to only 10% for prokaryotes, to associating different functions to different interfaces. In the context of modelling biomolecular assemblies, we introduce the concept of “recognition entropy”, related to the number of possible interfaces of the components of a protein-protein complex, which we demonstrate to correlate with the modelling difficulty in classical docking approaches. The identified interface clusters can also be used to generate various combinations of interface-specific restraints for integrative modelling. The ARCTIC-3D software is freely available at github.com/haddocking/arctic3d and can be accessed as a web-service at wenmr.science.uu.nl/arctic3d.
format Article in Journal/Newspaper
author Marco Giulini
Rodrigo V. Honorato
Jesús L. Rivera
Alexandre M. J. J. Bonvin
author_facet Marco Giulini
Rodrigo V. Honorato
Jesús L. Rivera
Alexandre M. J. J. Bonvin
author_sort Marco Giulini
title ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information
title_short ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information
title_full ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information
title_fullStr ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information
title_full_unstemmed ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information
title_sort arctic-3d: automatic retrieval and clustering of interfaces in complexes from 3d structural information
publisher Nature Portfolio
publishDate 2024
url https://doi.org/10.1038/s42003-023-05718-w
https://doaj.org/article/c0e738ae06f14b90a8e16af6ae031f55
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source Communications Biology, Vol 7, Iss 1, Pp 1-9 (2024)
op_relation https://doi.org/10.1038/s42003-023-05718-w
https://doaj.org/toc/2399-3642
doi:10.1038/s42003-023-05718-w
2399-3642
https://doaj.org/article/c0e738ae06f14b90a8e16af6ae031f55
op_doi https://doi.org/10.1038/s42003-023-05718-w
container_title Communications Biology
container_volume 7
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