AlphaFold Database Download

What is AlphaFold Database Download?

AlphaFold Database Download is a direct retrieval tool for predicted protein structures deposited in the AlphaFold Protein Structure Database. It looks up a known UniProt accession and returns the model files that AlphaFold DB makes available for that record, rather than generating a new structure prediction.

The database is useful for starting from a published model with its confidence information intact. A downloaded model is still a prediction, not an experimental structure, and the confidence data matters as much as the coordinates when deciding whether a region or domain arrangement is suitable for downstream analysis.

How to use AlphaFold Database Download online

Enter a UniProt accession in ProteinIQ, such as P00533 for EGFR, then choose all available files or one output format. AlphaFold Database Download retrieves the AlphaFold DB model and available confidence data as CIF, PDB, BCIF, or PAE JSON files, ready to download and inspect alongside the source record.

Input and settings

The tool retrieves one known record at a time. If the accession is malformed, has no matching AlphaFold DB entry, or the selected file type is unavailable, no substitute model is chosen. Search AlphaFold DB first when the accession is unknown or when several proteins share a gene name.

Files returned

| File | Extension | Contents | Useful for | | --- | --- | --- | | CIF | .cif | Predicted atomic coordinates in mmCIF format. | Modern structural-biology software and workflows that preserve richer structure metadata. | | PDB | .pdb | Predicted atomic coordinates in legacy PDB format. | Viewers and analysis programs that specifically require PDB input. | | BCIF | .bcif | Binary CIF representation of the predicted model. | Faster transfer and compatible software that supports BinaryCIF. | | PAE JSON | .json | Pairwise predicted aligned error values and the reported maximum PAE. | Assessing confidence in relative domain or residue placement, or plotting the matrix programmatically. |

The files shown in the results panel preserve the selected record's source URL, format, and normalized filename. Typical names include:

alphafold-P00533-cif.cif
alphafold-P00533-pdb.pdb
alphafold-P00533-bcif.bcif
alphafold-P00533-pae-json.json

Understanding AlphaFold DB confidence data

AlphaFold DB reports a local confidence measure, pLDDT, for each residue and a predicted aligned error, PAE, for pairs of residues. pLDDT helps judge whether the model is locally reliable at a position. PAE answers a different question: how confidently the model places one residue or region relative to another.

Reading PAE JSON

The PAE JSON contains a square predicted_aligned_error matrix. Entry (i, j) is the expected position error for residue j after the predicted structure is aligned on residue i. The matrix is directional, so (i, j) and (j, i) can differ.

Low PAE within a compact block supports confidence in the relative arrangement inside that domain. Low PAE within two domains but high PAE between them means each domain may be credible while their mutual orientation is uncertain. That distinction is important before using a full-length prediction for rigid-body docking, interpreting a long linker, or measuring a distance between domains.

PAE JSON is raw data rather than a universal structure format. It is best read with code or a viewer that explicitly supports the current AlphaFold DB PAE schema. The exported matrix is not a binding score, an experimental error estimate, or evidence that a particular conformation is populated in solution.

Choosing an AlphaFold DB file for analysis

Choose mmCIF when the next program supports it. It is the more expressive coordinate format and avoids several legacy PDB restrictions. Choose PDB for programs that only accept PDB, then open the model in PDB Viewer for a quick structural inspection. PDB to CIF can convert a PDB file when a downstream workflow requires mmCIF, although downloading the CIF directly retains the original database delivery format.

Use AlphaFold Database Download when a published AlphaFold DB model already exists for a UniProt entry. For an experimental coordinate set, retrieve the corresponding archive record with PDB Download instead. For a sequence without a suitable database model, or when a new prediction is required for a sequence variant or designed protein, run AlphaFold2 or a single-sequence predictor such as ESMFold.

Predicted structures should not be treated as automatically suitable for every task. Low-confidence residues can reflect intrinsic disorder or flexibility, and a confident isolated domain does not establish the orientation of neighboring domains. Retain the accession, model version shown on the AlphaFold DB entry, file type, and any PAE assessment with downstream results so the chosen model remains traceable.