Signal S (clamped/externally controlled) drives production of species A, which is converted reversibly to species B through a saturable enzyme step. B feeds back to inhibit the production of A from S, closing a single negative-feedback loop: S → A → B ⊣ A. Unlike the antithetic-feedback (X-mediated) design, a direct feedback loop like this one generally gives only approximate homeostasis — watch whether B truly returns to its starting value after each step in S, or merely comes close.
Drag across the plot to inspect values at a given time. Adjust the controls below and watch this graph update.
Compare "B at t = 0" with "B at end of run" (S returns to the same value at both times by default). If this were perfect adaptation the two numbers would match exactly, as they do in the antithetic-feedback (X-mediated) model. Here they land close but not identical — the signature of a direct negative feedback loop, which buys approximate, not exact, homeostasis.
Reaction network: S → A, rate = k1S(1−A) − k2AB (inhibited by B) · A ⇆ B, reversible saturable kinetics (Vf, Vr, Kmf, Kmr)
This ModelBrick is a variant built from the same article as the antithetic (X-mediated) perfect-adaptation model: a three-node network in which signal S drives species A, A interconverts with B through a saturable enzymatic step, and B feeds back to suppress A's production — a direct, single negative-feedback loop rather than the article's separate integral-feedback pathway. S is stepped up in four increments of 0.2 and then back down in four decrements of 0.2, letting you compare A and B's response on the way up against the way down. Originally built and simulated in VCell and exported as SBML.