pdb-database

提供对全球蛋白质数据库的全面访问,支持通过文本、序列或三维结构检索生物大分子模型,获取实验数据与质量参数,并下载标准格式的坐标文件,适用于药物设计、蛋白工程及结构生物学研究。

快捷安装

在终端运行此命令,即可一键安装该 Skill 到您的 Claude 中

npx skills add davila7/claude-code-templates --skill "pdb-database"

PDB Database

Overview

RCSB PDB is the worldwide repository for 3D structural data of biological macromolecules. Search for structures, retrieve coordinates and metadata, perform sequence and structure similarity searches across 200,000+ experimentally determined structures and computed models.

When to Use This Skill

This skill should be used when:

  • Searching for protein or nucleic acid 3D structures by text, sequence, or structural similarity
  • Downloading coordinate files in PDB, mmCIF, or BinaryCIF formats
  • Retrieving structural metadata, experimental methods, or quality metrics
  • Performing batch operations across multiple structures
  • Integrating PDB data into computational workflows for drug discovery, protein engineering, or structural biology research

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
uv pip install rcsb-api

# For legacy code (deprecated, use rcsb-api instead)
uv 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