claude-scientific-skills/scientific-databases/pdb-database/SKILL.md

name, description

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description

pdb-database

Access and analyze the RCSB Protein Data Bank (PDB) - the global repository for 3D structural data of biological macromolecules including proteins, nucleic acids, complexes, and ligands. This skill enables searching structures by text, attributes, sequence similarity, and structural similarity; retrieving detailed metadata and experimental information; downloading coordinate files in PDB, mmCIF, and BinaryCIF formats; performing batch operations on multiple structures; and integrating PDB data into computational workflows. Use this skill for protein structure analysis, molecular visualization, drug discovery research, protein engineering, structural biology studies, crystallographic data analysis, homology modeling, ligand binding site analysis, structure-function relationship studies, evolutionary analysis, educational content creation, and any task requiring access to experimentally determined or computationally predicted macromolecular structures. Key capabilities include querying by organism, resolution, experimental method, deposition date, biological assembly information, and performing sequence/structure similarity searches across the entire PDB archive.

PDB Database

Overview

This skill provides tools and guidance for working with the RCSB Protein Data Bank (PDB), the worldwide repository for 3D structural data of biological macromolecules. The PDB contains over 200,000 experimentally determined structures of proteins, nucleic acids, and complex assemblies, along with computed structure models. Use this skill to search for structures, retrieve structural data, perform sequence and structure similarity searches, and integrate PDB data into computational workflows.

Core Capabilities

1. Searching for Structures

Find PDB entries using various search criteria:

Text Search: Search by protein name, keywords, or descriptions

from rcsbapi.search import TextQuery
query = TextQuery("hemoglobin")
results = list(query())
print(f"Found {len(results)} structures")

Attribute Search: Query specific properties (organism, resolution, method, etc.)

from rcsbapi.search import AttributeQuery
from rcsbapi.search.attrs import rcsb_entity_source_organism

# Find human protein structures
query = AttributeQuery(
    attribute=rcsb_entity_source_organism.scientific_name,
    operator="exact_match",
    value="Homo sapiens"
)
results = list(query())

Sequence Similarity: Find structures similar to a given sequence

from rcsbapi.search import SequenceQuery

query = SequenceQuery(
    value="MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLCVFAINNTKSFEDIHHYREQIKRVKDSEDVPMVLVGNKCDLPSRTVDTKQAQDLARSYGIPFIETSAKTRQGVDDAFYTLVREIRKHKEKMSKDGKKKKKKSKTKCVIM",
    evalue_cutoff=0.1,
    identity_cutoff=0.9
)
results = list(query())

Structure Similarity: Find structures with similar 3D geometry

from rcsbapi.search import StructSimilarityQuery

query = StructSimilarityQuery(
    structure_search_type="entry",
    entry_id="4HHB"  # Hemoglobin
)
results = list(query())

Combining Queries: Use logical operators to build complex searches

from rcsbapi.search import TextQuery, AttributeQuery
from rcsbapi.search.attrs import rcsb_entry_info

# High-resolution human proteins
query1 = AttributeQuery(
    attribute=rcsb_entity_source_organism.scientific_name,
    operator="exact_match",
    value="Homo sapiens"
)
query2 = AttributeQuery(
    attribute=rcsb_entry_info.resolution_combined,
    operator="less",
    value=2.0
)
combined_query = query1 & query2  # AND operation
results = list(combined_query())

2. Retrieving Structure Data

Access detailed information about specific PDB entries:

Basic Entry Information:

from rcsbapi.data import Schema, fetch

# Get entry-level data
entry_data = fetch("4HHB", schema=Schema.ENTRY)
print(entry_data["struct"]["title"])
print(entry_data["exptl"][0]["method"])

Polymer Entity Information:

# Get protein/nucleic acid information
entity_data = fetch("4HHB_1", schema=Schema.POLYMER_ENTITY)
print(entity_data["entity_poly"]["pdbx_seq_one_letter_code"])

Using GraphQL for Flexible Queries:

from rcsbapi.data import fetch

# Custom GraphQL query
query = """
{
  entry(entry_id: "4HHB") {
    struct {
      title
    }
    exptl {
      method
    }
    rcsb_entry_info {
      resolution_combined
      deposited_atom_count
    }
  }
}
"""
data = fetch(query_type="graphql", query=query)

3. Downloading Structure Files

Retrieve coordinate files in various formats:

Download Methods:

• PDB format (legacy text format): https://files.rcsb.org/download/{PDB_ID}.pdb
• mmCIF format (modern standard): https://files.rcsb.org/download/{PDB_ID}.cif
• BinaryCIF (compressed binary): Use ModelServer API for efficient access
• Biological assembly: https://files.rcsb.org/download/{PDB_ID}.pdb1 (for assembly 1)

Example Download:

import requests

pdb_id = "4HHB"

# Download PDB format
pdb_url = f"https://files.rcsb.org/download/{pdb_id}.pdb"
response = requests.get(pdb_url)
with open(f"{pdb_id}.pdb", "w") as f:
    f.write(response.text)

# Download mmCIF format
cif_url = f"https://files.rcsb.org/download/{pdb_id}.cif"
response = requests.get(cif_url)
with open(f"{pdb_id}.cif", "w") as f:
    f.write(response.text)

4. Working with Structure Data

Common operations with retrieved structures:

Parse and Analyze Coordinates: Use BioPython or other structural biology libraries to work with downloaded files:

from Bio.PDB import PDBParser

parser = PDBParser()
structure = parser.get_structure("protein", "4HHB.pdb")

# Iterate through atoms
for model in structure:
    for chain in model:
        for residue in chain:
            for atom in residue:
                print(atom.get_coord())

Extract Metadata:

from rcsbapi.data import fetch, Schema

# Get experimental details
data = fetch("4HHB", schema=Schema.ENTRY)

resolution = data.get("rcsb_entry_info", {}).get("resolution_combined")
method = data.get("exptl", [{}])[0].get("method")
deposition_date = data.get("rcsb_accession_info", {}).get("deposit_date")

print(f"Resolution: {resolution} Å")
print(f"Method: {method}")
print(f"Deposited: {deposition_date}")

5. Batch Operations

Process multiple structures efficiently:

from rcsbapi.data import fetch, Schema

pdb_ids = ["4HHB", "1MBN", "1GZX"]  # Hemoglobin, myoglobin, etc.

results = {}
for pdb_id in pdb_ids:
    try:
        data = fetch(pdb_id, schema=Schema.ENTRY)
        results[pdb_id] = {
            "title": data["struct"]["title"],
            "resolution": data.get("rcsb_entry_info", {}).get("resolution_combined"),
            "organism": data.get("rcsb_entity_source_organism", [{}])[0].get("scientific_name")
        }
    except Exception as e:
        print(f"Error fetching {pdb_id}: {e}")

# Display results
for pdb_id, info in results.items():
    print(f"\n{pdb_id}: {info['title']}")
    print(f"  Resolution: {info['resolution']} Å")
    print(f"  Organism: {info['organism']}")

Python Package Installation

Install the official RCSB PDB Python API client:

# Current recommended package
pip install rcsb-api

# For legacy code (deprecated, use rcsb-api instead)
pip install rcsbsearchapi

The rcsb-api package provides unified access to both Search and Data APIs through the rcsbapi.search and rcsbapi.data modules.

Common Use Cases

Drug Discovery

• Search for structures of drug targets
• Analyze ligand binding sites
• Compare protein-ligand complexes
• Identify similar binding pockets

Protein Engineering

• Find homologous structures for modeling
• Analyze sequence-structure relationships
• Compare mutant structures
• Study protein stability and dynamics

Structural Biology Research

• Download structures for computational analysis
• Build structure-based alignments
• Analyze structural features (secondary structure, domains)
• Compare experimental methods and quality metrics

Education and Visualization

• Retrieve structures for teaching
• Generate molecular visualizations
• Explore structure-function relationships
• Study evolutionary conservation

Key Concepts

PDB ID: Unique 4-character identifier (e.g., "4HHB") for each structure entry. AlphaFold and ModelArchive entries start with "AF_" or "MA_" prefixes.

mmCIF/PDBx: Modern file format that uses key-value structure, replacing legacy PDB format for large structures.

Biological Assembly: The functional form of a macromolecule, which may contain multiple copies of chains from the asymmetric unit.

Resolution: Measure of detail in crystallographic structures (lower values = higher detail). Typical range: 1.5-3.5 Å for high-quality structures.

Entity: A unique molecular component in a structure (protein chain, DNA, ligand, etc.).

Resources

This skill includes reference documentation in the references/ directory:

references/api_reference.md

Comprehensive API documentation covering:

• Detailed API endpoint specifications
• Advanced query patterns and examples
• Data schema reference
• Rate limiting and best practices
• Troubleshooting common issues

Use this reference when you need in-depth information about API capabilities, complex query construction, or detailed data schema information.

Additional Resources

• RCSB PDB Website: https://www.rcsb.org
• PDB-101 Educational Portal: https://pdb101.rcsb.org
• API Documentation: https://www.rcsb.org/docs/programmatic-access/web-apis-overview
• Python Package Docs: https://rcsbapi.readthedocs.io/
• Data API Documentation: https://data.rcsb.org/
• GitHub Repository: https://github.com/rcsb/py-rcsb-api