# AlphaFold Protein Structure Database 2025: a redesigned interface and updated structural coverage

Article · Damian Bertoni, Maxim I. Tsenkov, Paulyna Magaña, Sreenath Sasidharan Nair, Ivanna Pidruchna, Marcelo Querino Lima Afonso, Adam Midlik, Urmila Paramval, Dare Kayode Lawal, Ahsan Tanweer, Meera Last, Risha Patel, Agata Laydon, Dariusz Lasecki, Nick Dietrich, Hamish Tomlinson, Augustin Žídek, Tim Green, Oleg V. Kovalevskiy, Andy M C Lau, Shaun M. Kandathil, Nicola Bordin, Ian Sillitoe, Milot Mirdita, David T. Jones and 4 more

- Archive id: doi:10.1093/nar/gkaf1226
- Published: 2025-11-22
- Venue: Nucleic Acids Research
- DOI: https://doi.org/10.1093/nar/gkaf1226
- PMID: 41273079
- Citations: 78
- Source URL: https://doi.org/10.1093/nar/gkaf1226
- Provenance: openalex

## Abstract

The AlphaFold Protein Structure Database (AFDB; https://alphafold.ebi.ac.uk), developed by EMBL-EBI and Google DeepMind, provides open access to hundreds of millions of high-accuracy protein structure predictions, transforming research in structural biology and the wider life sciences. Since its launch, AFDB has become a widely used bioinformatics resource, integrated into major databases, visualization platforms, and analysis pipelines. Here, we report the update of the database to align with the UniProt 2025\_03 release, along with a comprehensive redesign of the entry page to enhance usability, accessibility, and structural interpretation. The new design integrates annotations directly with an interactive 3D viewer and introduces dedicated domains and summary tabs. Structural coverage has also been updated to include isoforms plus underlying multiple sequence alignments. Data are available through the website, FTP, Google Cloud, and updated APIs. Together, these advances reinforce AFDB as a sustainable resource for exploring protein sequence-structure relationships.

_Abstract reproduced under CC-BY (publisher license, via OpenAlex)._

Topics: [AI Protein Design & Structure Prediction](https://space-kitty.com/topics/protein-design)

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