query-alphafold
Queries the AlphaFold EBI API for protein 3D structure predictions and confidence data.
Install
mkdir -p .claude/skills/query-alphafold && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/11475" && unzip -o skill.zip -d .claude/skills/query-alphafold && rm skill.zipInstalls to .claude/skills/query-alphafold
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Query AlphaFold protein structure predictions. Use when user asks about protein structure, 3D structure, protein folding, or structure prediction. Triggers on "alphafold", "protein structure", "3D structure", "folding", "pLDDT", "structure prediction".Key capabilities
- →Retrieve AlphaFold prediction information for a UniProt ID.
- →Download protein structure files in PDB or CIF format.
- →Obtain per-residue pLDDT confidence scores.
- →Access URLs for predicted protein structures and related data.
How it works
The skill queries the AlphaFold EBI API to retrieve protein structure predictions and related data. It can then download structure files or extract confidence scores.
Inputs & outputs
When to use query-alphafold
- →Fetch AlphaFold predicted structure info
- →Download PDB or CIF files for a protein
- →Retrieve pLDDT per-residue confidence scores
About this skill
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?"
When not to use it
- →When the user is asking about experimental PDB structures.
- →When the user wants to identify disordered regions without prior structure retrieval.
Limitations
- →The skill only provides predicted protein structures, not experimental ones.
- →The skill relies on the AlphaFold EBI API for data retrieval.
How it compares
This skill automates the process of fetching and downloading AlphaFold protein structure data directly from the EBI API, unlike manual browsing and downloading.
Compared to similar skills
query-alphafold side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| query-alphafold (this skill) | 0 | 2mo | Review | Beginner |
| literature-review | 559 | 2mo | Review | Advanced |
| openalex-database | 48 | 7mo | Review | Intermediate |
| scientific-critical-thinking | 18 | 7mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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