Open Access

Nucleic Acids Research

, том 52 , издание D1 , страницы D368-D375

AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences

Mihaly Varadi ¹

Damian Bertoni ¹

Paulyna Magana ¹

Urmila Paramval ¹

Ivanna Pidruchna ¹

Malarvizhi Radhakrishnan ¹

Maxim Tsenkov ¹

Sreenath Nair ¹

Milot Mirdita ²

Jingi Yeo ²

Oleg Kovalevskiy ³

Kathryn Tunyasuvunakool ³

Agata Laydon ³

Augustin Žídek ³

Hamish Tomlinson ³

Dhavanthi Hariharan ³

Josh Abrahamson ³

Tim Green ³

John Jumper ³

Ewan Birney ¹

Martin Steinegger ²

Demis Hassabis ³

Sameer Velankar ¹

Скрыть аффилиации авторов Показать аффилиации авторов: 3 аффилиации

European Molecular Biology Laboratory, European Bioinformatics Institute , Hinxton, UK |

School of Biological Sciences, Seoul National University , Seoul , South Korea |

Google DeepMind , London , UK |

Тип публикации: Journal Article

Дата публикации: 2023-11-02

Oxford University Press

Nucleic Acids Research

scimago Q1

wos Q1

БС1

SJR: 7.776

CiteScore: 31.7

Impact factor: 13.1

ISSN: 03051048, 13624962

DOI: 10.1093/nar/gkad1011

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PubMed ID: 37933859

Genetics

Краткое описание

The AlphaFold Database Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) has significantly impacted structural biology by amassing over 214 million predicted protein structures, expanding from the initial 300k structures released in 2021. Enabled by the groundbreaking AlphaFold2 artificial intelligence (AI) system, the predictions archived in AlphaFold DB have been integrated into primary data resources such as PDB, UniProt, Ensembl, InterPro and MobiDB. Our manuscript details subsequent enhancements in data archiving, covering successive releases encompassing model organisms, global health proteomes, Swiss-Prot integration, and a host of curated protein datasets. We detail the data access mechanisms of AlphaFold DB, from direct file access via FTP to advanced queries using Google Cloud Public Datasets and the programmatic access endpoints of the database. We also discuss the improvements and services added since its initial release, including enhancements to the Predicted Aligned Error viewer, customisation options for the 3D viewer, and improvements in the search engine of AlphaFold DB.

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Varadi M. et al. AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences // Nucleic Acids Research. 2023. Vol. 52. No. D1. p. D368-D375.

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Varadi M., Bertoni D., Magana P., Paramval U., Pidruchna I., Radhakrishnan M., Tsenkov M., Nair S., Mirdita M., Yeo J., Kovalevskiy O., Tunyasuvunakool K., Laydon A., Žídek A., Tomlinson H., Hariharan D., Abrahamson J., Green T., Jumper J., Birney E., Steinegger M., Hassabis D., Velankar S. AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences // Nucleic Acids Research. 2023. Vol. 52. No. D1. p. D368-D375.

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TY - JOUR

DO - 10.1093/nar/gkad1011

UR - https://doi.org/10.1093/nar/gkad1011

TI - AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences

T2 - Nucleic Acids Research

AU - Varadi, Mihaly

AU - Bertoni, Damian

AU - Magana, Paulyna

AU - Paramval, Urmila

AU - Pidruchna, Ivanna

AU - Radhakrishnan, Malarvizhi

AU - Tsenkov, Maxim

AU - Nair, Sreenath

AU - Mirdita, Milot

AU - Yeo, Jingi

AU - Kovalevskiy, Oleg

AU - Tunyasuvunakool, Kathryn

AU - Laydon, Agata

AU - Žídek, Augustin

AU - Tomlinson, Hamish

AU - Hariharan, Dhavanthi

AU - Abrahamson, Josh

AU - Green, Tim

AU - Jumper, John

AU - Birney, Ewan

AU - Steinegger, Martin

AU - Hassabis, Demis

AU - Velankar, Sameer

PY - 2023

DA - 2023/11/02

PB - Oxford University Press

SP - D368-D375

IS - D1

VL - 52

PMID - 37933859

SN - 0305-1048

SN - 1362-4962

ER -

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@article{2023_Varadi,

author = {Mihaly Varadi and Damian Bertoni and Paulyna Magana and Urmila Paramval and Ivanna Pidruchna and Malarvizhi Radhakrishnan and Maxim Tsenkov and Sreenath Nair and Milot Mirdita and Jingi Yeo and Oleg Kovalevskiy and Kathryn Tunyasuvunakool and Agata Laydon and Augustin Žídek and Hamish Tomlinson and Dhavanthi Hariharan and Josh Abrahamson and Tim Green and John Jumper and Ewan Birney and Martin Steinegger and Demis Hassabis and Sameer Velankar},

title = {AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences},

journal = {Nucleic Acids Research},

year = {2023},

volume = {52},

publisher = {Oxford University Press},

month = {nov},

url = {https://doi.org/10.1093/nar/gkad1011},

number = {D1},

pages = {D368--D375},

doi = {10.1093/nar/gkad1011}

}

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Varadi, Mihaly, et al. “AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences.” Nucleic Acids Research, vol. 52, no. D1, Nov. 2023, pp. D368-D375. https://doi.org/10.1093/nar/gkad1011.