Biological data is fragmented and non-textual
Language models excel at text, but structural biology lives in scattered metadata, 3D coordinates, and complex experimental records.
Fragmented knowledge
Hidden similarities
Non-textual data
First, make PDB queryable
Semantic search that understands biochemical context, not just keywords
Ask natural questions
Instead of rigid BLAST queries or keyword filters, describe what you need: binding sites, crystallization conditions, ligand contexts, functional properties.
Our search engine understands the semantic relationships between experimental metadata, structural features, and biological functions, bridging scattered PDB annotations into coherent, ranked results.
PDB Semantic Search
Query 240,000+ protein structures using natural language.
Get ranked results that understand biochemical context, not just exact keyword matches.
Built for experts: results include source snippets and direct provenance links.
Beyond search,the AI operating layer for biology
Semantic search solves retrieval.
But computational biology needs more: navigating 3D structures, connecting experimental context to design decisions, and navigating biochemical constraints.
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