AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer

SUMMARY: The artificial intelligence-based structure prediction program AlphaFold-Multimer enabled structural modelling of protein complexes with unprecedented accuracy. Increasingly, AlphaFold-Multimer is also used to discover new protein–protein interactions (PPIs). Here, we present AlphaPulldown,...

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Detalles Bibliográficos
Autores principales: Yu, Dingquan, Chojnowski, Grzegorz, Rosenthal, Maria, Kosinski, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Applications Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9805587/
https://www.ncbi.nlm.nih.gov/pubmed/36413069
http://dx.doi.org/10.1093/bioinformatics/btac749
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author Yu, Dingquan
Chojnowski, Grzegorz
Rosenthal, Maria
Kosinski, Jan
author_facet Yu, Dingquan
Chojnowski, Grzegorz
Rosenthal, Maria
Kosinski, Jan
author_sort Yu, Dingquan
collection PubMed
description SUMMARY: The artificial intelligence-based structure prediction program AlphaFold-Multimer enabled structural modelling of protein complexes with unprecedented accuracy. Increasingly, AlphaFold-Multimer is also used to discover new protein–protein interactions (PPIs). Here, we present AlphaPulldown, a Python package that streamlines PPI screens and high-throughput modelling of higher-order oligomers using AlphaFold-Multimer. It provides a convenient command-line interface, a variety of confidence scores and a graphical analysis tool. AVAILABILITY AND IMPLEMENTATION: AlphaPulldown is freely available at https://www.embl-hamburg.de/AlphaPulldown. SUPPLEMENTARY INFORMATION: Supplementary note is available at Bioinformatics online.
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spelling pubmed-98055872023-01-03 AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer Yu, Dingquan Chojnowski, Grzegorz Rosenthal, Maria Kosinski, Jan Bioinformatics Applications Note SUMMARY: The artificial intelligence-based structure prediction program AlphaFold-Multimer enabled structural modelling of protein complexes with unprecedented accuracy. Increasingly, AlphaFold-Multimer is also used to discover new protein–protein interactions (PPIs). Here, we present AlphaPulldown, a Python package that streamlines PPI screens and high-throughput modelling of higher-order oligomers using AlphaFold-Multimer. It provides a convenient command-line interface, a variety of confidence scores and a graphical analysis tool. AVAILABILITY AND IMPLEMENTATION: AlphaPulldown is freely available at https://www.embl-hamburg.de/AlphaPulldown. SUPPLEMENTARY INFORMATION: Supplementary note is available at Bioinformatics online. Oxford University Press 2022-11-22 /pmc/articles/PMC9805587/ /pubmed/36413069 http://dx.doi.org/10.1093/bioinformatics/btac749 Text en © The Author(s) 2022. 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 Applications Note
Yu, Dingquan
Chojnowski, Grzegorz
Rosenthal, Maria
Kosinski, Jan
AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer
title AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer
title_full AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer
title_fullStr AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer
title_full_unstemmed AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer
title_short AlphaPulldown—a python package for protein–protein interaction screens using AlphaFold-Multimer
title_sort alphapulldown—a python package for protein–protein interaction screens using alphafold-multimer
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9805587/
https://www.ncbi.nlm.nih.gov/pubmed/36413069
http://dx.doi.org/10.1093/bioinformatics/btac749
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