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AlphaFold Protein Structure Database 2025: a redesigned interface and updated structural coverage
Damian Bertoni1, Maxim Tsenkov1, Paulyna Magana1
1European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.
Nucleic Acids Research
|November 22, 2025
Summary
The AlphaFold Protein Structure Database (AFDB) now includes updated protein structures and a redesigned interface for easier exploration. This enhanced resource supports structural biology research by providing access to millions of protein predictions.
Area of Science:
- Structural biology
- Bioinformatics
- Computational biology
Background:
- The AlphaFold Protein Structure Database (AFDB) is a key resource for accessing protein structure predictions.
- It has been widely adopted in life sciences research and integrated into various bioinformatics tools.
- Previous versions required updates to incorporate new data and improve user experience.
Purpose of the Study:
- To update the AlphaFold Protein Structure Database (AFDB) with the latest UniProt release (2025_03).
- To redesign the AFDB entry page for improved usability, accessibility, and structural interpretation.
- To expand structural coverage and enhance data accessibility.
Main Methods:
- Database update aligning with UniProt 2025_03 release.
- Redesign of the entry page with integrated annotations and an interactive 3D viewer.
- Inclusion of isoforms and multiple sequence alignments in structural coverage.
Main Results:
- The AFDB is updated to UniProt 2025_03, providing access to millions of high-accuracy protein structure predictions.
- A redesigned entry page features integrated annotations, an interactive 3D viewer, and dedicated tabs for domains and summaries.
- Expanded structural coverage now includes isoforms and multiple sequence alignments.
Conclusions:
- The updated AFDB enhances usability and accessibility for researchers.
- The database remains a vital, sustainable resource for exploring protein sequence-structure relationships.
- New features facilitate deeper structural interpretation and data integration.
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