AlphaFold Database

AlphaFold数据库

Programmatic access to DeepMind's AlphaFold Protein Structure Database (200M+ predicted structures).

通过编程方式访问DeepMind的AlphaFold蛋白质结构数据库（包含2亿+预测结构）。

Quick Reference

快速参考

python

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Fetch structure via Biopython

from Bio.PDB import alphafold_db predictions = list(alphafold_db.get_predictions("P00520")) alphafold_db.download_cif_for(predictions[0], directory="./output")

Direct API call

import requests resp = requests.get("https://alphafold.ebi.ac.uk/api/prediction/P00520") entry_id = resp.json()[0]['entryId'] # AF-P00520-F1

Download structure file

structure_url = f"https://alphafold.ebi.ac.uk/files/{entry_id}-model_v4.cif"

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structure_url = f"https://alphafold.ebi.ac.uk/files/{entry_id}-model_v4.cif"

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When to Use

使用场景

Obtain 3D coordinates for proteins without experimental structures
Assess prediction quality via pLDDT and PAE metrics
Download structure files (mmCIF, PDB) for visualization or docking
Retrieve proteome-scale datasets for computational analysis

获取无实验结构的蛋白质3D坐标
通过pLDDT和PAE指标评估预测质量
下载结构文件（mmCIF、PDB）用于可视化或对接
检索蛋白质组规模的数据集以进行计算分析

Key Concepts

核心概念

Term	Description
UniProt Accession	Protein identifier (e.g., `P00520` ) used to query
AlphaFold ID	Format: `AF-{UniProt}-F{fragment}` (e.g., `AF-P00520-F1` )
pLDDT	Per-residue confidence (0-100); >90 = reliable, <50 = disordered
PAE	Predicted Aligned Error; <5A = high confidence domain positions

See

references/confidence-scores.md

for detailed interpretation guidance.

术语	描述
UniProt Accession	用于查询的蛋白质标识符（例如： `P00520` ）
AlphaFold ID	格式： `AF-{UniProt}-F{fragment}` （例如： `AF-P00520-F1` ）
pLDDT	每个残基的置信度（0-100）；>90表示可靠，<50表示无序
PAE	预测对齐误差；<5Å表示结构域位置的置信度高

请参阅

references/confidence-scores.md

获取详细的解读指南。

File Types

文件类型

File	URL Pattern	Contents
Coordinates	`{id}-model_v4.cif`	Atomic positions (mmCIF)
Confidence	`{id}-confidence_v4.json`	Per-residue pLDDT array
PAE Matrix	`{id}-predicted_aligned_error_v4.json`	Inter-residue error

Base URL:

https://alphafold.ebi.ac.uk/files/

文件类型	URL格式	内容
坐标文件	`{id}-model_v4.cif`	原子位置（mmCIF格式）
置信度文件	`{id}-confidence_v4.json`	每个残基的pLDDT数组
PAE矩阵文件	`{id}-predicted_aligned_error_v4.json`	残基间误差

基础URL：

https://alphafold.ebi.ac.uk/files/

Core Operations

核心操作

Fetch Structure Metadata

获取结构元数据

python

import requests
resp = requests.get(f"https://alphafold.ebi.ac.uk/api/prediction/{uniprot_id}")
metadata = resp.json()[0]
af_id = metadata['entryId']

python

import requests
resp = requests.get(f"https://alphafold.ebi.ac.uk/api/prediction/{uniprot_id}")
metadata = resp.json()[0]
af_id = metadata['entryId']

Download All Files

下载所有文件

Use

scripts/alphafold_utils.py

:

python

from scripts.alphafold_utils import download_alphafold_files
paths = download_alphafold_files("AF-P04637-F1", output_dir="./data")

使用

scripts/alphafold_utils.py

：

python

from scripts.alphafold_utils import download_alphafold_files
paths = download_alphafold_files("AF-P04637-F1", output_dir="./data")

Analyze Confidence

分析置信度

python

from scripts.alphafold_utils import get_plddt_scores
stats = get_plddt_scores("AF-P04637-F1")
print(f"Average pLDDT: {stats['mean']:.1f}")

python

from scripts.alphafold_utils import get_plddt_scores
stats = get_plddt_scores("AF-P04637-F1")
print(f"Average pLDDT: {stats['mean']:.1f}")

Bulk Proteome Access

批量蛋白质组访问

bash

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Google Cloud Storage

gsutil ls gs://public-datasets-deepmind-alphafold-v4/ gsutil -m cp "gs://public-datasets-deepmind-alphafold-v4/proteomes/proteome-tax_id-9606-*.tar" ./


See `references/bulk-access.md` for BigQuery queries and batch processing.

gsutil ls gs://public-datasets-deepmind-alphafold-v4/ gsutil -m cp "gs://public-datasets-deepmind-alphafold-v4/proteomes/proteome-tax_id-9606-*.tar" ./


请参阅`references/bulk-access.md`获取BigQuery查询和批量处理相关内容。

Caveats

注意事项

Predictions, not experiments: Verify critical findings experimentally
Confidence matters: Always check pLDDT before using regions
Single chains only: No multimers or complexes
No ligands: Missing cofactors, ions, PTMs

仅为预测结果，非实验数据：关键发现需通过实验验证
置信度至关重要：使用区域前务必检查pLDDT
仅支持单链：不包含多聚体或复合物
无配体信息：缺少辅因子、离子、翻译后修饰（PTMs）

Setup

环境搭建

bash

pip install biopython requests numpy matplotlib pandas scipy

bash

pip install biopython requests numpy matplotlib pandas scipy

Optional: pip install google-cloud-bigquery gsutil

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alphafold-database

Original

Translation

AlphaFold Database

AlphaFold数据库

Quick Reference

快速参考

Fetch structure via Biopython

Fetch structure via Biopython

Direct API call

Direct API call

Download structure file

Download structure file

When to Use

使用场景

Key Concepts

核心概念

File Types

文件类型

Core Operations

核心操作

Fetch Structure Metadata

获取结构元数据

Download All Files

下载所有文件

Analyze Confidence

分析置信度

Bulk Proteome Access

批量蛋白质组访问

Google Cloud Storage

Google Cloud Storage

Caveats

注意事项

Setup

环境搭建

Optional: pip install google-cloud-bigquery gsutil

Optional: pip install google-cloud-bigquery gsutil

Links

相关链接