foldseek

name	foldseek
description	Structure similarity search with Foldseek. Use this skill when: (1) Finding similar structures in PDB/AFDB databases, (2) Structural homology search, (3) Database queries by 3D structure, (4) Finding remote homologs not detected by sequence, (5) Clustering structures by similarity. For sequence similarity, use uniprot BLAST. For structure prediction, use chai or boltz.
license	MIT
category	utilities
tags	["search","structure","database","similarity"]

Foldseek Structure Search

Prerequisites

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

How to run

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

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

# Upload structure to web server
curl -X POST "https://search.foldseek.com/api/ticket" \
  -F "q=@query.pdb" \
  -F "database[]=afdb50" \
  -F "database[]=pdb100"

Option 2: Local installation

# 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/

Option 3: Python API

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"])

Key parameters

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	1000	Max hits to pass through prefilter; reducing this affects sensitivity

Databases

Database	Description	Size
pdb100	PDB chains	~340K structures
afdb50	AlphaFold DB clustered at 50% sequence identity	~53M structures
swissprot	SwissProt structures	~540K structures
cath50	CATH domains	~50K domains

Output format

# 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

Sample output

Successful run

$ foldseek easy-search query.pdb pdb100 results.m8 tmp/
# results.m8 columns: query target pident alnlen mismatch gapopen qstart qend tstart tend evalue bits
query   1abc_A  85.2  120  ...  1e-45  180.5
query   2def_B  72.1  115  ...  1e-32  145.2

Hit identities and E-values above are placeholders; foldseek does not print the [INFO] lines shown by some other tools.

Decision tree

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

Common use cases

Find similar designs

# Compare your design to PDB
foldseek easy-search design.pdb pdb100 similar_natural.m8 tmp/

Novelty check

# Ensure design is novel (low similarity to known)
foldseek easy-search design.pdb afdb50 novelty.m8 tmp/

# Novel if: top hit identity < 30%

Scaffold search

# Find scaffolds for motif grafting
foldseek easy-search motif.pdb pdb100 scaffolds.m8 tmp/ \
  --min-seq-id 0.0 -e 10

---

Verify

wc -l results.m8  # Number of hits

---

Troubleshooting

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

Error interpretation

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.