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feat: optimize CASTp SASA with KDTree, add sequence input to CASTp + Structure Prep, ESMFold integration for unknown genes
Backend: - castp.py: Replace O(n²) adjacency loop with scipy KDTree O(n log n), compute SASA on first model only - castp router: Accept pdb_id, sequence (auto-ESMFold), or pdb_text input - structure_prep.py: Add esmfold_predict() for raw sequences via HF Inference API - structure_prep router: Accept sequences for full pipeline (ESMFold → chain detection → repair → cleanup → pockets) Frontend: - CASTp page: PDB ID / amino acid sequence toggle, textarea with residue counter - Structure Prep page: PDB ID / amino acid sequence toggle, progress bar with ESMFold step - api.ts: Add runCastpSequence(), runStructurePrepSequence(), sequence_source on CastpResulte21c532
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feat: add CASTp pockets, SWISS-MODEL, ESMFold + fix Dockerfiles
- CASTp pocket analysis: Biopython SASA + grid-based cavity detection, 3 endpoints - SWISS-MODEL Repository: query SMR API for homology models + experimental structures - ESMFold structure prediction: HF Inference API proxy, async job with progress - Fix root Dockerfile: add g++/libgl1/libgomp1/libopenblas-dev/libxml2/libxslt1.1 - Fix primer3-py quoting bug in both Dockerfiles (shell redirect issue) - Wire 3 routers into main.py, add API client functions, update analyze hub - TypeScript clean, zero errorsbe36a29