biochemistry - What's the difference between Ki and IC50? - Biology Stack Exchange
I saw in the literature in some cases the Ki values were less than IC50, but others Ki values were As Dominique correctly states, IC50 must be greater than or equal to Ki, according to the Cheng-Prusoff relationship. 1 Recommendation. To understand the difference between Eqs. 1 and 2, we . with the same Bmax and KD, can also be modeled with the . Relationship between IC50 and KD. based on the relationship that, for competitive inhibition, Ki = IC50/2 when enzymes based on the FDA's draft Guidance for Industry on.
The inhibitory constant Ki and the IC50 of a drug that is known to cause inhibition of a cytochrome P CYP enzyme have to do with the concentration needed to reduce the activity of that enzyme by half. More specifically the Ki is reflective of the binding affinity and the IC50 is more reflective of the functional strength of the inhibitor for a drug.
Since the Ki takes into account the IC50 is its calculation, the Ki is being reported more often by drug companies. For noncompetitive inhibition of enzymes, the Ki of a drug is essentially the same numerical value as the IC50, whereas for competitive and uncompetitive inhibition the Ki is about one-half that of the IC50's numerical value.
50% of what? How exactly are IC50 and EC50 defined? - FAQ - GraphPad
The smaller the Ki, the greater the binding affinity and the smaller amount of medication needed in order to inhibit the activity of that enzyme. If a Ki is much larger than the maximal drug concentrations that a patient is typically exposed to from typical dosing, then that drug is not likely to inhibit the activity of that enzyme. October Explanation If clinicians have not already started to encounter Ki's in the literature and product package inserts for medications, they will likely encounter them in the future.
More specifically the Ki is reflective of the binding affinity and the IC50 is more reflective of the functional strength of the inhibitor, but both factor in the concentration of drug present to inhibit the enzyme activity. Of note, for drugs that are noncompetitive inhibitors of CYP enzymes, the Ki of a drug is essentially the same numerical value as the IC50's numerical value, whereas for competitive and uncompetitive inhibition the Ki is about one-half that of the IC If a Ki is much larger than the maximal plasma drug concentrations a patient is exposed to from typical dosing, then that drug is not likely to inhibit the activity of that enzyme.
This leads to alternative definitions of IC Clearly, a single value cannot summarize such a curve. You'd need at least two values, one to quantify the middle of the curve the drug's potency and one to quantify how low it gets the drug's maximum effect.
The graph above shows two definitions of the IC The relative IC50 is by far the most common definition, and the adjective relative is usually omitted. The NS values are totally ignored with this definition of IC This definition is the one upon which classical pharmacological analysis of agonist and antagonist interactions is based. With appropriate consideration of the biological system and concentrations of interacting ligands, estimated Kd values can often be derived from the IC50 value defined this way not so for the "so-called absolute IC50" mentioned below.
This term is not entirely standard.
50% of what? How exactly are IC50 and EC50 defined?
The concept but not the term "absolute IC50" is used to quantify drugs that slow cell growth. The abbreviation GI50 is used for what we call here the absolute IC They don't use the terms relative and absolute. Incomplete dose-response curves Any attempt to determine an IC50 by fitting a curve to the data in the graph above will be useless.
A curve fitting program might, or might not, be able to fit a dose-response curve to the data. But if the curve fits, the value of the IC50 is likely to be meaningless and have a very wide confidence interval. The data simply don't form a top plateau which would define or a bottom plateau which would define 0.
If data haven't defined or 0, then 50 is undefined too, as is the IC If you also have control values that define and 0, then the curve can be easily fit. The curve below was created by fitting a dose response curve, but constraining the Top plateau to be a constant value equal to the mean of the Blanks values, and the Bottom plateau equal to the mean of the NS values.
The value of the IC50 fit this way only makes sense if you assume that higher concentrations of the inhibitor would eventually inhibit down to the NS values. That is an assumption that can't be tested with the data at hand.
The distinction between relative and absolute IC50 doesn't really apply to these data. Because the data don't define a bottom plateau, the IC50 must be defined relative to the NS control values. You can fit curves using data in their natural units.
A common mistake is to assume that fitting dose-response curves requires that data first be normalized. There are three strategies you can use: From external controls Blank and NS in the figures above. Since these values are so important, consider measuring these controls with more replicates than used for the rest of the experiment.
From very low and very high concentrations of the test substance. From the plateaus of nonlinear regression.