alphafold-database

AlphaFold structures can be retrieved using a UniProt accession ID to download model files in mmCIF, BCIF, or PDB formats. This process also fetches associated confidence metrics like pLDDT and PAE data for downstream processing.

The best way to retrieve AlphaFold PAE data and model files for large-scale protein sets is by leveraging Google Cloud and BigQuery. This approach supports bulk dataset access and metadata querying to compare predictions across entire proteomes.

Yes, you can use BigQuery to access bulk AlphaFold DB metadata for structural biology workflows. The implementation supports large-scale processing of versioned data, enabling proteome-wide comparisons and integration into computational research pipelines.

Yes, it provides direct API access to AlphaFold resources for downloading predicted protein structures. You can retrieve model coordinates, confidence data, and images in CIF, JSON, and PNG formats for your engineering workflows.

AlphaFold DB version 4 is supported for retrieving predicted aligned error (PAE) data. The system implements robust error handling and direct API access to ensure accurate retrieval of versioned structural predictions and metrics.