alphafold-api

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Summary

Query AlphaFold protein structure predictions by UniProt accession

SKILL.md

AlphaFold Protein Structure Database API

Overview

The AlphaFold DB, maintained by EMBL-EBI and DeepMind, provides open access to over 200 million protein structure predictions. The REST API enables programmatic lookup of predicted structures, confidence metrics (pLDDT, PAE), and downloadable structure files (PDB, mmCIF, BinaryCIF) keyed on UniProt accessions. Free, no authentication required.

Authentication

None. All endpoints are publicly accessible without API keys or tokens.

Core Endpoints

Base URL: https://alphafold.ebi.ac.uk/api

1. Get Prediction by UniProt Accession

Retrieves all AlphaFold models for a given UniProt accession or model ID.

curl "https://alphafold.ebi.ac.uk/api/prediction/P04637"

Response (first entry, abbreviated):

[
  {
    "entryId": "AF-P04637-F1",
    "uniprotAccession": "P04637",
    "uniprotId": "P53_HUMAN",
    "uniprotDescription": "Cellular tumor antigen p53",
    "gene": "TP53",
    "organismScientificName": "Homo sapiens",
    "taxId": 9606,
    "globalMetricValue": 75.06,
    "fractionPlddtVeryHigh": 0.527,
    "fractionPlddtConfident": 0.071,
    "fractionPlddtLow": 0.104,
    "fractionPlddtVeryLow": 0.298,
    "latestVersion": 6,
    "modelCreatedDate": "2025-08-01T00:00:00Z",
    "sequenceStart": 1,
    "sequenceEnd": 393,
    "pdbUrl": "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-model_v6.pdb",
    "cifUrl": "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-model_v6.cif",
    "bcifUrl": "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-model_v6.bcif",
    "paeImageUrl": "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-predicted_aligned_error_v6.png",
    "paeDocUrl": "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-predicted_aligned_error_v6.json",
    "plddtDocUrl": "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-confidence_v6.json",
    "amAnnotationsUrl": "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-aa-substitutions.csv"
  }
]

2. Per-Residue Confidence Scores (pLDDT)

Download the per-residue pLDDT confidence JSON linked in plddtDocUrl:

curl "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-confidence_v6.json"

{
  "residueNumber": [1, 2, 3, 4, 5],
  "confidenceScore": [40.66, 44.53, 49.97, 48.59, 44.88],
  "confidenceCategory": ["D", "D", "D", "D", "D"]
}

curl "https://alphafold.ebi.ac.uk/api/uniprot/summary/P04637.json"

{
  "uniprot_entry": {
    "ac": "P04637",
    "id": "P53_HUMAN",
    "sequence_length": 393
  },
  "structures": [
    {
      "summary": {
        "model_identifier": "AF-P04637-F1",
        "model_url": "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-model_v6.cif",
        "provider": "AlphaFold DB",
        "confidence_type": "pLDDT",
        "confidence_avg_local_score": 75.06,
        "coverage": 1.0
      }
    }
  ]
}

# PDB format
curl -O "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-model_v6.pdb"

# mmCIF format
curl -O "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-model_v6.cif"

# Predicted Aligned Error (PAE) matrix
curl -O "https://alphafold.ebi.ac.uk/files/AF-P04637-F1-predicted_aligned_error_v6.json"

Field	Type	Description
`entryId`	string	AlphaFold model ID (e.g., `AF-P04637-F1`)
`uniprotAccession`	string	UniProt accession code
`gene`	string	Gene symbol
`globalMetricValue`	float	Average pLDDT score (0-100)
`fractionPlddtVeryHigh`	float	Fraction of residues with pLDDT > 90
`fractionPlddtConfident`	float	Fraction with pLDDT 70-90
`fractionPlddtLow`	float	Fraction with pLDDT 50-70
`fractionPlddtVeryLow`	float	Fraction with pLDDT < 50
`pdbUrl`	string	Direct download URL for PDB file
`cifUrl`	string	Direct download URL for mmCIF file
`paeDocUrl`	string	URL for predicted aligned error JSON
`plddtDocUrl`	string	URL for per-residue confidence JSON
`latestVersion`	int	Model version number

import requests


def get_alphafold_prediction(uniprot_id: str) -> dict:
    """Fetch AlphaFold structure prediction for a UniProt accession."""
    url = f"https://alphafold.ebi.ac.uk/api/prediction/{uniprot_id}"
    resp = requests.get(url)
    resp.raise_for_status()
    entries = resp.json()
    # Return the canonical (first) entry
    return entries[0] if entries else None


def get_confidence_scores(prediction: dict) -> dict:
    """Download per-residue pLDDT confidence scores."""
    resp = requests.get(prediction["plddtDocUrl"])
    resp.raise_for_status()
    return resp.json()


def download_structure(prediction: dict, fmt: str = "pdb",
                       output_dir: str = ".") -> str:
    """Download structure file in pdb, cif, or bcif format."""
    url_key = {"pdb": "pdbUrl", "cif": "cifUrl", "bcif": "bcifUrl"}[fmt]
    url = prediction[url_key]
    filename = url.split("/")[-1]
    path = f"{output_dir}/{filename}"

    resp = requests.get(url)
    resp.raise_for_status()
    with open(path, "wb") as f:
        f.write(resp.content)
    return path


# Example: fetch p53 structure and assess quality
pred = get_alphafold_prediction("P04637")
print(f"Gene: {pred['gene']} ({pred['uniprotDescription']})")
print(f"Organism: {pred['organismScientificName']}")
print(f"Average pLDDT: {pred['globalMetricValue']}")
print(f"Very high confidence: {pred['fractionPlddtVeryHigh']:.1%}")

# Download per-residue scores
scores = get_confidence_scores(pred)
high_conf = [i+1 for i, c in enumerate(scores["confidenceCategory"])
             if c in ("A", "B")]
print(f"High-confidence residues: {len(high_conf)}/{len(scores['residueNumber'])}")

# Download PDB file
path = download_structure(pred, fmt="pdb")
print(f"Structure saved to: {path}")

alphafold-api

Summary

SKILL.md

AlphaFold Protein Structure Database API

Overview

Authentication

Core Endpoints

1. Get Prediction by UniProt Accession

2. Per-Residue Confidence Scores (pLDDT)

3. UniProt Summary (3D-Beacons Format)

4. Download Structure Files

Key Response Fields

Rate Limits

Python Example

Academic Use Cases

References

Related skills