RCSB PDB 数据库 API 使用指南：搜索、下载与分析蛋白质三维结构数据

pdb-database by davila7/claude-code-templates

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安装命令

npx skills add https://github.com/davila7/claude-code-templates --skill pdb-database

科研工具生物信息学 API

🇨🇳中文介绍

PDB 数据库

概述

RCSB PDB 是全球生物大分子三维结构数据的存储库。可搜索结构、获取坐标和元数据，在超过 20 万个实验测定结构和计算模型中进行序列和结构相似性搜索。

何时使用此技能

此技能应在以下情况下使用：

通过文本、序列或结构相似性搜索蛋白质或核酸的三维结构
下载 PDB、mmCIF 或 BinaryCIF 格式的坐标文件
检索结构元数据、实验方法或质量指标
跨多个结构执行批量操作
将 PDB 数据集成到药物发现、蛋白质工程或结构生物学研究的计算工作流程中

核心功能

1. 搜索结构

使用各种搜索条件查找 PDB 条目：

文本搜索： 按蛋白质名称、关键词或描述搜索

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

属性搜索： 查询特定属性（生物体、分辨率、方法等）

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

# 查找人类蛋白质结构
query = AttributeQuery(
    attribute=rcsb_entity_source_organism.scientific_name,
    operator="exact_match",
    value="Homo sapiens"
)
results = list(query())

序列相似性： 查找与给定序列相似的结构

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2. 检索结构数据

访问特定 PDB 条目的详细信息：

基本条目信息：

from rcsbapi.data import Schema, fetch

# 获取条目级数据
entry_data = fetch("4HHB", schema=Schema.ENTRY)
print(entry_data["struct"]["title"])
print(entry_data["exptl"][0]["method"])

聚合物实体信息：

# 获取蛋白质/核酸信息
entity_data = fetch("4HHB_1", schema=Schema.POLYMER_ENTITY)
print(entity_data["entity_poly"]["pdbx_seq_one_letter_code"])

使用 GraphQL 进行灵活查询：

from rcsbapi.data import fetch

# 自定义 GraphQL 查询
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. 下载结构文件

以各种格式检索坐标文件：

PDB 格式（传统文本格式）：https://files.rcsb.org/download/{PDB_ID}.pdb
mmCIF 格式（现代标准）：https://files.rcsb.org/download/{PDB_ID}.cif
BinaryCIF（压缩二进制格式）：使用 ModelServer API 进行高效访问
生物组装体：https://files.rcsb.org/download/{PDB_ID}.pdb1（针对组装体 1）

import requests

pdb_id = "4HHB"

# 下载 PDB 格式
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)

# 下载 mmCIF 格式
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. 处理结构数据

对检索到的结构进行常见操作：

解析和分析坐标： 使用 BioPython 或其他结构生物学库处理下载的文件：

from Bio.PDB import PDBParser

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

# 遍历原子
for model in structure:
    for chain in model:
        for residue in chain:
            for atom in residue:
                print(atom.get_coord())

提取元数据：

from rcsbapi.data import fetch, Schema

# 获取实验细节
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}")

高效处理多个结构：

from rcsbapi.data import fetch, Schema

pdb_ids = ["4HHB", "1MBN", "1GZX"]  # 血红蛋白、肌红蛋白等

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}")

# 显示结果
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']}")

安装官方的 RCSB PDB Python API 客户端：

# 当前推荐包
uv pip install rcsb-api

# 对于遗留代码（已弃用，请使用 rcsb-api）
uv pip install rcsbsearchapi

rcsb-api 包通过 rcsbapi.search 和 rcsbapi.data 模块提供对搜索和数据 API 的统一访问。

搜索药物靶点的结构
分析配体结合位点
比较蛋白质-配体复合物
识别相似的结合口袋

查找用于建模的同源结构
分析序列-结构关系
比较突变体结构
研究蛋白质稳定性和动力学

结构生物学研究

下载结构用于计算分析
构建基于结构的比对
分析结构特征（二级结构、结构域）
比较实验方法和质量指标

检索用于教学的结构
生成分子可视化
探索结构-功能关系
研究进化保守性

PDB ID： 每个结构条目的唯一 4 字符标识符（例如，"4HHB"）。AlphaFold 和 ModelArchive 条目以 "AF_" 或 "MA_" 前缀开头。

mmCIF/PDBx： 使用键值结构的现代文件格式，取代了用于大型结构的传统 PDB 格式。

生物组装体： 大分子的功能形式，可能包含来自不对称单元的多个链副本。

分辨率： 晶体学结构中细节的度量（数值越低 = 细节越高）。高质量结构的典型范围：1.5-3.5 Å。

实体： 结构中的独特分子组分（蛋白质链、DNA、配体等）。

此技能在 references/ 目录中包含参考文档：

references/api_reference.md

全面的 API 文档，涵盖：

详细的 API 端点规范
高级查询模式和示例
数据模式参考
速率限制和最佳实践
常见问题排查

当您需要关于 API 功能、复杂查询构建或详细数据模式信息的深入信息时，请使用此参考。

RCSB PDB 网站： https://www.rcsb.org
PDB-101 教育门户： https://pdb101.rcsb.org
API 文档： https://www.rcsb.org/docs/programmatic-access/web-apis-overview
Python 包文档： https://rcsbapi.readthedocs.io/
数据 API 文档： https://data.rcsb.org/
GitHub 仓库： https://github.com/rcsb/py-rcsb-api

2026 年 1 月 21 日

🇺🇸English

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

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

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RCSB PDB 数据库 API 使用指南：搜索、下载与分析蛋白质三维结构数据

🇨🇳中文介绍

PDB 数据库

概述

何时使用此技能

核心功能

1. 搜索结构

相关 Skills

2. 检索结构数据

3. 下载结构文件

4. 处理结构数据

5. 批量操作

Python 包安装

常见用例

药物发现

蛋白质工程

结构生物学研究

教育和可视化

关键概念

资源

references/api_reference.md

其他资源

🇺🇸English

PDB Database

Overview

When to Use This Skill

Core Capabilities

1. Searching for Structures

2. Retrieving Structure Data

3. Downloading Structure Files

4. Working with Structure Data

5. Batch Operations

Python Package Installation

Common Use Cases

Drug Discovery

Protein Engineering

Structural Biology Research

Education and Visualization

Key Concepts

Resources

references/api_reference.md

Additional Resources

最新 Skills