alphagenome_atlas_webs…
Constructs deep-links and URLs for the AlphaGenome Atlas website. Supports generating…
Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene
$ npx -y skills add google-deepmind/science-skills --skill alphafold_database_fetch_and_analyze --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/alphafold_database_fetch_and_analyzeContext preview
The summary Claude sees to decide when to auto-load this skill.
Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene
name: alphafold-database-fetch-and-analyze description: > Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.
1. **`uv`**: Read the `uv` skill and follow its Setup instructions to ensure `uv` is installed and on PATH. 2. **User Notification**: If .licenses/alphafold_database_fetch_and_analyze_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://alphafold.ebi.ac.uk/, then (2) create the file recording the notification text and timestamp.
Downloads AlphaFold predicted structures (mmCIF) and Predicted Aligned Error (PAE) matrices from the AlphaFold Database for a given UniProt ID, then performs automated heuristic analysis on structural confidence (pLDDT), intrinsically disordered regions, rigid domain boundaries, and inter-domain flexibility.
**Do NOT use when:**
UniProt ID) — ask them to look up the ID on [UniProt](https://www.uniprot.org).
database rather than accessing the database directly. The scripts automatically enforce the required rate limit gracefully.
yourself; always rely on the output provided by the script.
**1. Fetch Structure Files**
Downloads the `.cif` structure file, `_predicted_aligned_error.json`, and API metadata JSON (`-metadata.json`) for a UniProt ID. Handles fragment fallback for very large proteins.
Examples:
uv run scripts/fetch_structure.py P00520 -o /path/to/output/ uv run scripts/fetch_structure.py P04637 -o /path/to/custom_results/
Always specify `-o` with an absolute path or a path relative to the user's project root, never a path relative to the skill directory.
**2. Analyze pLDDT Confidence**
Reads pLDDT confidence metrics from a saved AFDB metadata JSON file (produced by `fetch_structure.py`) and prints a heuristic confidence assessment (structured, disordered, mixed).
Example:
uv run scripts/analyze_plddt.py ./data/AF-P00520-F1-metadata.json
**3. Analyze PAE / Domain Boundaries**
Reads a downloaded PAE JSON file and detects rigid domain boundaries using a sliding-window PAE heuristic.
Example:
uv run scripts/analyze_pae.py ./data/AF-P00520-F1-predicted_aligned_error_v6.json
The script prints analysis to stdout. Read it carefully and synthesize the results for the user:
1. **Isoform / Large Protein Warning (MANDATORY):** Check the script output for any `[!] WARNING` lines. If the script reports that no canonical entry was found and an isoform was used, or if the protein is very large (>2700 AAs), you **MUST** prominently relay this warning to the user. Do not omit this warning. 2. **Synthesize the Structural Analysis**: Combine the "pLDDT Conclusion" and the "PAE Structural Conclusion" into a single, cohesive overall summary. Describe the protein's overall folding confidence, the presence of disordered regions, and its rigid domain layout. 3. Highlight the supporting metrics:
(especially Very Low vs. Very High).
specific residue ranges). 4. **Explicit Disorder Warning:** If the analysis concludes that the protein is highly intrinsically disordered (e.g., high fraction of <50 pLDDT or lack of rigid domains), issue a separate, prominent warning. Advise the user against proceeding with whole-protein downstream structural analysis (like Foldseek or docking). If small ordered domains exist amidst the disorder, advise the user to restrict any future analysis strictly to those specific residue boundaries. 5. Remind the user that per-residue pLDDT is embedded in the B-factor column of the downloaded mmCIF file.
A collection of agent skills for scientific research tasks, spanning genomics, structural biology, cheminformatics, literature search, and more.
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