Foldseek Structural Search
Google DeepMindOfficialPublished by Google DeepMind
- Skill
- Workflow
- Science and research
- Apache-2.0
- Low risk
- Has scripts
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill enables users to perform structural similarity searches for proteins by submitting a 3D coordinate file (such as .pdb, .cif, or .mmcif) to the Foldseek API. It compares the query structure against established databases like PDB, AlphaFold, and CATH to identify structural homologues. The skill processes the search, interprets key alignment metrics such as probability and query coverage, and provides a functional analysis of the top matches, saving results in both human-readable Markdown and machine-readable JSON formats.
What it does
- Submits 3D protein structure files to the Foldseek API for structural comparison.
- Supports searches against databases including PDB, AlphaFold, CATH, and MGnify.
- Generates a Markdown table summarizing top structural hits and alignment metrics.
- Saves detailed search results into a local JSON file for further analysis.
- Interprets alignment metrics like probability, query coverage, and E-value.
- Synthesizes functional information from structural matches to suggest potential protein roles.
When to use it
- When you have a physical 3D protein structure file and need to find structurally similar proteins.
- When you need to identify potential protein functions based on structural homology.
- When you want to compare a protein structure against specific databases like AlphaFold or PDB.
- When you require a structured report of structural matches for further research.
Advantages
- Automates the submission and retrieval process for structural protein searches.
- Provides clear interpretation of structural alignment metrics.
- Enables functional analysis by identifying homologous protein families.
- Produces both human-readable summaries and data-rich files for downstream workflows.
Usage examples
- “Find structural matches for my protein structure file located at ./data/protein_model.pdb using the AlphaFold database.”
- The agent validates the file, queries the AlphaFold database, and returns a summary of the top structural matches with their functional annotations.
- “Search for structural homologues of structure.cif in the PDB and CATH databases.”
- The agent performs the search against the specified databases and provides a Markdown table detailing the structural similarity and functional context of the results.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/google-deepmind/foldseek-structural-search/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip foldseek-structural-search.zip -d .agents/skills
Documentation by Google DeepMind
Prerequisites
uv: Read theuvskill and follow its Setup instructions to ensureuvis installed and on PATH.User Notification: If .licenses/foldseek_structural_search_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://search.foldseek.com/search and https://github.com/steineggerlab/foldseek, then (2) create the file recording the notification text and timestamp.
Goal
Submit a user-provided 3D protein structure file (.cif, .mmcif, or .pdb)
to the Foldseek web server API to find structurally similar proteins. Report the
top structural hits, interpret key alignment metrics, summarize the inferred
protein functions, save the Markdown-formatted table to a .md file, and save
the full detailed results to a local JSON file.
Core Rules
File Requirement: This tool absolutely cannot search by sequence, name, or accession ID. It strictly requires a
.pdb,.cif, or.mmciffile path.Strict Validation: Never bypass the input validation or the database allowlist check.
Do Not Parse the JSON: Rely entirely on the generated
.mdfile for your immediate summary. The JSON is saved purely for subsequent, specialized tool use.No Raw Parsing: Do not attempt to parse or read the raw 3D coordinates yourself; always pass the file to the script.
Notification: If this skill is used, ensure this is mentioned in the output.
Instructions
Strict Input Validation: Verify that the user has explicitly provided a valid path to a
.cif,.mmcif, or.pdbfile in their workspace.If the user provided a protein name, an amino acid sequence, or an accession ID (e.g., a UniProt ID) but NO downloaded structure file, halt immediately. Do not run the script.
Inform the user that Foldseek requires a physical 3D coordinate file, and suggest downloading the structure first (e.g., using the AlphaFold fetch tool).
Database Validation: Check if the user requested specific databases to search.
Allowed List:
afdb50,afdb-swissprot,pdb100,BFVD,mgnify_esm30,cath50,gmgcl_id,bfmd,afdb-proteome.If the user requests a database NOT on this list, halt immediately. Do not run the script. Inform the user that the database is unsupported and provide them with the allowed list.
Generate File Names: Generate descriptive output file names for both the JSON data and the Markdown table based on the input file (e.g.,
proteinA_foldseek_results.jsonandproteinA_foldseek_results.md).Execute the python script based on the user's request, redirecting the standard output into your generated
.mdfile:Default (No databases specified):
uv run scripts/search.py <path-to-file> -o <generated-filename.json> > <generated-filename.md>Custom (Valid databases specified):
uv run scripts/search.py <path-to-file> -o <generated-filename.json> --databases <db1,db2,db3> > <generated-filename.md>
The script will query the databases, save the full JSON payload, and write a Markdown-formatted table to your specified
.mdfile.Read the Results: Open and read the newly generated
.mdfile carefully to view the Markdown table.Interpret the Metrics: Summarize the top 3 to 5 structural matches that have meaningfull annotations for the user. When reporting, assess the match quality using these specific fields:
Prob (Probability): Values approaching 1.0 (100%) indicate extreme confidence that the fold is a true structural homologue.
Q-Cov (Query Coverage): High percentages mean the match covers the majority of the query protein's overall shape, rather than just a small local motif.
E-value & Seq Identity: Use these to provide additional evolutionary context.
Perform Functional Analysis: Analyze the text descriptions embedded within the
Target IDcolumn for the reported matches.Explicitly report the specific protein names/functions of the top structural homologues.
Provide a synthesized overview summarizing the entire variety of different functions, domains, or protein families found across the whole list of homologues (e.g., "Most hits are portal proteins, but there is also a distinct cluster of viral capsid matches...").
Explicitly inform the user of both newly created files (
.jsonand.md) and their locations so they can be seamlessly used in subsequent analysis steps.
* If the API returns an error or the file is missing, inform the user clearly
and ask them to verify the file path.
Files
- ATTRIBUTION.mdAdded by AutoGineer934 B
- LICENSELicence file added by AutoGineer11.1 KiB
- SKILL.md5.2 KiB
- references/citation.bib445 B
- scripts/search.pyScript7.8 KiB
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs Python
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Attribution and licence
- Published by
- Google DeepMind
- Publisher
- Google DeepMind (Official)
- Source
- google-deepmind/science-skills · skills/foldseek_structural_search · commit 4de6786
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download foldseek-structural-search.zip