In a book by Robert Copeland, "Enzymes: a Practical Introduction", on the page 358 (paper edition) ie 380 (e-book), there is a Table 11.2 with patterns of dead-end inhibition observed for the BiBi reactions for differing rxn mechanisms. I don't understand the last two rows. Namely, I don't understand why, in ping pong mechanism, when competitive inhibitor for Ax (Ax being one of the substrates with a group "x" to be transferred to substrate B) is added to the rxn mixture and B is varied, we observe uncompetitive inhibition.
An inhibitor is uncompetitive with a substrate if that substrate must bind first in order for the inhibitor to bind. It is easy to see why a substrate B-competitive inhibitor is uncompetitive with substrate A in a Ping Pong mechanism because A must react with the enzyme before the inhibitor can bind. It's harder to understand why a substrate A-competitive inhibitor is uncompetitive with substrate B. It helps to remember that the enzyme reaction is a cycle, with the enzyme going through many turnovers, so B must bind in order for the unliganded enzyme, to which the A-competitive inhibitor binds, to be regenerated.
Personally, I find this terminology confusing. It comes from the use of various types of linear plots, such as double reciprocal plots, with uncompetitive describing the parallel pattern of lines for different inhibitor concentrations. I much prefer to use nonlinear least squares to fit the whole original (not reciprocal) data set at once to each of a set of rate equations describing the various types of competitive (i.e. dead-end) inhibition and see which fits best. With this approach, the whole competitive/noncompetitive/uncompetitive/mixed inhibition business can be replaced with: competitive with A, or competitive with B, or competitive with both A and B. For a Ping Pong Bi reaction, that requires fitting the data to each of 3 rate equations.
I think I see your point. I guess I was stuck with the penultimate row in the table and didn't pay enough attention to the last row, which is as you say much easier to understand.
Thank you very much Dr Shapiro.
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