foldseek

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English

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Translation

Chinese

Foldseek Structure Search

Foldseek 结构搜索

Prerequisites

前置要求

Requirement	Minimum	Recommended
Python	3.8+	3.10
RAM	8GB	16GB
Disk	10GB	50GB (for local databases)

要求	最低配置	推荐配置
Python	3.8+	3.10
内存	8GB	16GB
磁盘	10GB	50GB（用于本地数据库）

How to run

运行方法

Note: Foldseek can run locally or via web server. No GPU required.

注意：Foldseek可在本地运行或通过Web服务器运行，无需GPU。

Option 1: Web Server (Quick; rate-limited, use sparingly)

选项1：Web服务器（快速；有调用频率限制，谨慎使用）

bash

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bash

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Upload structure to web server

curl -X POST "https://search.foldseek.com/api/ticket"
-F "q=@query.pdb"
-F "database[]=afdb50"
-F "database[]=pdb100"

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curl -X POST "https://search.foldseek.com/api/ticket"
-F "q=@query.pdb"
-F "database[]=afdb50"
-F "database[]=pdb100"

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Option 2: Local installation

选项2：本地安装

bash

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bash

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Install Foldseek

conda install -c conda-forge -c bioconda foldseek

Search PDB

foldseek easy-search query.pdb /path/to/pdb100 results.m8 tmp/

Search AlphaFold DB

foldseek easy-search query.pdb /path/to/afdb50 results.m8 tmp/

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foldseek easy-search query.pdb /path/to/afdb50 results.m8 tmp/

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Option 3: Python API

选项3：Python API

python

import subprocess
import pandas as pd

def foldseek_search(query_pdb, database, output="results.m8"):
    """Run Foldseek search."""
    subprocess.run([
        "foldseek", "easy-search",
        query_pdb, database, output, "tmp/",
        "--format-output", "query,target,pident,alnlen,evalue,bits"
    ])
    return pd.read_csv(output, sep="\t",
                       names=["query", "target", "pident", "alnlen", "evalue", "bits"])

python

import subprocess
import pandas as pd

def foldseek_search(query_pdb, database, output="results.m8"):
    """运行Foldseek搜索。"""
    subprocess.run([
        "foldseek", "easy-search",
        query_pdb, database, output, "tmp/",
        "--format-output", "query,target,pident,alnlen,evalue,bits"
    ])
    return pd.read_csv(output, sep="\t",
                       names=["query", "target", "pident", "alnlen", "evalue", "bits"])

Key parameters

关键参数

Parameter	Default	Description
`--min-seq-id`	0.0	Minimum sequence identity
`-e`	0.001	E-value threshold
`--alignment-type`	2	0=3Di, 1=TM, 2=3Di+AA
`--max-seqs`	300	Max hits to pass through prefilter; reducing this affects sensitivity

参数	默认值	说明
`--min-seq-id`	0.0	最小序列一致性
`-e`	0.001	E值阈值
`--alignment-type`	2	0=3Di, 1=TM, 2=3Di+AA
`--max-seqs`	300	预过滤后保留的最大命中数；降低该值会影响灵敏度

Databases

数据库

Database	Description	Size
`pdb100`	PDB clustered at 100%	~200K structures
`afdb50`	AlphaFold DB at 50%	~67M structures
`swissprot`	SwissProt structures	~500K structures
`cath50`	CATH domains	~50K domains

数据库	说明	大小
`pdb100`	按100%一致性聚类的PDB库	~200K个结构
`afdb50`	按50%一致性聚类的AlphaFold DB库	~67M个结构
`swissprot`	SwissProt结构库	~500K个结构
`cath50`	CATH结构域库	~50K个结构域

Output format

输出格式

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results.m8 (tabular)

query target pident alnlen evalue bits query 1abc_A 85.2 120 1e-45 180.5 query 2def_B 72.1 115 1e-32 145.2

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query target pident alnlen evalue bits query 1abc_A 85.2 120 1e-45 180.5 query 2def_B 72.1 115 1e-32 145.2

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Sample output

示例输出

Successful run

运行成功示例

$ foldseek easy-search query.pdb pdb100 results.m8 tmp/
[INFO] Loading database: pdb100 (194,527 entries)
[INFO] Searching...
[INFO] Found 127 hits

Top 5 hits:
1. 1abc_A - 85.2% identity, E=1e-45
2. 2def_B - 72.1% identity, E=1e-32
3. 3ghi_C - 68.5% identity, E=1e-28
4. 4jkl_A - 55.3% identity, E=1e-18
5. 5mno_B - 42.1% identity, E=1e-10

$ foldseek easy-search query.pdb pdb100 results.m8 tmp/
[INFO] Loading database: pdb100 (194,527 entries)
[INFO] Searching...
[INFO] Found 127 hits

前5个命中结果：
1. 1abc_A - 85.2%一致性, E=1e-45
2. 2def_B - 72.1%一致性, E=1e-32
3. 3ghi_C - 68.5%一致性, E=1e-28
4. 4jkl_A - 55.3%一致性, E=1e-18
5. 5mno_B - 42.1%一致性, E=1e-10

Decision tree

决策树

Should I use Foldseek?
│
├─ What are you searching?
│  ├─ By 3D structure → Foldseek ✓
│  ├─ By sequence → Use BLAST (uniprot skill)
│  └─ Both → Run both, compare results
│
└─ What do you need?
   ├─ Find structural homologs → Foldseek ✓
   ├─ Remote homolog detection → Foldseek ✓
   ├─ Structural clustering → Foldseek ✓
   └─ Functional annotation → Cross-reference with UniProt

是否应该使用Foldseek?
│
├─ 你要搜索什么?
│  ├─ 通过3D结构 → Foldseek ✓
│  ├─ 通过序列 → 使用BLAST (uniprot skill)
│  └─ 两者都要 → 同时运行两者，对比结果
│
└─ 你需要实现什么目标?
   ├─ 查找结构同源物 → Foldseek ✓
   ├─ 远源同源物检测 → Foldseek ✓
   ├─ 结构聚类 → Foldseek ✓
   └─ 功能注释 → 与UniProt交叉参考

Common use cases

常见使用场景

Find similar designs

查找相似设计

bash

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bash

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Compare your design to PDB

将你的设计与PDB库对比

foldseek easy-search design.pdb pdb100 similar_natural.m8 tmp/

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foldseek easy-search design.pdb pdb100 similar_natural.m8 tmp/

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Novelty check

新颖性检查

bash

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bash

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Ensure design is novel (low similarity to known)

确保设计具有新颖性（与已知结构相似度低）

foldseek easy-search design.pdb afdb50 novelty.m8 tmp/

Novel if: top hit identity < 30%

若顶部命中结果的一致性 < 30%，则视为新颖

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Scaffold search

支架搜索

bash

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bash

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Find scaffolds for motif grafting

查找用于基序移植的支架

foldseek easy-search motif.pdb pdb100 scaffolds.m8 tmp/
--min-seq-id 0.0 -e 10

---

foldseek easy-search motif.pdb pdb100 scaffolds.m8 tmp/
--min-seq-id 0.0 -e 10

---

Verify

验证

bash

wc -l results.m8  # Number of hits

bash

wc -l results.m8  # 命中结果数量

Troubleshooting

故障排除

No hits: Lower e-value threshold, try larger database Too many hits: Increase min-seq-id threshold Slow search: Use smaller database

无命中结果：降低E值阈值，尝试更大的数据库 命中结果过多：提高最小序列一致性阈值 搜索缓慢：使用更小的数据库

Error interpretation

错误解读

Error	Cause	Fix
`Database not found`	Wrong path	Check database location
`Invalid PDB`	Malformed structure	Validate PDB format
`Out of memory`	Large database	Use more RAM or web server

Next: Download hits with

pdb

skill → use for scaffold design.

错误	原因	解决方法
`Database not found`	路径错误	检查数据库位置
`Invalid PDB`	结构格式错误	验证PDB格式
`Out of memory`	数据库过大	使用更大内存或Web服务器

下一步：使用

pdb

技能下载命中结果 → 用于支架设计。