RCSB PDB Database Query
SkillAI & modelsQuery RCSB PDB for experimental protein structures. Use when user asks about crystal structures, X-ray, cryo-EM, NMR structures, or PDB IDs. Triggers on "pdb", "crystal structure", "cryo-em", "x-ray structure", "protein crystal", "experimental structure".
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the RCSB PDB Database Query skill
What this skill tells your AI
The instructions your AI receives, as published by biotender-max/awesome-bio-agent-skills in skills/bioclaw/query-pdb/SKILL.md and read by ahel’s review.
Query the RCSB Protein Data Bank for experimental 3D structures.
When to Use
- User asks for experimental structures of a protein
- User provides a PDB ID (e.g., "6LU7")
- User wants to find structures solved by X-ray, cryo-EM, or NMR
- User asks about resolution, ligands, or binding sites
How to Execute
import requests
import json
# 1. Text search (simple keyword)
def search_pdb(query_text, max_results=5):
url = "https://search.rcsb.org/rcsbsearch/v2/query"
query = {
"query": {
"type": "terminal",
"service": "full_text",
"parameters": {"value": query_text}
},
"return_type": "entry",
"request_options": {"paginate": {"start": 0, "rows": max_results}}
}
r = requests.post(url, json=query)
r.raise_for_status()
return r.json()
# 2. Advanced search (by gene + organism + method)
def advanced_search_pdb(gene_name, organism="Homo sapiens", method=None, max_results=5):
nodes = [
{"type": "terminal", "service": "text",
"parameters": {"attribute": "rcsb_entity_source_organism.rcsb_gene_name.value",
"operator": "exact_match", "value": gene_name}},
{"type": "terminal", "service": "text",
"parameters": {"attribute": "rcsb_entity_source_organism.ncbi_scientific_name",
"operator": "exact_match", "value": organism}}
]
if method:
nodes.append({"type": "terminal", "service": "text",
"parameters": {"attribute": "exptl.method", "operator": "exact_match", "value": method}})
query = {
"query": {"type": "group", "logical_operator": "and", "nodes": nodes},
"return_type": "entry",
"request_options": {"paginate": {"start": 0, "rows": max_results},
"sort": [{"sort_by": "rcsb_accession_info.deposit_date", "direction": "desc"}]}
}
r = requests.post("https://search.rcsb.org/rcsbsearch/v2/query", json=query)
r.raise_for_status()
return r.json()
# 3. Get entry details
def get_pdb_entry(pdb_id):
url = f"https://data.rcsb.org/rest/v1/core/entry/{pdb_id}"
r = requests.get(url)
r.raise_for_status()
return r.json()
# 4. Download structure
def download_pdb(pdb_id, output_dir="/workspace/group"):
url = f"https://files.rcsb.org/download/{pdb_id}.pdb"
r = requests.get(url)
r.raise_for_status()
path = f"{output_dir}/{pdb_id}.pdb"
with open(path, 'w') as f:
f.write(r.text)
return path
# Example
results = search_pdb("human insulin")
for hit in results.get("result_set", []):
pdb_id = hit["identifier"]
details = get_pdb_entry(pdb_id)
title = details.get("struct", {}).get("title", "N/A")
method = details.get("exptl", [{}])[0].get("method", "N/A")
resolution = details.get("rcsb_entry_info", {}).get("resolution_combined", ["N/A"])[0]
print(f"{pdb_id}: {title}")
print(f" Method: {method}, Resolution: {resolution} Å")
Common Methods
X-RAY DIFFRACTION— crystal structuresELECTRON MICROSCOPY— cryo-EMSOLUTION NMR— NMR in solution
Follow-up Suggestions
- "Want me to download this structure and analyze binding sites?"
- "Should I compare with the AlphaFold prediction?"
- "Want me to find ligands bound in this structure?"
Signals
- GitHub stars
- 178
- Forks
- 32
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
query-pdb- Source
- github.com/biotender-max/awesome-bio-agent-skills