foldseek
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.
npx skills add majiayu000/claude-skill-registry --skill foldseek-adaptyvbio-protein-design-skill-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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) ```bash # 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 ```bash # 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 ```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", "ev
- Prerequisites
- How to run
- Option 1: Web Server (Quick; rate-limited, use sparingly)
- Option 2: Local installation
- Option 3: Python API
- Key parameters
- Databases
- Output format
- Sample output
- Successful run
- Decision tree
- Common use cases
- Find similar designs
- Novelty check
Upload structure to web server curl -X POST "https://search.foldseek.com/api/ticket" \ 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/ Compare your design to PDB foldseek easy-search design.pdb pdb100 similar_natural.m8 tmp/
What does the foldseek skill do?
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.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill foldseek-adaptyvbio-protein-design-skill-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.