Chapter 3

Enzymes and Enzymatic Sensors

3.1 General

Enzymes are protein compounds that are specifically structured to bind to and act on a substrate (reactant molecule) to convert it by a catalytic mechanism, that is, by lowering the activation energy of the reaction with no effect on the chemical equilibrium [1–4].

Enzyme-catalyzed reactions rely on the formation of an intermediate involving both a shape and structure match of the substrate with the active site on the enzyme (Figure 3.1). In the resulting complex, substrate conversion is facilitated by various means. Thus, the enzyme–substrate interaction can cause a key chemical bond in the substrate to become weaker and prone to further alteration. Furthermore, the enzyme provides favorable conditions for stabilizing a reaction intermediate and preventing its reconversion to the initial form. When more than one reactant is involved, the enzyme, by specific chemical bindings, can gather all of them in a state that stimulates the reaction to proceed. In some cases, the enzyme active site can shuttle particles such as electrons or hydrogen ions that are needed in the reaction. Although Figure 3.1 shows a single-substrate reaction, many enzyme reactions involve two or more reactants (cosubstrates).

Figure 3.1 Mechanism of enzyme-catalyzed substrate conversion. E is the enzyme, S is the substrate, P₁ and P₂ are product. The intermediate state is an enzyme–substrate complex.

Enzymatic methods are widely used in bioanalytical chemistry in order to determine the enzyme itself or its substrate [5]. To this end, either the reaction rate or the concentration of a reactant or a product is assessed by a suitable analytical method.

As an extension of this, the application of enzymes in biosensor design relies on their specificity for a substrate-analyte that cannot be detected in a direct way. Therefore, in order to build up an enzyme sensor, the enzyme should be immobilized as part of a recognition layer at the surface of a suitable transducer so as to gage the concentration of a detectable species (Figure 3.2). The substrate and any additional reactants undergo first of all diffusion from the sample solution into the recognition layer where the enzyme reaction takes place. The transducer allows the monitoring of the course of the reaction by detecting either a product, or the excess of reactant that escaped the enzyme reaction. In addition, pure physical effects (such as heat evolution) are suitable for monitoring the rate of the enzyme reaction and, implicitly, the substrate concentration. Perm-selective membranes are often incorporated at interfaces in order to control the diffusion of certain reactants. Also, diffusion of some interfering compound from the sample to the recognition element can be hindered by a suitable external membrane.

Figure 3.2 Typical configuration of an enzymatic biosensor.

As well as isolated enzymes, enzymes included in living entities (such as micro-organisms or living tissues) can be used directly in order to perform analyte recognition and conversion (see Chapter). A biosensor based on an enzyme, either isolated or incorporated in living materials, is often termed a metabolism sensor.

Moreover, any inhibitor (for example, an organic compound or a metal ion) of the enzyme catalytic activity can be determined by its slowing down effect on the substrate conversion rate. Further, an enzyme can act as a transduction tag if it is attached to a nondetectable species. By its action on a suitable substrate, a detectable product forms that enables indirect detection of the target compound. As a large amount of product results in the presence of a minute amount of enzyme-tagged compound, this allows for extremely sensitive detection.

For a long time, the availability of enzymes was limited to those produced by natural living organisms. Recently, genetic engineering has made it possible to extend the range of enzyme sources and to create new enzymes that are able to meet specific requirements.

3.2 Enzyme Nomenclature and Classification

Many enzymes have been named by adding the suffix “-ase” to the substrate name. Thus, urease catalyzes the hydrolysis of urea to ammonia and carbon dioxide, whereas phosphatase catalyzes the hydrolysis of phosphate esters. However, in order to avoid confusion, enzymes are classified into six major classes and a series of subclasses, according to the kind of catalyzed reaction (Table 3.1). At the same time, rules for unambiguous identification of each enzyme were recommended by the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology [6].

Table 3.1 Enzyme classes.

According to this systematic nomenclature, each enzyme is ascribed a recommended name, suitable for common use, a systematic name, which denotes the reaction it catalyzes, and a four digit classification number (preceded by the EC acronym that stands for Enzyme Commission). For example, glucose oxidase (that catalyzes the oxidation of glucose by oxygen) is denoted EC 1.1.3.4, and has the systematic name β-D-Glucose:oxygen 1-oxidoreductase, (see the scheme in Figure 3.3).

Figure 3.3 Assigning the classification number to the glucose oxidase enzyme (EC 1.1.3.4).

3.3 Enzyme Components and Cofactors

Although enzymes are protein-type compounds, many of them need a nonprotein cofactor in order to fulfill the biological function (Figure 3.4). The cofactor can be an organic molecule acting as a coenzyme. Some coenzymes are tightly bound to the protein structure as a prosthetic group. If the cofactor is removed, the remaining substance is called an apoenzyme, whilst the whole enzyme is called a holoenzyme. In other cases, the cofactor is an independent substance (cosubstrate) that is bound temporarily to the enzyme in order to take part in the catalytic process. By free diffusion, coenzymes contribute to the transport of electrons, atoms or groups of atoms between molecules.

Figure 3.4 Different cofactors and their interaction with proteins.

The simplest cofactors are metal ions attached to the protein side chains by coordination or electrostatic bonds. Thus, an activator metal ion obliges the active site to adopt a favorable configuration or can be involved in binding the substrate to the active site. In some cases, a transition-metal ion acts as an electron conveyor. Tightly bound metal ions (such as nickel in urease) are structural constituents of the enzyme active site.

An example of a tightly bound cofactor is flavin adenine dinucleotide (FAD) that occurs as a prosthetic group of various oxidoreductases. It conveys electrons and hydrogen ions between an enzyme and its substrate by undergoing a redox reaction similar to that depicted in Figure 3.5. Electrochemical oxidation of the FADH₂ form may be the basis for electrochemical transduction in some biosensors. However, as the FAD center is surrounded by the protein backbone, direct electron transfer can be achieved only when electrodes composed of particular materials are used. Alternatively, the transduction can be performed by detecting a redox mediator that conveys electrons between the FADH₂ center and a metal or graphite electrode.

Figure 3.5 The redox reaction of the active part of FAD. R denotes the remaining part of the FAD/FADH₂ unit.

An example of a coenzyme is nicotinamide adenine dinucleotide (NAD⁺) that consists of two nucleotides linked by two phosphate groups, with nicotinamide attached to one end position and adenine to the other end position. It can undergo the redox reaction shown in Figure 3.6 and act as an electron and proton conveyer in reactions catalyzed by some oxidoreductases. In an amperometric enzyme sensor, the electron acceptor/donor role in a reaction like that in Figure 3.6 can be assumed by an electrode in a suitable electrochemical cell. In such circumstances, the NAD⁺/NADH couple performs as an electron shuttle between a substrate and the electrode, giving rise to the response current.

Figure 3.6 The redox reaction of nicotinamide adenine dinucleotide. The featured reacting moiety is nicotinamide; R denotes the remaining part of the coenzyme molecule.

Nicotinamide adenine dinucleotide phosphate (NADP⁺/NADPH), which is a phosphorylated derivative of NAD/NADH, performs similar functions in various enzyme-catalyzed reactions.

Pyrroloquinoline quinone cofactor (PQQ, (Figure 3.7)) occurs in some bacterial enzymes and plays a role similar to that of NAD⁺. This cofactor is attached to a protein carboxylate via a calcium ion, which, in addition, allows temporary binding of the substrate (for example, an alcohol) to the active site.

Figure 3.7 The pyrroloquinoline quinone cofactor (PQQ). R represents the protein backbone.

A common prosthetic group in some oxidoreductases is of the heme type (Figure 3.8). It consists of an iron atom coordinated in the center of a large heterocyclic porphyrin ring. As the iron atom can swing between several oxidation states, it acts as an electron donor/acceptor in redox reactions.

Figure 3.8 (A) Heme B, a typical heme group. (B) Cytochrome c, a heme protein. Adapted from http://www.rcsb.org/pdb/explore/explore.do?structureId=1HRCLastaccessed16/05/2012.

The above discussion has been limited to several cofactors that have wide applications in enzyme biosensor. Many other cofactors occur in living organisms.

3.4 Some Enzymes with Relevance to Biosensors

Among the vast number of enzymes that occur in living organisms, several have proved useful for bioanalytical purposes and also for designing enzyme biosensors. The following section includes a short outline of enzymes of particular relevance from this standpoint. A comprehensive overview of enzymes application for biosensor design and construction is available in ref. [7].

3.4.1 Oxidases

FAD-oxidases use molecular oxygen as the electron and hydrogen ion acceptor in the catalytic cycle. A typical example involves glucose oxidation catalyzed by glucose oxidase using the FAD prosthetic group as an electron and hydrogen ion conveyer (Figure 3.9). Glucose oxidase from Aspergillus niger is broadly employed in bioanalytical chemistry, either as an analytical reagent or as recognition material in glucose biosensors [8–12]. This is because glucose is a compound of great analytical concern in diabetes monitoring as well as in the food industry. In addition, the relatively low price and good stability makes the glucose/glucose oxidase system a very suitable model for method development in biosensor science.

Other FAD-dependent oxidases with wide applications in sensor science are summarized in Table 3.2. The last enzyme in this table (lactate oxidase) relies on the flavin mononucleotide prosthetic group (FMD). Flavin-oxidases use oxygen as a cosubstrate and give rise to hydrogen peroxide. Monitoring of one of the above compounds is a general transduction method for FAD-oxidase-based sensors. Oxygen, however, can be substituted by an artificial electron acceptor allowing oxygen-independent operation. As shown in Table 3.2, some flavoenzyme oxidases give rise to inorganic gases such as ammonia or carbon dioxide. Monitoring of such gases or their hydrolysis products (for example, or H⁺) represents another convenient transduction strategy.

Table 3.2 Some flavoenzyme oxidases with applications in biosensors. Systematic names are given in parentheses.

A series of copper-containing oxidases (Table 3.3) are also used extensively in biosensors for biologically active compounds or phenolic pollutants [13, 14]. The product of phenols oxidation is a reducible quinone, which can be determined by electrochemistry. Copper enzymes can perform direct electron transfer to an electrode, which can provide an electrochemical transduction method [15]. Laccase, that catalyses the oxidation of benzenediol, is used in sensors for monitoring the environment pollution [16].

Table 3.3 Copper-containing oxidases with applications in biosensors.

Another class of oxidases is represented by peroxidases that can shuttle electrons to hydrogen peroxide (or small organic peroxides) from electron donors. The prosthetic group in many peroxidases is of a heme type (Figure 3.8). The most common member of this class is horseradish peroxidase (HRP) that can accept electrons from virtually any reducing agent, for example, ferrocyanide, phenol, hydroquinones, ortho- and para-phenylenediamine, ascorbate, iodide or ferrocene. The reaction mechanism for a peroxidase-catalyzed reaction can be described by the following steps [17]:

(3.1)

(3.2)

(3.3)

In the first step, the ferriheme prosthetic group in the enzyme undergoes a two-electron oxidation by hydrogen peroxide or organic hydroperoxides. This reaction results in the formation of the compound-I (oxidation state +5), consisting of oxyferryl ion () and a porphyrin cation radical. In the next reaction, compound-I accept one electron from the donor substrate molecule and forms the compound-II (oxidation state +4). In the third step, the compound-II undergoes additional one-electron reduction by reaction with a second molecule, whereby the enzyme is restored to its native state. Therefore, the overall reaction is:

(3.4)

where R and R′ represent organic residues or hydrogen atoms.

The final product depends on the nature of the substrate. Organic electron donors such as aromatic amines and phenolic compounds are oxidized to free radicals, . Inorganic substrates like hexacyanoferrate(II) are simply oxidized by withdrawing one electron.

Reactions (3.1) and (3.2) can also proceed as electrochemical reactions (in which the cell cathode acts as electron donor) either by direct electron transfer or by means of redox mediators. In both cases, the electrolytic current is correlated to the concentration of peroxide in the solution.

Peroxidase sensors can be used for determining either the peroxide or the electron-donor substrate and also inhibitors such as CN⁻ and F⁻. Peroxidases are also widely used as transduction tags in affinity sensors.

3.4.2 Dehydrogenases

Dehydrogenase performs the transfer of a hydride ion (H⁻) between a substrate containing a –CHOH group and a suitable cofactor [18]. Such a reaction is equivalent to the transfer of one proton and two electrons. Thus, NAD⁺- (or NADP⁺-) dependent hydrogenases convert an alcohol to a carbonyl compound as follows:

(3.5)

Over 250 enzymes belong to this class, thus offering a broad range of analytical applications. Several dehydrogenases with relevance to biosensor applications are included in Table 3.4.

Table 3.4 Some NAD⁺-dependent dehydrogenase enzymes with applications in biosensors.

In dehydrogenase-based biosensors transduction can in principle be performed by monitoring the cofactor in either the oxidized or reduced form by electrochemical reactions or light absorption/emission. As the hydrogen ion is involved in such reactions, pH monitoring could also be a straightforward transduction method. In the case of amino acid dehydrogenases, determination of ammonia (or ammonium) by a suitable probe provides an additional transduction method.

Some bacterial dehydrogenases rely on the PQQ cofactor (Figure 3.7), which is relatively tightly bound to the enzyme. Such an enzyme can in some instances be a convenient alternative to NAD⁺-dependent dehydrogenases because the NAD⁺/NADH system is a soluble and freely diffusing species. In natural systems, PQQ-enzymes perform the same task as NAD⁺-dependent dehydrogenases (that is, catalysis of hydride ion transfer) but use quinone as the electron acceptor. Quinoprotein alcohol dehydrogenase (alcohol:quinone oxidoreductase, EC 1.1.5.5) and quinoprotein glucose dehydrogenase (D-glucose:ubiquinone oxidoreductase, EC 1.1.5.2) are examples of PQQ-dehydrogenase already investigated for biosensor applications.

3.4.3 Hydrolases

A hydrolase is an enzyme that catalyzes the hydrolysis of a chemical bond such as the ester bond (esterases) or the peptide bond (proteases).

Several enzymes in the hydrolase class deserve a particular mention. Thus, acetylcholinesterase (AChE, EC 3.1.1.7) is essential to nerve cell function through its capacity to break down the neurotransmitter acetylcholine into its constituents (Figure 3.10). Various pesticide or war gases are AChE inhibitors that renders a inhibition-based AChE sensor useful for detecting such harmful compounds [19].

Figure 3.9 Glucose oxidation catalyzed by glucose oxidase (GOD). FAD and FADH₂ are the oxidized and reduced forms, respectively, of the prosthetic group. Glucose is oxidized upon electron and hydrogen ion transfer to the oxidized form of the prosthetic group (FAD) that is reduced to FADH₂. FAD is regenerated by the oxidation of FADH₂ with molecular oxygen. Hydrogen peroxide forms as a byproduct of this reaction.

Figure 3.10 Enzymatic hydrolysis of acetylcholine.

As hydrogen ions result from hydrolysis, transduction in AChE sensors can be performed simply by assessing the change in pH. For amperometric sensor applications, the natural substrate is substituted by a derivative that gives rise to an easily detectable product (such as acetylthiocoline). Thiocholine (), which results from the hydrolysis reaction, can be monitored by its electrochemical oxidation.

Urease (urea amidohydrolase EC 3.5.1.5) catalyzes the hydrolysis of urea (Figure 3.11) and is widely used for both urea determination and also for determining enzyme inhibitors [20]. At a suitable pH, either ammonia or carbon dioxide form and probes for such gases are suitable for transduction.

Figure 3.11 Enzymatic hydrolysis of urea.

Alkaline phosphatase (ALP) (phosphate-monoester phosphohydrolase (alkaline optimum), EC 3.1.3.1) is responsible for removing phosphate groups from many types of phosphate esters, including nucleotides, proteins, and alkaloids. ALP-catalyzed dephosphorylation proceed as shown in reaction (3.6).

(3.6)

ALP as an isolated enzyme or as a component of living micro-organisms is useful for pollutant determination by inhibition of the enzymatic reaction. ALP is also employed as a transduction tag in affinity sensors.

Sensors used in the antibiotics industry have been developed by means of penicillase, which converts the substrate (for example, penicillin) into a substituted -amino acid. This brings about a change in the pH that is utilized as a response signal.

Some amino derivatives undergo enzymatic hydrolysis with formation of ammonia, which can be determined by an ammonia probe included in a biosensor. In this way, clinically relevant compounds such as creatinine and adenosine can be determined by means of sensors based on relevant enzymes (creatinase and adenosine deaminase, respectively).

3.4.4 Lyases

Lyases are enzymes that catalyse the breaking of various chemical bonds by means other than hydrolysis and oxidation.

Clinically relevant oxalic acid can be determined by sensors based on oxalate decarboxylase. This enzyme converts oxalic acid to formic acid and carbon dioxide (reaction (3.7)). The transduction can be performed by means of a carbon dioxide probe.

(3.7)

Another lyase of interest is L-aspartase (aspartate ammonia-lyase) that converts aspartate to fumarate yielding ammonia, which can be monitored by an ammonia probe.

3.4.5 Outlook

Enzymes are protein compounds that perform as specific catalysts in living organisms. Enzyme specificity is imparted by the chemical structure and the configuration of the active site, which allows the enzyme to bind the substrate and give rise to an enzyme–substrate complex. In this state, the substrate undergoes chemical conversion to products that are released, leaving the active site. At the end of this process, the enzyme is able to bind and convert another substrate molecule.

Certain enzymes are plain proteins, whilst other enzymes rely on an active site formed of a nonprotein species (cofactors). A cofactor can be bound to the protein backbone or can be an independent molecule that acts as a conveyor of electrons, atoms or groups of atoms.

Enzymatic sensors are produced by integrating an enzyme layer with a transducer that monitors the concentration of a reactant or product involved in the enzymatic reaction. The response signal thus generated is in relation with the substrate concentration in the sample.

The selectivity of an enzymatic sensor depends on the enzyme selectivity. In this respect, it should be borne in mind that only a few enzymes exhibit absolute selectivity that is, they will catalyze only the conversion of one particular compound. Other enzymes will be specific for a particular type of chemical bond or functional group.

Besides the substrate determination, enzymatic sensor can be used to determine enzyme inhibitors. Moreover, enzymes are utilized as signaling labels in certain types of sensors such as immunosensors or nucleic acid sensors.

3.5 Transduction Methods in Enzymatic Biosensors

3.5.1 Transduction Methods

The transduction strategy is chosen with regard to the enzyme reaction by taking into account the methods available for gaging the physical and chemical consequences of the recognition process.

Purely physical effects such as heat evolution or change in ionic conductivity represent general transduction methods that can, in principle, be put into operation with any kind of enzyme sensor. However, such transduction methods are not selective and should be used cautiously.

Chemical transduction relies on monitoring the concentration of any possible compound that is involved in the enzyme reaction. The main restriction in this case is the availability of a suitable monitoring method. If such a method is missing, additional reactions can be integrated into the transduction scheme, in order to generate a detectable compound.

The general principles of transduction in enzymatic sensors will be illustrated here for the particular case of the glucose oxidase-based glucose sensor. Figure 3.12 illustrates the main course of glucose oxidation in the presence of glucose oxidase and the subsequent strategies for performing transduction in a glucose sensor. The substrate–enzyme electron transfer takes place within an intermediate complex formed by the substrate and the oxidixed form of the enzyme (GOD_ox). Then, the complex undergoes a chemical conversion that releases the product and the enzyme in its reduced form (GOD_red). In order for the enzyme to fulfill further its function this form should be changed back to GOD_ox by an electron-transfer reaction. In natural media, the electron donor in this step is dissolved oxygen and hydrogen peroxide results as the product (path I). Hence, transduction can be performed by monitoring either the oxygen or the hydrogen peroxide concentration within the sensing layer by means of an appropriate probe. However, in this method both oxygen and a pH buffer should be added to the sample as auxiliary reagents. A reagentless glucose biosensor can be obtained if GOD_ox is regenerated by direct electrochemical oxidation of GOD_red with the electrolytic current acting as the response signal (path II). Another method relies on a redox mediator (M) that is included in the sensor structure along with the enzyme itself (path III). GOD_red is reoxidized to GOD_ox by electron transfer to the oxidized form of the mediator (M_ox). The resulting reduced mediator (M_red) is converted back to M_ox by an electrochemical reaction that provides the response current. In addition, hydrolysis of the primary product (gluconolactone) to the gluconate anion (path IV) induces a pH change that can be monitored for achieving transduction.

Figure 3.12 Possible transduction methods for glucose oxidase-based sensors. GOD and Gluc stands for glucose oxidase and glucose, respectively.

Additional reactions can be integrated with the transduction scheme in order to generate products that can be detected by means of available probes. Thus, hydrogen peroxide can react with the iodide ion in the presence of a suitable catalyst, which allows transduction to be performed by means of a potentiometric iodide sensor.

It is clear from the above discussion that, for a given enzyme–substrate couple, different transduction approaches can be feasible. A selective transduction method, which responds specifically to a particular reaction product, is preferable, but perfect specificity is difficult to achieve. Endogenous components in the sample may in many cases interfere with the transduction step. In such cases, corrections should be applied to the response signal in order to avoid errors. Thus, a reference sensor, containing no enzyme, can be used in order to obtain the response background due to interferences and this signal has to be subtracted from the overall response provided by the main sensor. Alternatively, perm-selective membranes should be selected such as to prevent sample interferents from reaching the transduction zone. So, a key problem in enzyme sensor research is finding the most suitable transduction procedure for a particular recognition reaction in order to obtain a reliable sensor that fits specific requirements imposed by the sample composition and the operational conditions.

Certain enzymatic reactions releases gases such as ammonia or carbon dioxide. These gases can be monitored by specific probes in order to generate the response signal.

3.5.2 Multienzyme Sensors

In enzyme assays, a reaction leading to a detectable product is termed an indicator reaction. If such a reaction is not available for a specific substrate, the initial product can be further converted into a detectable compound (also called an indicator species) by means of a second enzyme-catalyzed reaction. In such cases the primary reaction is termed an auxiliary reaction, whereas the second reaction acts as the actual indicator reaction.

Application of multienzyme systems has also proved to be successful in developing enzymatic sensors. Thus, the glucose sensor can be adapted in order to build up a sucrose sensor by integrating glucose oxidase with invertase (EC 3.2.1.26) within the sensing layer. Invertase catalyzes the hydrolysis of sucrose to D-fructose and a mixture of - and -glucose and the latter product can be monitored by means of a glucose sensor. This scheme has been improved by including glucose mutarotase (EC 5.1.3.3), which converts -glucose into -glucose. Such an enzymatic sensor is termed a sequence sensor. It includes two enzyme layers: the first one contains the auxiliary enzyme and is in contact with the sample solution, whereas the next layer, which contains the indicator enzyme, communicates with the transducer.

An additional enzyme in the biosensor configuration can be included in order to remove interferents. Thus, the above-mentioned sucrose biosensor responds not only to sucrose itself but also to endogenous glucose from biological and foods samples. In order to remove glucose interference, an additional glucose oxidase layer is incorporated in front of the invertase layer. Within this layer, glucose is oxidized and is thus removed from the flux of reactants before reaching the indicator enzyme layer.

A large increase in sensitivity can be achieved by means of a second enzyme that performs substrate recycling. This principle is demonstrated in Figure 3.13 for the case of a lactate sensor. Here, the lactate ion is oxidized to pyruvate by means of oxygen under catalysis by lactate oxidase (LOD). Next, lactate dehydrogenase (LDH) restores the initial analyte molecule and thus assists a recycling process which enhances the response signal arising from either oxygen depletion or peroxide formation. What results is a chemical amplification of the response signal.

Figure 3.13 Chemical amplification by substrate recycling in a lactate sensor.

Clearly, a great expansion of the field of application of enzyme sensor can be achieved by integrating more enzymes into the sensing layer [7, 21]. However, such an approach should be implemented with caution because a multienzyme sensor is more susceptible to interferences and other disturbances caused by various factors affecting each of the enzymes (such as enzyme degradation, inhibition or sensitivity to pH changes).

3.6 Kinetics of Enzyme Reactions

The application of enzymes in analytical chemistry is based on their ability to act as specific catalysts for a broad range of biochemical reactions [3, 22, 23]. When an enzyme and its substrate are present in a solution and certain physicochemical conditions are fulfilled, substrate conversion proceeds steadily. Clearly, such a system is not at equilibrium and its behavior is dominated by kinetic factors. Hence, a preliminary examination of the enzyme kinetics is essential for understanding the underlying principles of enzyme biosensors. The goal of the kinetic approach is to derive the rate equation, that is, an equation giving the reaction rate as a function of relevant concentrations. The reaction rate indicates how fast a reaction proceeds and it represents the number of moles consumed or produced per time unit and volume unit (in mol dm⁻³ s⁻¹). In order to derive the rate equation, a reaction mechanism based on experimental investigation of the reaction system should be assumed.

3.6.1 The Michaelis–Menten Mechanism

A large diversity of reaction mechanisms is possible for enzyme-catalyzed reactions, as emphasized in standard texts [24–26]. The present approach will refer to the Michaelis–Menten mechanism that is a representative one and that highlights some essential features of enzyme kinetics. Denoting by E, S, and P the enzyme, the substrate, and the product, respectively, the Michaelis–Menten mechanism can be formulated as a two-step process (reaction (3.8)), the k symbols being assigned to relevant reaction rate constants:

(3.8)

Accordingly, the first step is an equilibrium reaction driven by the affinity of the substrate for the catalytic site, which yields an enzyme–substrate complex, ES. After the substrate has been converted irreversibly into the product P, the enzyme is released and is able to convert another substrate molecule. The symbols e, s, c, and p will be further used to denote the concentration of the free enzyme, substrate, enzyme–substrate complex, and product, respectively. It will be assumed for simplicity that the substrate concentration remains approximately constant. According to the rules of chemical kinetics, the reaction rate with reference to formation of the product depends on complex concentration as:

(3.9)

As c is an unknown, it will be expresses as a function of known parameters using the steady-state assumption that states that c is time independent (Briggs–Haldane assumption). Accordingly, the rate of ES formation in the first step above should be equal to the rate of ES decay:

(3.10)

This equation can be rearranged in order to derive the expression for the Michaelis–Menten constant (K_M) as follows:

(3.11)

Now, the concentration of the complex ES can be expressed as:

(3.12)

Therefore, the reaction rate equation becomes:

(3.13)

As some enzyme molecules are bound in ES, the concentration of the free enzyme is:

(3.14)

where e_t stands for the total enzyme concentration and c is given by Equation (3.12). By combining Equations (3.11), (3.12) and (3.13), one obtains:

(3.15)

This equation proves that the reaction rate increases with substrate concentration and attains a constant, limiting value () if :

(3.16)

Under these conditions, Equation (3.12) combined with Equation (3.14) proves that all enzyme molecules will be in the form of ES complex, which correspond to the enzyme saturation state. The reaction rate is in this case independent of substrate concentration (zero-order kinetics) but it is proportional to the enzyme concentration. Using Equation (3.16), Equation (3.15) becomes:

(3.17)

Equation (3.17) is known as the Michaelis–Menten equation. It was assumed above that the substrate concentration is constant. In order to fulfill this condition, the experimentally determined reaction rate should be extrapolated to initial moment. The resulting value (that is, initial rate of reaction, ) should be plotted as a function of the initial substrate concentration (s₀) in order to determine K_M and (Figure 3.14). The curve is a hyperbola that tends towards a limit () at substrate concentrations very high with respect to .

Figure 3.14 A plot of enzyme kinetics data according to the Michaelis–Menten equation. Enzyme concentration for curve 2 is twice as high as that for curve 1. Notice that K_M equals the substrate concentration yielding a reaction rate that is half of the maximum value. Substrate determination is best achieved within the quasilinear range (), whereas enzyme determination should be performed within the quasihorizontal region that corresponds to the condition.

At the opposite extreme (), the reaction rate is proportional to the substrate concentration (first-order kinetics) but is independent of the concentration of the enzyme:

(3.18)

The first-order kinetics limit represents the ideal condition for performing substrate determination. When designing an enzyme biosensor, it is therefore crucial to secure a sufficiently low substrate concentration within the enzyme layer. The pre-s factor in Equation (3.18) is the pseudofirst-order rate constant () that depends on the total concentration of the enzyme:

(3.19)

An accurate determination of K_M and can be obtained by means of a linearized form of Equation (3.17) which is known as the Lineweaver–Burk equation:

(3.20)

According to the Lineweaver–Burk equation, a plot of vs. yields a straight line whose intercept is and the slope is ; this enables determining both and . However, this method is statistically inconsistent and the best alternative is the nonlinear regression based on Equation (3.17).

It should be emphasized that K_M is not an equilibrium constant because it is associated with a dynamic system under steady-state conditions. However, if the backconversion of the complex is very fast relative to the second step (), K_M will reduce to:

(3.21)

Only under these special circumstances does the formation of EC occurs under near-equilibrium conditions and K_M then represents the dissociation constant of EC. K_M is, in this case, a measure of the enzyme affinity for substrate; the higher the value of K_M, the lower is the affinity.

In conclusion, the reaction rate of an enzymatic reaction can follow three different kinetic laws, depending on the concentration of the substrate relative to the Michaelis–Menten constant. If , the reaction follows a first order kinetic law with the pseudorate constant defined in Equation (3.19). At the other extreme (), the reaction rate is independent on substrate concentration (Equation (3.16)) and the reaction proceeds according to the zero-order kinetics. In the intermediate case (), a second-order kinetics operates, according to Equation (3.13).

3.6.2 Other Mechanisms

So far, enzyme-catalyzed reactions involving only one substrate have been considered. However, in a large number of cases two or more substrates are involved. For example, the conversion of the enzyme–substrate complex to product may involve a second substrate, W, which causes the second step in reaction (3.8) to be formulated as follows:

(3.22)

It is easy to prove that, in the steady state, the reaction rate is:

(3.23)

Here, w is the concentration of W. Setting (for a high excess of W, its concentration is almost constant), , and causes Equation (3.23) to assume the form of the Michaelis–Menten equation. Therefore, although the overall reaction involves three reactants (S, E, and W), at a high excess of W the reaction is described fairly by a pseudosecond-order kinetic equation.

Multisubstrate reactions are often represented by schemes proposed by Cleland [27] such as that presented in Figure 3.15 for the double displacement mechanism (also termed the ping-pong mechanism). This mechanism operates in reactions involving coenzymes. During such a process, the enzyme alternates between two states that are, for example, the oxidized and reduced forms, in the case of an oxidase.

Figure 3.15 Cleland scheme for a two-substrate reaction that obeys the ping-pong mechanism.

In Figure 3.15, below the horizontal line, the enzyme itself, along with the enzyme complexes are shown. The arrows pointing downwards or upwards indicate substrate binding an product release, respectively. Although the arrows are single-headed, they symbolize as a rule reversible reactions. Often, the relevant rate constants are included on the left or right side of the arrow. Thus, in the scheme in Fig. 3.15, the substrate S₁ binds first to the enzyme to form the ES₁ complex. After ES₁ conversion to E*P₁, the product P₁ and the altered enzyme E* are released. Next, the second substrate S₂ gives the E*S₂ complex that undergoes conversion to EP₂, in which the enzyme is restored to the initial state. Finally, the dissociation of EP₂ yields the product P₂ and the free enzyme. In the particular case of glucose oxidation, E and E^∗ are the enzyme with the FAD group in the oxidized or reduced form, respectively. S₁ and S₂ represent glucose and oxygen, respectively, whereas P₁ and P₂ represent glucono-lactone and hydrogen peroxide, respectively.

The ping-pong mechanism is characterized by the following kinetic equation:

(3.24)

Here, and are constant specific to each of the substrates. If the concentration of S₂ is sufficiently high such that , the above kinetic equation reduces to the Michaelis–Menten equation in , which allows the determination of the constant. If the above inequality is reversed, can be determined in a similar way. These constants, as well as depend on the relevant rate constants in the reaction scheme in Figure 3.15.

Another kind of two-substrate reaction pathway is the single displacement ordered mechanism represented in Figure 3.16. In this case, a ternary complex ((ES₁S₂)) forms by successive reactions of the enzyme with substrates, followed by the conversion of the substrates to products to yield a second ternary complex (EP₁P₂), followed by the stepwise release of products.

Figure 3.16 Schematics of the single displacement ordered mechanism for a two-substrate reaction.

An example of this type is the conversion of ethanol to acetaldehyde by the action of alcohol dehydrogenase, with the coenzyme NAD⁺ acting as electron and proton acceptor (Figure 3.17). This reaction is used in ethanol enzymatic sensors.

Figure 3.17 An example of single displacement ordered reaction: dehydrogenase-catalyzed conversion of ethanol to acetaldehyde.

In summary, many enzymatic reactions involve more than one substrates. Under particular conditions, the kinetic equation of a multisubstrate reaction can be reduced to the Michaelis–Menten equation.

3.6.3 Expressing the Enzyme Activity

The kinetic approach in the previous sections allows the derivation of several physical parameters that characterize the enzyme under study. As in some cases the conversion of ES to product involves several distinct steps, it would be more correct to replace with an overall constant , which can be calculated by means of experimental data as follows:

(3.25)

Hence, is the rate constant at enzyme saturation. This constant is often referred to as the turnover number of the enzyme and is expressed in reciprocal time units (). It represents the number of catalytic cycles that each active site undertakes per unit time under saturation conditions. So, if s⁻¹, the catalytic cycle occurs 10 times a second.

In many real situations, the substrate concentration is very low (); this implies that the free enzyme concentration is approximately equal to the total enzyme concentration (). Taking into account this approximation, and also substituting for in Equation (3.13), this equation assumes the following form:

(3.26)

The second-order rate constant defined by the ratio (dimensions: ) in the above equation is called the specificity constant and is a quantitative measure of the substrate specificity of an enzyme.

Very often, the experimenter has to deal not with pure enzyme but with enzyme samples containing other (inactive) protein species. Besides, some enzymes contain more catalytic sites per molecule and the turnover number, as defined above, cannot be unambiguously determined. A suitable alternative in such instances is to express the quantity of enzyme in an empirical way, by means of the enzyme activity. Enzyme activity represents that amount of the enzyme preparation that catalyzes the conversion of a given quantity of substrate per unit time, under specified conditions (such as temperature and pH):

(3.27)

where is the amount of substrate, is the sample volume, and is the concentration of the substrate. This definition implies that the activity is determined close to the zero-order kinetics region, such as to render it practically independent of substrate concentration. The SI unit for enzyme activity is the katal that represents the amount of enzyme preparation that converts 1 mole of substrate per second (1 katal = mole/s). For example, one katal of trypsin is that amount of trypsin that breaks a mole of peptide bonds per second under specified conditions.

A commonly used value is the enzyme unit (U) that denotes the amount of enzyme that converts 1 μmol of substrate per minute (units: [μmol/min]. 1 U corresponds to 16.67 nanokatals. From the kinetic standpoint, enzyme activity represents an approximation of the maximum reaction rate.

Activity is an extensive quantity. Hence, in order to characterize the enzyme activity independently of its amount, the term specific activity was introduced; it is defined as follows:

(3.28)

The SI unit for specific activity is katal kg⁻¹, but a more practical unit is μmol mg⁻¹ min⁻¹. The specific activity is an indicator of enzyme purity:

(3.29)

Clearly, an impure sample has lower specific activity because some of its content is not an actual enzyme.

3.6.4 pH Effect on Enzyme Reactions

Acid or base groups can be present at the enzyme catalytic site. Consequently, their ionization state can influence the and values and, therefore, the reaction rate. The pH can determine the protonation state of a site involved in the binding of substrate and affect the stability of the enzyme–substrate complex with an immediate effect on the value. On the other hand, the protonation state of a particular site can be essential for the progress of the reaction within this complex. If a change in the protonation state removes the catalytic activity completely, only a fraction of the total enzyme amount will remain active. As the reaction rate is measured with respect to the total enzyme concentration, this change results in a decrease in the value. Often, the combined pH effect on both and causes the reaction rate–pH curve to display a maximum at a specific pH.

Charged substrates may also influence the pH dependence of the reaction rate either directly or indirectly, as they affect the local ionic strength and thereby the thermodynamic activity of the reactants.

Moreover, the transduction process itself can be affected by pH such as in the case of NH₃- or CO₂-linked transduction. At a high pH, protonation of the above compounds leads to the formation of or , respectively. Consequently, the response generated by a gas-sensitive transducer is diminished with respect to the response obtained at an optimum pH.

In summary, an enzyme reaction and, implicitly, the response of an enzymatic sensor can be strongly dependent on pH. Hence, this parameter should be controlled by means of a pH buffer system whose components do not participate in the enzyme-catalyzed reaction.

3.6.5 Temperature Effect on Enzyme Reactions

Like any chemical reaction, the rate of an enzyme-catalyzed reaction increases as the temperature is raised. The Michaelis–Menten equation includes a reaction rate constant () and a pseudoequilibrium constant () that are both temperature dependent. The effect of temperature on the rate constant is given by the Arrhenius Equation (3.30) that demonstrates an exponential increase in the rate constant with the temperature, the steepness of the variation being determined by the activation energy (). In this equation, A is a constant factor R is the ideal gas constant and T is the absolute temperature.

(3.30)

The effect of temperature on can be expressed by the van't Hoff equation, which includes the reaction standard Gibbs energy for the formation of the enzyme–substrate complex ().

(3.31)

where B is a constant. is always positive, whereas can be either positive or negative. Consequently, always increases with temperature, whereas can increase or decrease with this parameter. As , the reaction rate will generally increase with temperature up to a maximum value. Further increase is prevented by enzyme denaturation, which leads to a sharp decrease in enzyme activity. As a rule, enzyme processes should be carried out about 10–20 °C below the maximum activity temperature in order to avoid enzyme denaturation.

3.6.6 Outlook

Enzyme-catalyzed reactions can follow a large variety of pathways. A plot of the initial reaction rate vs. substrate concentration (as in Figure 3.14) is the first test for assessing the reaction mechanism. A double-reciprocal plot according to Equation (3.20) is actually much more informative at this stage. Any deviation from the Michaelis–Menten behavior suggests that additional factors come into play (such as inhibition by substrate or product) or the mechanism does not match the Michaelis–Menten assumptions. Under particular conditions, a more complicated mechanism can be described by the Michaelis–Menten equation provided that the characteristic constants are properly defined in accordance with mechanism details.

The Michaelis–Menten equation puts into evidence two limiting cases, according to the substrate concentration relative to the Michaelis–Menten constant. If the substrate concentration is very low with respect to this constant, the reaction rate is proportional to the substrate concentration. This case represents the first-order kinetics limit. Enzymatic sensors designed for substrate determination should operate under these conditions. The opposite case, of a high substrate concentration, corresponds to the zero-order kinetics regime, in which the reaction rate is proportional to enzyme concentration but independent of substrate concentration. Conditions close to this limit are convenient for performing enzyme quantifications when the enzyme is used as a label tag or when the sensor is designed for inhibitor determination.

Questions and Exercises (Section 3.5)

1. What are the key assumptions in the Michaelis–Menten mechanism?

2. What is the meaning of the Michaelis–Menten constant?

3. In what way can the substrate concentration affect the kinetics of an enzyme reaction? What conditions are suited for determining the substrate?

4. Comment on possible two-substrate mechanisms. In what conditions does the Michaelis–Menten equation represent a fair description of the reaction kinetics for such mechanisms?

5. Summarize the quantities used to assess the catalytic activity of an enzyme and point out the specific conditions for each of them.

6. What is the effect of pH and temperature on enzyme reactions?

7. The following kinetic data were obtained for an enzyme-catalyzed reaction.

a. Plot the above data according to the Michaelis–Menten equation and estimate the values of and from the curve.

b. Process the Michaelis–Menten equation in order to derive the following linear relationships (1) vs. (Lineweaver–Burk equation); (2) vs. (Hanes equation); (3) vs. (Eady–Hofstee equation).

c. Plot the kinetic data according to the previously derived equations and calculate the values of and using the slopes and intercepts of the plotted lines.

Hints and answers: (c) : = 0.069 μmol/L min; mM. Small differences between the values determined by each of the above plots may occur due to the effect of error propagation when calculating the new variables. These differences are insignificant if the experimental data are accurate enough. The most reliable results are obtained if experimental data are processed by nonlinear regression according to the Michaelis–Menten equation.

8. An enzymatic reaction occurs as follows: S + NAD⁺ = P + NADH. In order to assess the enzyme, the progress of the reaction was determined by recording NADH absorbance at 340 nm (molar absorptivity: L mole⁻¹ cm⁻¹) in a cell containing solution. The absorbance (A) varied linearly with time at the beginning and changed by units within the time interval .

a. What is the role of NAD⁺ in this reaction?

b. Calculate the enzyme activity in katal and enzyme units.

c. Calculate the specific enzyme activity assuming that the solution contains 0.02 mg enzyme.

9. Hints and answers: Convert all quantities into SI units. is proportional to , in accordance to Beer's law. Activity = 0.84 nanokatal = 0.05 U. Specific activity = 42 μkatal/s kg = 2.5 U/mg.

In order to determine the enzyme activity, the substrate concentration should be selected such that the reaction rate is as close as possible to its maximum value. For an enzyme with mM, calculate the lowest substrate concentration that leads to a deviation of the reaction rate not lower than 95% of the maximum reaction rate.

Hints and answers: Rearrange the Michaelis–Menten equation such as to obtain the ratio as a function of , equate this ratio to 0.95 and solve for .

Answer:

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3.7 Enzyme Inhibition

Some compounds termed effectors can bind to an enzyme molecule and thereby diminish or enhance its activity. In the first case, such a compound acts as an inhibitor; in the second one, it performs as an activator [24, 28]. Enzyme inhibition allows the quantification of inhibitor concentration by standard nonsensor assay methods but also forms the basis for inhibitor determination by means of enzyme biosensors [29–31]. This section reviews first the principles of enzyme inhibition and then presents the basics of inhibition-based biosensors.

3.7.1 Reversible Inhibition

Reversible inhibition involves a reversible reaction between the inhibitor and the enzyme (E); the enzyme can be in the free state or can be part of an enzyme–substrate (ES) complex. Thus, the inhibitor (I) may form one of two kinds of inactive complex: a binary (EI) or a ternary (ESI) complex. Therefore, in order to derive kinetic equations for inhibited catalysis, the following reactions should be considered:

• Enzyme reaction in the absence of the inhibitor:

(3.32)

• Reversible binding of the inhibitor to the free enzyme:

(3.33)

• Reversible formation of an enzyme-substrate-inhibitor ternary complex

(3.34)

(3.35)

Reversible inhibition is characterized by the inhibition constant, , which is the dissociation constant for each of reactions (3.33) to (3.35). The reaction rates in the presence () and in the absence () of the inhibitor are conveniently compared using the degree of inhibition, d_i:

(3.36)

Various types of reversible inhibition can be defined by combinations of the above reactions (see Table 3.5). The reaction rate for the inhibited reaction can be derived under the steady-state condition using a procedure similar to that employed in Section 3.7.1. It can be proved in this way that the kinetic equation in the presence of reversible inhibition has the same form as the Michaelis–Menten equation but either or (or both) are replaced by the apparent parameters and . and may be dependent on both inhibitor concentration (i) and the inhibition constant. The combined effect of these quantities is indicated the over-unity parameter :

(3.37)

Table 3.5 Selected mechanisms of reversible inhibition.

Competitive inhibition occurs if the inhibitor binds to the free enzyme (reaction (3.33)), either at the active site or at another (distant) site on the enzyme, with destructive effects on catalytic activity. As a result, the concentration of the enzyme available to the substrate is reduced. Thus, hydroxyurea, a urea-analog, is a competitive inhibitor of urea hydrolysis in the presence of soya bean urease. As in the case of urea, it forms a coordination bond with a nickel atom at the active site but yields an inactive complex. It is worth noting that fluoride ions also cause inhibition by bonding to the nickel atoms in the enzyme [32].

Competitive inhibition has no effect on but is replaced by the greater parameter . Due to the competition of substrate and inhibitor for the same site, the degree of inhibition decreases with increasing the substrate/inhibitor concentration ratio.

In uncompetitive inhibition an inhibitor binds only to the enzyme–substrate complex (reaction (3.34)) but not to the free enzyme. The formation of the ternary complex prevents the substrate from being converted to the final product. Both and are lowered by uncompetitive inhibition. As there is no competition between substrate and inhibitor for the same binding site, an increase in the substrate concentration does not overcome the uncompetitive inhibition. Conversely, at a constant inhibitor concentration, the degree of inhibition may increase with the substrate concentration because the chance of forming the inert EIS species is thus enhanced.

In noncompetitive inhibition the inhibitor can combine with both the free enzyme and the enzyme–substrate complex (reactions (3.33) and (3.34)) in order to give a dead-end complex. This implies that the inhibitor binds at a site other than the active one and brings about a conformational change that removes enzyme affinity for substrate. By virtue of this two-site feature, the substrate can also combine with the EI complex (reaction (3.35)). For the same reason, noncompetitive inhibition is not alleviated by increased substrate concentration. A specific inhibition constant should be defined in this case for each of reactions (3.34) and (3.35).

The effect of inhibition on reaction parameters is illustrated in Table 3.5 for the particular case in which the above constants are equal. If this condition is not fulfilled, decreases, while may increase or decrease with increasing inhibitor concentration. Often, the term mixed inhibition is assigned to this general case.

The most frequent type of inhibition is the competitive one. Uncompetitive and noncompetitive inhibition are rare in nature [2].

3.7.2 Irreversible Inhibition

Irreversible inhibitors interact with enzymes so strongly that the concentration of active enzyme is reduced from an initial value to , according to a 1-to-1 stoichiometry. Consequently, the maximum reaction rate in the presence of the inhibitor is always less than the normal value:

(3.38)

A well-known example is represented by organophosphorus derivatives (widely employed as pesticides) that react with –OH groups in serine side chains of some enzymes such as acetylcholine esterase.

In contrast to reversible inhibition, which is a fast, diffusion-controlled process, irreversible inhibition is a slow reaction that needs an incubation time in order to be completed. During this stage, enzyme activity decreases exponentially.

3.7.3 Enzymatic Sensors for Inhibitors: Design and Operation

In order to detect an enzyme inhibitor, the sensor should be operated under zero-order kinetics, as pointed out in Section. Inhibitor determination is therefore prone to interference by any factor affecting the enzyme activity, such as pH, temperature and enzyme degradation.

Determination of the inhibitor can be performed under steady-state conditions by means of a calibration function that expresses the percentage of inhibition (, Equation (3.39)) vs. inhibitor concentration. Here and stand for sensor response in the absence and in the presence of inhibitor, respectively.

(3.39)

Clearly, this equation is formally analogous to Equation (3.36) defined for the inhibition of a dissolved enzyme.

The calibration line is, as a rule, nonlinear but, under properly optimized conditions, a quasilinear region can be identified. A log plot can sometimes display a better linear feature. In some instances, a plot of the residual activity vs. inhibitor concentration yields a convenient calibration graph. The main parameters to be optimized are the immobilization procedure, the enzyme loading, substrate concentration, pH and incubation time.

Alternatively, a kinetic approach can be implemented. In this case, after the reaction attains the steady state with the substrate alone, the inhibitor is added and the rate of inhibition is assessed as the slope of the signal–time curve (), which is a function of inhibitor concentration.

In principle, any transduction method that is compatible with the enzyme reaction can be implemented. Much research work in this respect has been devoted to electrochemical methodologies [33–35].

A critical issue with inhibitor assay is the limited selectivity. As the inhibition phenomenon can be caused by very different type of compounds (for example, metal cations and various inorganic or organic species) the selectivity is poor [36]. That is why an inhibitor sensor should be appraised in natural samples in order to assess how useful it is for solving real problems. Selectivity of enzyme-inhibition-based biosensors can be enhanced by using an array of sensors, each of them based on a different enzyme, with subsequent chemometric treatment of data. Alternatively, the assay can include a separation step in order to get rid of interferences. Limited selectivity, however, can be an advantage if the sensor is used for screening the toxicity of environmental samples.

Another critical aspect is the reactivation of the enzyme after being exposed to an inhibitor-containing sample. Reactivation should be designed according to the chemistry of each enzyme–inhibitor couple. So, reversible inhibition by metal ions can be removed by means of a strong chelating agent, such as EDTA. In many instances, reversible inhibition by organic compounds can be eliminated by soaking the sensor in a buffer solution at the optimum pH of the enzyme. As the reactivation is not always total, the calibration graph should be checked regularly. Reactivation is much more difficult in the case of irreversible inhibition, but even in this instance, suitable procedures may be devised. If reactivation proves not to be feasible, it is possible to resort to the disposable-sensor approach.

The detection limit for an inhibitor sensor depends on both the substrate concentration and enzyme loading. In the case of competitive inhibition, the limit of detection decreases as the substrate and enzyme concentration decrease but is limited by the characteristic detection limit of the transduction process.

As the analysis by means of inhibition-based biosensors involves several steps (such as pH adjustment, incubation and regeneration) it is convenient to include the sensor in an automatic flow-analysis system.

A comprehensive overview of the performance of electrochemical biosensors developed for the determination of inhibiting species is given in [37].

3.7.4 Applications of Enzyme-Inhibition Sensors

Enzyme-inhibition methods have been applied mostly to determine hazardous substances such as pesticides and heavy-metal ions. The choice of a particular enzyme is made with reference to the properties of the targeted pollutant. Widely used are choline esterase enzymes [12]. Thus, acetylcholine esterase (AChE, EC 3.1.1.7) [19, 39] is an enzyme that catalyzes the hydrolysis of the neurotransmitter acetylcholine, producing choline and acetate (see also Figure 3.10):

(3.40)

Similarly, butyrylcholine esterase (BuChE, EC 3.1.1.8) acts on the synthetic substrate butyrylcholine. In the above reactions, carbamate pesticides induce reversible, competitive inhibition, while organophosphorus derivatives are irreversible inhibitors via esterification to a hydroxyl group in serine.

As an acid product results in reaction (3.40), transduction can be performed simply by means of a potentiometric or optical pH probe. Properly selected synthetic substrates can enhance the sensitivity. Thus, a nonfluorescent substrate that yields a fluorescent product enables a very low limit of detection to be achieved owing to the intrinsic sensitivity of fluorimetry. Alternatively, the substrate can be selected so as to give an electrochemically active product (such as thiocholine), which allows amperometric transduction. On the other hand, choline oxidase can be added to the sensing layer in order to convert choline (resulted from reaction (3.40)) into betaine aldehyde with oxygen consumption and hydrogen peroxide formation. With such a bi-enzyme sensor, transduction can be performed by the electrochemical monitoring the concentration of either oxygen or hydrogen peroxide.

Also useful for pesticide determination are oxidoreductase enzymes (such as glucose oxidase and tyrosinase) and hyrolases (such as alkaline phosphatase and urease).

Heavy-metal ions (Hg²⁺, Cu²⁺, Pb²⁺, Cd²⁺, Ag⁺) cause enzyme inhibition by strong interaction with thiol groups near the active site of the enzyme. Urease, choline esterases and oxidases are among the enzymes mostly employed in developing heavy-metal ion sensors based on this principle. Selectivity is, as a rule, very poor, and determination of an individual metal ion in the presence of similar interfering species is hardly achievable.

In conclusion, enzyme inhibition represents a convenient approach for performing the determination of organic and inorganic pollutants in environment samples as well as in foods. Application of nanomaterials is expected to bring about further progress in this field [40]. However, it should be kept in mind that the selectivity of inhibition sensors could be problematic.

Although much research effort has been exerted in this field, there are still many concerns regarding the reliability of the sensor in applications to real samples.

Exercises (Section 3.6)

1. Download the structure 1IE7 in the Protein Data Bank (http://www.pdb.org/pdb/home/home.do) and examine the binding of the phosphate ion inhibitor to the active center of urease.

2. In the absence of inhibition, of an enzyme was of 8 μM. In the presence of 3 μM inhibitor, the apparent Michaelis–Menten constant () was 12 μM. Calculate the inhibition constant.

Answer: 6 µM

3. Derive equations relating to substrate and inhibitor concentrations for each kind of inhibition in Table 3.5 and discuss the effect of inhibitor and substrate concentration on . Prove that, for competitive inhibition, increases if the ratio decreases at a constant inhibitor concentration.

Hint: use dimensionless concentrations .

Answer: Competitive: ; uncompetitive: ; noncompetitive: .

4. The concentration of the mercury ion can be determined by means of a urea sensor consisting of a urease layer attached to a CO₂ probe (log-type transduction). Using calibration data in the table below, plot the percentage of inhibition vs. log [Hg²⁺], define the linear response range, calculate the sensitivity within the linear region and calculate the Hg²⁺ concentration in two samples yielding %I = 38 and 67, respectively.

Hint. A linear calibration function can be identified within the intermediate concentration range.

Answer: 0.07 and 0.27 μM.

5. An urea sensor, which was used to determine the fluoride ion by inhibition, was checked for the effect of the enzyme activity in the sensing layer. To this end, the effect of fluoride ion concentration on the percentage of inhibition was determined at two different enzyme activities, as shown in the Table below. Plot the percentage of inhibition vs. the fluoride concentration and comment on the effect of enzyme activity on the working range and limit of detection.

Hint. Assume that the limit of detection is the fluoride concentration at which the percentage of inhibition is 10%.

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3.8 Concluding Remarks

Enzymes are proteins that catalyze chemical reactions in biological systems. Under suitable conditions, enzymes isolated from biological preparations display catalytic activity in artificial systems as well. This property is utilized in the development of enzymatic sensors. An enzymatic sensor is obtained by integration of an enzyme with a transduction device that indicates the concentration of a reactant or product of the enzymatic reaction. Integration of the enzyme and the transducer is achieved by enzyme immobilization at the surface of the transducer.

As long as the enzyme substrate is available, an enzyme reaction continues to proceed. Therefore, the process occurring in an enzymatic sensor is a dynamic process, characterized by its reaction rate. Substrate supply occurs by diffusion from the solution to the active part of the sensor. As diffusion has a limited rate, a steady state is reached; in the steady state, the concentration of reactants and products at the transducer surface is constant. As a result, the sensor response is also constant and is determined either by the diffusion rate or by the reaction rate or both. The next chapter demonstrates that the best conditions for the determination of the substrate are achieved when the enzymatic reaction is of the first order with respect to the substrate and the rate of the overall process is determined by diffusion.

Application of enzymes in chemical sensing is not limited to the determination of the enzyme substrate. Other applications are based on the measurement of the activity of the enzyme incorporated in an enzymatic sensor.

Enzyme activity can be affected by inhibitors such as toxic metal ions or certain organic compounds. Therefore, enzymatic sensors can be used for the determination of enzyme inhibitors. In such applications, the sensor should be operated such that the enzyme reaction occurs close to the zero-order kinetic regime. Under these conditions, the response is independent on the substrate concentration but is dependent on the enzyme activity.

Monitoring of enzyme activity is also of great interest in the application of enzymes as signaling labels in affinity sensors. In such applications, an enzyme-tagged species is allowed to interact with the sensing layer such that the amount of enzyme incorporated in this layer is a function of the analyte concentration. In the presence of added substrate, the sensor functions as an enzymatic sensor acting as an indicator of the amount of incorporated enzyme. The optimal kinetic regime in this case is the zero-order regime in which the response depends on the concentration of the incorporated enzyme. In order to obtain good sensitivity, enzymes with a high turnover number are used as labels.

In conclusion, owing to their broad range of applications, enzymes occupy a central role in chemical-sensor science and technology.

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