Enzyme Kinetics (ToolUniverse Claude Skill)

A ToolUniverse agent skill that turns substrate-concentration and initial-velocity data into Km, Vmax, kcat and kcat/Km, and classifies an inhibitor as competitive, uncompetitive or non-competitive.

   
Type Claude Skill (one of ToolUniverse’s pre-built agent skills)
Supplier Zitnik Lab, Harvard Medical School
Availability GA — part of the ToolUniverse skills collection (skills/tooluniverse-enzyme-kinetics/)
Pricing Free / OSS (Apache-2.0); computation is local to the ToolUniverse server — no external API required
Capabilities Read-only — drives ToolUniverse tool calls; no data writes

How to install

This skill calls ToolUniverse tools, so the ToolUniverse MCP server must be installed first (see the ToolUniverse page). Simplest registration:

claude mcp add --transport stdio tooluniverse -- uvx tooluniverse

Then add the skills:

  • Claude Code — install the whole skill collection (the skill resolves as tooluniverse-enzyme-kinetics): 
    npx skills add mims-harvard/ToolUniverse
  • Manual / other agents — copy just this skill directory into your skills folder: 
    git clone https://github.com/mims-harvard/ToolUniverse
cp -r ToolUniverse/skills/tooluniverse-enzyme-kinetics ~/.claude/skills/

    (replace ~/.claude/skills/ with your agent’s skills directory if you are not using Claude Code/Desktop.)

The skill sets disable-model-invocation: true upstream, so invoke it explicitly (e.g. ask Claude to “use the enzyme kinetics skill”) rather than relying on automatic dispatch.

What it does

Runs a five-phase kinetics workflow, primarily through the EnzymeKinetics_calculate tool (operations michaelis_menten and inhibition), with a bundled fit_michaelis_menten.py script for CSV input and Vmax→kcat conversion:

  1. Data preparation — validates that the velocities are genuinely initial rates, that the substrate range actually spans Km, and that units are consistent; asks for the enzyme concentration (needed for kcat) and for at least 5–7 data points.
  2. Michaelis-Menten fitting — nonlinear regression over the concentration/velocity pairs returning Vmax, Km, R² and SSE. A Lineweaver-Burk transform is emitted for reference only, not as the basis of the fit.
  3. Parameter interpretation — Km as substrate affinity, Vmax as saturation velocity, kcat as per-enzyme turnover, and kcat/Km as catalytic efficiency (the specificity constant), benchmarked against the diffusion-limited ~10⁸–10⁹ M⁻¹s⁻¹ range for catalytic perfection.
  4. Inhibition classification — compares velocity curves with and without inhibitor to assign competitive, uncompetitive or non-competitive mechanism and compute Ki.
  5. Quality assurance — flags substrate inhibition, a Km that falls outside the tested concentration range, a missing enzyme concentration, and systematic patterns in the residuals.

A fit is treated as good at R² ≥ 0.98.

Primary use cases: characterising a purified enzyme, mechanism-of-inhibition assignment for a screening hit, Ki determination for lead comparison.

Notes

It is a reasoning layer over ToolUniverse; without the MCP server registered, the tool calls fail. One scope exclusion is explicit upstream: this skill fits your data and is not a lookup of published constants — for that, use the BRENDA tools (BRENDA).

For cell- or organism-level potency rather than enzyme mechanism, Dose-Response Analysis fits the 4PL/Hill model instead. ToolUniverse ships ~68 such skills; other workflows are catalogued separately.

Sources

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