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Allosteric regulation and feedback loops

Build on your understanding of the two-step process of enzyme catalysis and the Michaelis-Menten Equation as you uncover how allosteric regulation influences enzymatic activity. Discover the role of activators and inhibitors, and unravel the mystery of feedback loops in multi-step processes like glycolysis. Created by Ross Firestone.

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Video transcript

Voiceover: So, today we're going to talk about how allosteric regulation can affect enzyme kinetics. But first, let's review the idea that an enzyme's catalysis can be divided into two steps. First, the binding of enzymes to substrate, and second the formation of products. And using this information, we can derive the Michaelis-Menten Equation, which allows us to look at an enzyme's rate of product formation with respect to substrate concentration. Also remember substrates will typically bind to enzymes at the active site. So what do we mean when we say allosteric regulation? Well, we know that enzymes usually have an active site where substrates combined, but enzymes can also have what we call an allosteric site. And these allosteric sites are places on the enzyme where any enzyme regulator can bind. And I've put this star here just to point out that allosteric sites can be anywhere on a enzyme. There can be any number of them as well. So what do we mean when we say regulators? Well, we generally say there are two types of regulators. There are allosteric activators, which increase enzymatic activity and activate them, and allosteric inhibitors, which decrease ezymatic activity and inhibit the enzymes. So let's take a look at what we mean by increasing and decreasing ezymatic activity from a kinetic perspective. So, remember the Michaelis-Menten equation, and if we're assuming substrate concentration to be constant, then there are two ways to influence enzymatic activity, or VO. In this first graph, I've drawn three different curves. The blue curve represents the enzyme functioning without an allosteric regulator at all. The red curve represents the enzyme with an allosteric inhibitor, and the green curve represents the enzyme with an allosteric activator. And in this example, activators and inhibitors affect VO by either increasing or decreasing KM since the V max values seem to be pretty close between the three curves. So an activator here might be decreasing KM. Now, in this next example, we have the same three colored curves, but instead of KM changing significantly, the regulators seem to be changing V max. With the activator increasing the V max value. So, now that we've talked about activators and inhibitors, let's introduce the idea of the feedback loop. And, the basic idea is that a feedback loop is when you have downstream products regulating upstream reactions. And I understand this can be a mouthful, so let me show you this little reaction sequence, where we have A forming B through reaction one, and B forming C through reaction two, and so on and so on. Now let's say that molecule F acted as an activator for the ezyme powering reaction one. So it had a positive effect on enzyme one's activity. Now we would call this a positive feedback loop since molecule F increases the rate of reaction one, which then causes even more F to be made, since we've increased the increase the rate of formation of molecule F. Now, let's say that molecule F had a negative effect on enzyme one, we would call this a negative feedback loop since molecule F decreases the rate of reaction one, which leads to a decrease in the rate of formation in molecule F. So, let's look at an example of a feedback loop just to really drive home the point if you're still confused. Now, phosphofructokianase is an enzyme involved in glycolysis, and it catalyzes the conversion of fructose six phosphate and ATP to form fructose one six bisphosphate and ADP. Now, remember that glycolysis is a metabolic process that cells use to generate ATP. So, here, our molecule F, or downstream regulator from the last example, is ATP. and it turns out that ATP is an allosteric inhibitor of phosphofructokianase. And this makes sense because if ATP is at a high level, it's like the cell saying "We have ATP and we don't really need any more. "And we don't need phosphofructokianase "to push glycolysis along." So this would be a good example of a negative feedback loop. Since making ATP slows down glycolysis, and thus slows down the rate of ATP production. Now, because ATP is both an allosteric regulator and a substrate for phosphofructokianase, we can call it a homotropic inhibitor, which is a new term, and we call it a homotropic inhibitor because the substrate and the regulator are the same molecule. Now AMP, which is used up ATP, is an activator for phosphofructokianase, and this also makes sense because if AMP levels are high, then ATP levels are probably low. And it's like the cell saying "We need ATP." So we do need phosphofructokianase to push glycolysis along. Now, since AMP is a regulating molecule but not an active site substrate for phosphofructokianase it would be considered a heterotropic activator since the substrate and regulator are different. Now, the final point I want to make is that specific reactions make excellent control points for long, multistep processes. And remember that glycolysis is a ten step sequence. So why is there so much regulation going on for this one step? Well, this reaction in particular has a very negative delta G, and it's actually negative 4.5 kCal per mol. And that means that it's not easily reversed since there'll be a big release of energy from the reaction, and this makes THIS step of glycolysis an excellent control point for ALL ten steps together, since it's more or less a one way reaction. So, what did we learn? Well, first, we learned about the concept of allostery, and how regulatory molecules bind to allosteric sites instead of active sites. Second, we learned that these allosteric regulators influence an enzyme's kinetics by increasing KM or V max, and third we learned about what a feedback loop is, and how in long, multi-step processes like glycolysis, the best control points are highly committing steps, the ones with very negative delta G values.