Enzyme Kinetics Tools

Two tools for fitting enzyme kinetics data from substrate depletion time courses.

Tools

1. Michaelis-Menten Fitter (michaelis_menten_fitter.py)

Simple Dash app for quick Michaelis-Menten fitting. Paste data from Excel, get Km and Vmax with confidence intervals.

• Nonlinear least-squares curve fitting
• Lineweaver-Burk, Eadie-Hofstee, and Hanes-Woolf linearizations
• Interactive Plotly plots
• Copy-paste from Excel or CSV

pip install dash plotly pandas numpy scipy
python michaelis_menten_fitter.py
# Open http://127.0.0.1:8050

2. Advanced Bayesian Enzyme Kinetics (multimodel_enzyme_kinetics_app.py)

Streamlit app for multi-model Bayesian fitting of substrate depletion curves using PyMC and ODE integration.

Supported models:

• Michaelis-Menten (sQSSA and tQSSA formulations)
• Hill equation (cooperative binding)
• Competitive, noncompetitive, and uncompetitive inhibition
• Substrate inhibition

Features:

• Global fitting across multiple substrate concentrations
• Bayesian parameter estimation with posterior distributions (PyMC/NUTS)
• Automatic model comparison (WAIC, LOO)
• ODE-based fitting (not initial-rate approximations)
• Residual analysis and diagnostic plots

pip install streamlit numpy pandas scipy plotly pymc pytensor arviz
streamlit run multimodel_enzyme_kinetics_app.py

Requirements

• Python 3.10+
• See individual tool sections for dependencies