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KatalistSeek

KatalistSeek — a grounded reasoning layer over fragmented enzyme/reaction databases.

Core trick

Answers reaction and enzyme questions only from live database calls, tagging each claim with its source record and refusing when retrieval fails.

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Description

KatalistSeek — a grounded reasoning layer over fragmented enzyme/reaction databases. Curated knowledge databases about a biochemical pathway or enzyme are scattered all over the internet — PubChem, Rhea, UniProt, COCONUT, AlphaFold, ChEBI. The questions a researcher actually cares about are: how do I make this molecule, and which enzyme catalyses the step? and what else might this enzyme accept? Answering either today means hours of manual cross-referencing to ensure grounded structure and honest provenance. KatalistSeek is a tool that will hopefully fill that gap by providing grounded and a provenance-tagged reasoning layer that collapses that work into minutes. Two modes share one core — make a molecule (target → natural-product gate → grounded producing reactions → candidate enzymes → homologue family → binding-pocket fit) and substrate scope of an enzyme (enzyme → its ortholog family, how the substrate drifts across species, its literature, its 3-D pocket, and a discovery step that proposes candidate promiscuous substrates from structurally-similar natural products — separating those already documented in a reaction from purely structural look-alikes). What makes the output trustworthy enough to act on is one non-negotiable rule: no EC number, accession, or catalytic residue is ever emitted unless a live database call returned it in the current session. Every biological claim carries a provenance handle back to the exact record that produced it; when retrieval fails, the tool says so and stops — it never backfills from memory. On naringenin it recovers chalcone isomerase from a live call and ranks the fold family so that catalytically inactive fold-homologues fall below the true isomerases — showing that conservation is not activity — while refusing to invent a precursor for a xenobiotic that has none.
jouell3/KatalistSeek★ 00 forksPythonMITCreated Jul 7, 2026 · last push Jul 18, 2026

README excerpt

# KatalistSeek

**A grounded, provenance-tagged, interrogable reasoning layer over fragmented enzyme/reaction databases.**

KatalistSeek has been developped to help biologists and biochemists answer two questions — *"how do I make this molecule, and which enzyme could catalyse the step?"* and *"what is the substrate scope of this enzyme?"* — collapsing days of manual cross-referencing into minutes. It **retrieves and reasons; it does not predict.** The differentiator is not a new model: generators (RetroRules, RetroBioCat, Selenzyme) and predictors (ESP, SPEPP) already exist and are strong. KatalistSeek **consumes them as tools** and adds the missing layer: **mechanistic reasoning with citations, confidence grading, and honest refusal.**

Every biological claim it surfaces carries a **provenance handle** — the exact tool call and record that produced it — so a claim is only ever as strong as its source.

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## THE ONE RULE

> **Never emit an EC number, accession, or catalytic residue that was not returned by a live database call.** No identifier from model recall — ever.

If retrieval fails, the correct behaviour is to say *"retrieval failed"* and stop, not to backfill from memory. This is the project's non-negotiable design constraint, and it is what makes the output trustworthy enough to act on. Model reasoning is always **advisory over grounded data** — it ranks, explains, and grades confidence, but it can never invent an identifier.

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## What it does

Two modes shar

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