Substrate Concentration (Introduction to Enzymes)
What is the relationship between Km and Kmax to Substrate and Enzyme The Michaelis constant Km is the substrate concentration at which the reaction . I have absorbance (at nm) and reaction time how to find the enzyme activity. set of mathematical expressions to calculate enzyme activity in terms of reaction speed from measurable laboratory data. The Michaelis constant Km is defined. To analyse the effect of substrate concentration on the activity of enzyme. The relationship between substrate concentration, [S] and Initial velocity of The necessary terms in this reaction are [S], V0, Vmax, and Km (Michaelis constant).
To analyze the effect of substrate concentration on the activity of enzymes. Enzymes are protein molecules that act as biological catalysts by increasing the rate of reactions without changing the overall process.
Introduction to Enzymes
They are long chain amino acids bound together by peptide bonds. Enzymes are seen in all living cells and controlling the metabolic processes in which they converted nutrients into energy and new cells. Enzymes also help in the breakdown of food materials into its simplest form.
- Structural Biochemistry/Enzyme/Michaelis and Menten Equation
The reactants of enzyme catalyzed reactions are termed as substrates. Each enzyme is quite specific in character, acting on a particular substrates to produce a particular products. The central approach for studying the mechanism of an enzyme-catalyzed reaction is to determine the rate of the reaction and its changes in response with the changes in parameters such as substrate concentration, enzyme concentration, pH, temperature etc.
This is known as enzyme kinetics. One of the important parameters affecting the rate of a reaction catalyzed by an enzyme is the substrate concentration, [S]. The relationship between rate of reaction and concentration of substrate depends on the affinity of the enzyme for its substrate. This is usually expressed as the Km Michaelis constant of the enzyme, an inverse measure of affinity.
For practical purposes, Km is the concentration of substrate which permits the enzyme to achieve half Vmax. An enzyme with a high Km has a low affinity for its substrate, and requires a greater concentration of substrate to achieve Vmax. An enzyme with a low Km relative to the physiological concentration of substrate, as shown above, is normally saturated with substrate, and will act at a more or less constant rate, regardless of variations in the concentration of substrate within the physiological range.
An enzyme with a high Km relative to the physiological concentration of substrate, as shown above, is not normally saturated with substrate, and its activity will vary as the concentration of substrate varies, so that the rate of formation of product will depend on the availability of substrate. If two enzymes, in different pathways, compete for the same substrate, then knowing the values of Km and Vmax for both enzymes permits prediction of the metabolic fate of the substrate and the relative amount that will flow through each pathway under various conditions.
In order to determine the amount of an enzyme present in a sample of tissue, it is obviously essential to ensure that the limiting factor is the activity of the enzyme itself, and not the amount of substrate available.
Basics of enzyme kinetics graphs
This means that the concentration of substrate must be high enough to ensure that the enzyme is acting at Vmax. In practice, it is usual to use a concentration of substrate about 10 - fold higher than the Km in order to determine the activity of an enzyme in a sample. If an enzyme is to be used to determine the concentration of substrate in a sample e.
The relationship is defined by the Michaelis-Menten equation: A number of ways of re-arranging the Michaelis-Menten equation have been devised to obtain linear relationships which permit more precise fitting to the experimental points, and estimation of the values of Km and Vmax. There are advantages and disadvantages associated with all three main methods of linearising the data.