Bio Structure Annotation
Structure prediction and structure-based annotation.
Instructions
Tool guides and versions: docs/README.md.
- Run a fast embedding screen with TM-Vec to triage candidate proteins by remote homology before incurring structure-prediction cost.
- Predict structures on a GPU node. AlphaFold3 is intentionally not part of this stack (non-commercial license, large VRAM footprint, no clear quality gap for the workflows in this repo). Use:
- Boltz-2 (MIT license; CUDA; NVIDIA cuEquivariance kernels) as the default predictor — joint structure-and-affinity, ~1000× faster than FEP for binding-affinity estimation, comparable accuracy to AF3 on benchmarked complexes.
- ColabFold v1.5.5+ with an MMseqs2-GPU MSA backend when a wider MSA than Boltz-2 builds is required (≈31.8× faster MSA generation versus the standard AF2 pipeline; Nature Protocols 2025, DOI: 10.1038/s41596-024-01060-5).
- ESMFold for fast monomer pre-screening only (15–20 GB VRAM; lower accuracy than Boltz-2).
- Search predicted or experimental structures with Foldseek v9+. Use
--gpu 1on CUDA Turing or newer for the ProstT5-backed search (4–27× speedup). Consider Foldseek-Multimer when complex-vs-complex search is needed. - Annotate hits and route high-value unknowns back to
/bio-annotationfor sequence-side context, or to comparative analyses via/bio-protein-clustering-pangenome. - Build and validate commands with
scripts/run_structure_annotation.py. Public MSA services receive biological sequences;--use-msa-serveris rejected unless the user explicitly approved upload with--approve-public-msa-upload.
Quick Reference
| Task | Action |
|---|---|
| Validate and plan | uv run --script skills/bio-structure-annotation/scripts/run_structure_annotation.py ... |
Input Requirements
Prerequisites:
- Tools declared in the project's pinned Pixi environment. See
docs/README.mdfor expected tools. - Reference DB root: set
BIO_DB_ROOTto the project or site-local database directory. - Protein FASTA inputs are available. Inputs:
- proteins.faa (FASTA protein sequences)
Output
- results/bio-structure-annotation/structures/
- results/bio-structure-annotation/structure_hits.tsv
- results/bio-structure-annotation/structure_report.md
- results/bio-structure-annotation/logs/
Quality Gates
- Prediction success rate meets project thresholds.
- Search hit thresholds meet project thresholds.
- On execution failure, preserve logs and report the failed command; retry only after diagnosing the cause and recording the changed parameters. Report unmet biological thresholds as results; never tune parameters solely to pass a gate.
- Verify proteins.faa is non-empty and amino acid encoded.
- Verify Foldseek databases exist under the reference root.
- GPU Foldseek searches use a database produced by
makepaddedseqdb. - Public MSA upload has explicit user approval recorded before
--use_msa_serveris used.