tooluniverse-enzyme-kinetics

Fit the Michaelis-Menten equation v = Vmax·[S]/(Km+[S]) to your substrate concentrations and initial velocities using nonlinear regression. The nonlinear fit values should be reported, not the Lineweaver-Burk linearization, which distorts error by over-weighting low-substrate points.

Compare fitted parameters with and without inhibitor: competitive inhibition raises apparent Km while Vmax stays unchanged, uncompetitive lowers both Km and Vmax, and non-competitive lowers Vmax with Km roughly unchanged. Ki quantifies inhibitor potency, with lower values meaning stronger inhibition.

No, kcat equals Vmax divided by the total molar enzyme concentration, so it cannot be computed from velocity data alone. Without [E], only Vmax and the Vmax/Km ratio on the velocity scale are available.

The double-reciprocal Lineweaver-Burk transformation distorts the error structure by over-weighting low-substrate points, biasing Km and Vmax estimates. It is suitable only for visualization and sanity checks; nonlinear regression gives the reportable parameters.

The model assumes a single substrate, initial-rate steady-state conditions, and one active site. Allosteric sigmoidal enzymes need the Hill equation, substrate inhibition breaks the fit, and Km estimates are unreliable if Km falls outside the tested substrate range.