Hill equation (biochemistry)
Hill equation (biochemistry)
In biochemistry and pharmacology, the Hill equation refers to two closely related equations that reflect the binding of ligands to macromolecules, as a function of the ligand concentration.
The distinction between the two equations is whether they measure occupancy or response. The Hill-Langmuir equation reflects the occupancy of macromolecules: the fraction that is saturated or bound by the ligand.[3][4][1] This equation is formally equivalent to the Langmuir isotherm.[5] Conversely, the Hill equation, reflects the cellular or tissue response to the ligand: the physiological output of the system, such as muscle contraction.
The Hill-Langmuir equation was originally formulated by Archibald Hill in 1910 to describe the sigmoidal O2 binding curve of haemoglobin.[6]
The binding of a ligand to a macromolecule is often enhanced if there are already other ligands present on the same macromolecule (this is known as cooperative binding). The Hill-Langmuir equation is useful for determining the degree of cooperativity of the ligand(s) binding to the enzyme or receptor. The Hill coefficient provides a way to quantify the degree of interaction between ligand binding sites.[7]
The Hill equation (for response) is important in the construction of dose-response curves.
Proportion of ligand-bound receptors
- ,
where:
is the fraction of the receptor protein concentration that is bound by the ligand,
is the free, unbound ligand concentration,
is the apparent dissociation constant derived from the law of mass action,
is the ligand concentration producing half occupation,
is the Hill coefficient.
Constants
Gaddum equation
The Gaddum equation is a further generalisation of the Hill-equation, incorporating the presence of a reversible competitive antagonist.[3] The Gaddum equation is derived similarly to the Hill-equation but with 2 equilibria: both the ligand with the receptor and the antagonist with the receptor. Hence, the Gaddum equation has 2 constants: the equilibrium constants of the ligand and that of the antagonist
Hill plot
The Hill plot is the rearrangement of the Hill-Langmuir Equation into a straight line.
- .
Transformations of equations into linear forms such as this were very useful before the ubiquity of computers, as they allowed researchers to determine parameters by fitting lines to data. However, these transformations affect how errors are propagated, which may result in undue weight to error in data points near 0 or 1.[2] This impacts the parameters of linear regression lines fitted to the data. Furthermore, the advent of computers in experiments allows for more robust analysis with nonlinear regression.
Tissue response
A distinction should be made between quantification of drugs binding to receptors and drugs producing responses. There may not necessarily be a linear relationship between the two values. In contrast to this article's previous definition of the Hill-Langmuir equation, the IUPHAR defines the Hill equation in terms of the tissue response (E), as
This form of the equation can reflect tissue/cell/population responses to drugs and can be used to generate dose response curves. The relationship between KD and EC50 may be quite complex as a biological response will be the sum of myriad factors; a drug will have a different biological effect if more receptors are present, regardless of its affinity.
The Del-Castillo Katz model is used to relate the Hill-Langmuir equation to receptor activation by including a second equilibrium of the ligand-bound receptor to an activated form of the ligand-bound receptor.
Statistical analysis of response as a function of stimulus may be performed by regression methods such as the probit model or logit model, or other methods such as the Spearman-Karber method.[10] Empirical models based on nonlinear regression are usually preferred over the use of some transformation of the data that linearizes the dose-response relationship.[11]
Hill coefficient
The Hill coefficient is a measure of ultrasensitivity (i.e. how steep is the response curve).
Interpretation
. Positively cooperative binding: Once one ligand molecule is bound to the enzyme, its affinity for other ligand molecules increases. For example, the Hill coefficient of oxygen binding to haemoglobin (an example of positive cooperativity) falls within the range of 1.7-3.2.[7]
. Negatively cooperative binding: Once one ligand molecule is bound to the enzyme, its affinity for other ligand molecules decreases.
. Noncooperative (completely independent) binding: The affinity of the enzyme for a ligand molecule is not dependent on whether or not other ligand molecules are already bound. When n=1, we obtain a model that can be modeled by Michaelis–Menten kinetics,[12] in which , the Michaelis-Menten constant.
Relationship between Hill coefficient, EC10 and EC90
The Hill coefficient can be calculated as:
- .[13]
Derivation from mass action kinetics
- ,
- .
- .
- ,
- .[4]
Applications
The Hill and Hill-Langmuir equations are used extensively in pharmacology to quantify the functional parameters of a drug and are also used in other areas of biochemistry.
The Hill equation can be used to describe dose-response relationships, for example ion channel open-probability (P-open) vs. ligand concentration.[15]
Regulation of gene transcription
The Hill-Langmuir equation can be applied in modelling the rate at which a gene product is produced when its parent gene is being regulated by transcription factors (e.g., activators and/or repressors).[12] Doing so is appropriate when a gene is regulated by multiple binding sites for transcription factors, in which case the transcription factors may bind the DNA in a cooperative fashion.[16]
If the production of protein from gene X is up-regulated (activated) by a transcription factor Y, then the rate of production of protein X can be modeled as a differential equation in terms of the concentration of activated Y protein:
- ,
where k is the maximal transcription rate of gene X.
Likewise, if the production of protein from gene Y is down-regulated (repressed) by a transcription factor Z, then the rate of production of protein Y can be modeled as a differential equation in terms of the concentration of activated Z protein:
- .
Limitations
Because of its assumption that ligand molecules bind to a receptor simultaneously, the Hill-Langmuir equation has been criticized as a physically unrealistic model.[7] Moreover, the Hill coefficient should not be considered a reliable approximation of the number of cooperative ligand binding sites on a receptor[7][17] except when the binding of the first and subsequent ligands results in extreme positive cooperativity.[7]
Unlike more complex models, the relatively simple Hill-Langmuir equation provides little insight into underlying physiological mechanisms of protein-ligand interactions. This simplicity, however, is what makes the Hill-Langmuir equation a useful empirical model, since its use requires little a priori knowledge about the properties of either the protein or ligand being studied.[4] Nevertheless, other, more complex models of cooperative binding have been proposed.[8] For more information and examples of such models, see Cooperative binding.
Response coefficient
Global sensitivity measure such as Hill coefficient do not characterise the local behaviours of the s-shaped curves. Instead, these features are well captured by the response coefficient measure [18] defined as:
There is a link between Hill Coefficient and Response coefficient, as follows. Altszyler et al. (2017) have shown that these ultrasensitivity measures can be linked by the following equation:[13]
See also
Cooperative binding
Logistic function
Gompertz curve