serotonin2A
Bluelighter
- Joined
- Sep 13, 2014
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Understanding the mechanics if binding isn't really necessary to understand these issues. Basically, the occupation level is calculated by taking the ligand concentration divided by the sum of the ligand concentration and the Ki.
In other words:
%occupation = [L]/([L]+[Ki])
So you know that 50% of the receptors will be occupied at the Ki. This gives you a working range of concentrations where a drug will interact with a receptor. At concentrations below the range there will be no interaction and above the range the receptor will be saturated and the response will max out.
That is why I keep emphasizing that Ki is not a relative measure -- ie, it isn't necessarily bad if a drug has micromolar affinity. When you see an affinity value, the immediate question in your mind should be whether it is possible that the in vivo concentration is likely to be similar. Micromolar drug concentrations in tissues are not uncommon, but mM concentrations are not as common. But ethanol concentrations are known to rise to the mM level when people drink. Mescaline has pretty low affinity for 5-HT2A receptors, which is why it takes hundreds of mg to produce a response.
No, this is determined by actually measuring the concentration in tissues or body fluids. Usually you can look up the plasma concentration, and potentially the ratio of blood/brain levels may be known. Even better, someone may have measured receptor occupancy using PET imaging.
Yes exactly. This determines how much occupation you can achieve at the primary site of action without producing side effects.
No, this is different than the Ki. The Ki measures the interaction of a ligand and its binding site. Efficacy refers to effects downstream from binding.
For antagonists, as a general rule, receptor occupation is often a useful predictor of response. So 50% occupation is a good place to start at for an antagonist. But for some things, 10% occupation may be sufficient, or you may need 100%. It depends on what you are trying to block.
The situation is even more complex with agonists, which produce graded responses. Each agonist has an intrinsic efficacy, which is a measure of how effectively it can activate a receptor. But even knowing the efficacy isn't sufficient to understand how an agonist acts in a particular tissue, because you also have to account for receptor reserve.
Obviously there are several complexities associated with trying to predict in vivo responses based on in vitro measures. The way around this problem is to measure tissue responses to a drug, for example using neurochemical methods, electrophysiology, or imaging. That way you can know what drug concentration is required to produce a given response in a particular tissue. That is a good guide for estimating the concentration range that is likely to produce a therapeutic response.
You are mixing up two different topics. Affinities are discussed to understand what receptors a drug binds to and its relative selectivity. This is information about pharmacodynamics.
The in vivo concentration is information about drug pharmacokinetics, which is a completely different aspect of pharmacology. Combining what is known about the pharmacodynamics and pharmacokinetics of a medication allows you to understand how it works in the body.
The amount of ground you want to cover encompasses an entire pharmacology course.
In terms of your question, there is no way to predict the answer with the information given. The drug company worked with the FDA to try to figure out a range of doses that produce brain concentrations that (1) yield interactions with NET, 5-HT2C, and alpha2 receptors sufficient to produce therapeutic effects, but (2) are not too high to produce off-target effects that could produce side-effects or toxicity.
Often, you are not going to know the tissue concentration of the drug when you read a table like that. What the table does is help to clarify which sites the drug may be interacting with in the brain, and which of those sites may be responsible for the therapeutic effects. You should be paying attention to the affinity at the primary target(s) relative to the other sites. Optimally, the Ki for the primary sites of action is at least 10- to 100-fold higher than other sites. If that isn't the case then you have to think about what side-effects may occur due to those secondary interactions.
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