Query Alphafold

AlphaFold Structure Database Query

Query the AlphaFold EBI API for predicted protein structures.

When to Use

• User asks about a protein's predicted 3D structure
• User wants to download PDB/CIF structure files
• User asks about structure confidence (pLDDT scores)
• User wants to visualize protein structure

How to Execute

import requests
import json

BASE_URL = "https://alphafold.ebi.ac.uk/api"

# 1. Get prediction info
def get_alphafold_prediction(uniprot_id):
    url = f"{BASE_URL}/prediction/{uniprot_id}"
    r = requests.get(url)
    r.raise_for_status()
    return r.json()

# 2. Download structure file
def download_structure(uniprot_id, output_dir="/workspace/group", fmt="pdb", version="v4"):
    filename = f"AF-{uniprot_id}-F1-model_{version}.{fmt}"
    url = f"https://alphafold.ebi.ac.uk/files/{filename}"
    r = requests.get(url)
    r.raise_for_status()
    filepath = f"{output_dir}/{filename}"
    with open(filepath, 'wb') as f:
        f.write(r.content)
    return filepath

# 3. Get per-residue confidence (pLDDT)
def get_plddt(uniprot_id):
    url = f"{BASE_URL}/prediction/{uniprot_id}"
    r = requests.get(url)
    data = r.json()
    if isinstance(data, list) and data:
        cif_url = data[0].get("cifUrl", "")
        plddt_url = data[0].get("paeImageUrl", "")
        return {"cifUrl": cif_url, "paeImageUrl": plddt_url, "data": data[0]}
    return data

# Example
data = get_alphafold_prediction("P04637")  # TP53
if isinstance(data, list) and data:
    entry = data[0]
    print(f"UniProt: {entry.get('uniprotAccession')}")
    print(f"Gene: {entry.get('gene', 'N/A')}")
    print(f"Organism: {entry.get('organismScientificName', 'N/A')}")
    print(f"Model confidence: {entry.get('globalMetricValue', 'N/A')}")
    print(f"PDB URL: {entry.get('pdbUrl', 'N/A')}")
    print(f"CIF URL: {entry.get('cifUrl', 'N/A')}")

Endpoints

| Endpoint | URL | Use | |----------|-----|-----| | Prediction | /api/prediction/{uniprot_id} | Get model info & download URLs | | Summary | /api/uniprot/summary/{uniprot_id}.json | Brief summary | | Annotations | /api/annotations/{uniprot_id} | Per-residue annotations |

Download Formats

• PDB: AF-{UNIPROT_ID}-F1-model_v4.pdb
• CIF: AF-{UNIPROT_ID}-F1-model_v4.cif
• PAE image: Available from prediction endpoint

Follow-up Suggestions

• "Want me to analyze the structure confidence by region?"
• "Should I compare this to the experimental PDB structure?"
• "Want me to identify disordered regions?"

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: cheatthegod
• Source: cheatthegod/BioHermes
• License: MIT

Install and usage instructions live in the source repository linked above.