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

Author:

Varadi Mihaly1ORCID,Bertoni Damian1,Magana Paulyna1,Paramval Urmila1,Pidruchna Ivanna1,Radhakrishnan Malarvizhi1,Tsenkov Maxim1,Nair Sreenath1,Mirdita Milot2,Yeo Jingi2,Kovalevskiy Oleg3,Tunyasuvunakool Kathryn3,Laydon Agata3,Žídek Augustin3,Tomlinson Hamish3,Hariharan Dhavanthi3,Abrahamson Josh3,Green Tim3,Jumper John3,Birney Ewan1ORCID,Steinegger Martin2,Hassabis Demis3,Velankar Sameer1ORCID

Affiliation:

1. European Molecular Biology Laboratory, European Bioinformatics Institute , Hinxton, UK

2. School of Biological Sciences, Seoul National University , Seoul , South Korea

3. Google DeepMind , London , UK

Abstract

Abstract 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.

Funder

Google DeepMind

National Research Foundation of Korea

Samsung DS Research Fund

Seoul National University

Publisher

Oxford University Press (OUP)

Subject

Genetics

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