AlphaFold Protein Structure Database

Description

AlphaFold is an advanced AI system created by Google DeepMind, designed to predict the three-dimensional structure of proteins from their amino acid sequences. This groundbreaking technology has been developed in collaboration with EMBL's European Bioinformatics Institute (EMBL-EBI) to create the AlphaFold Protein Structure Database. The database contains over 200 million entries, offering extensive coverage of UniProt, the standard repository for protein sequences and annotations.

The AlphaFold Protein Structure Database is a valuable resource for the scientific community, providing high-accuracy predictions that are competitive with experimental results. The database includes individual downloads for the human proteome and 47 other key organisms, crucial for research and global health. Additionally, it offers a download for the manually curated subset of UniProt, known as Swiss-Prot.

AlphaFold gained recognition as the top-ranked protein structure prediction method at CASP14, demonstrating its potential to advance biological research by enhancing our understanding of protein structures. Despite some limitations, the system's accuracy and reliability make it a powerful tool for researchers.

The database is continually updated with new protein structures, and its features and functionality are improved based on user feedback. Researchers can also generate their own AlphaFold predictions using the open-source code, which supports multimer prediction.

The data in the AlphaFold Protein Structure Database is available for academic and commercial use under a CC-BY-4.0 license, with proper attribution expected. The database facilitates functional and mechanistic discoveries across biology, contributing to advancements in understanding protein complexes and their roles in various biological processes.

AlphaFold Protein Structure Database's Core Features

• Predicts 3D protein structures

• Over 200 million entries

• High-accuracy predictions

• Coverage of UniProt

• Human and key organism proteomes

• Open-source prediction code

• Supports multimer prediction

• CC-BY-4.0 license for data use

How to use AlphaFold Protein Structure Database?

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AlphaFold Protein Structure Database's Use Cases

• Protein research
• Drug discovery
• Genetic studies
• Biological research
• Educational purposes

FAQ from AlphaFold Protein Structure Database

• How does AlphaFold work?

  AlphaFold predicts protein 3D structures using AI, with methods detailed in DeepMind's 2021 paper.

• Who can submit datasets to AlphaFold?

  Eligible datasets using AlphaFold 2 or multimer can be submitted with a scientific justification.

• What if I can’t find the protein I’m interested in?

  Try searching by protein or gene name, or generate predictions using the open-source code.

• How can I download and use the Predicted Aligned Error (PAE) file?

  PAE files can be downloaded as JSON and analyzed using Python or other programming languages.

• Who should I contact with enquiries about AlphaFold?

  Contact [email protected] for general inquiries or [email protected] for database-specific questions.

• What is the license for AlphaFold data?

  Data is available under a CC-BY-4.0 license, requiring proper attribution.

• What is the coverage of the AlphaFold database?

  The database covers over 200 million protein entries, including the human proteome and key organisms.

• What are the limitations of AlphaFold?

  While highly accurate, AlphaFold has some limitations and is continually improved based on feedback.