6. Enzyme activators

Activators are the molecules that enhance the rate of reaction by multi-fold which may or may not get utilized during the catalytic reaction progress. Depending upon their interaction with the enzymes, they are classified into various groups. The prosthetic groups generally bind covalently with the enzyme and act as a source of hydrogen or phosphorus group. Prosthetic


Table 6. Different types of enzyme activator and their examples.

group forms part of active group undergoes changes during reaction. The co-enzymes do not bind covalently with enzymes and very essential for the activity of the enzymes. Co-enzymes get chemically altered temporarily during the reactions which get reconverted into its original form by the same or another enzyme. The enzymes associated co-enzyme usually catalyses bisubstrate reactions [3, 4]. The co-factors are complex organic molecules or metal ions. Some of the activators are listed in Table 6.

#### 7. New developments in enzyme inhibition

to explore for their catalytic activity. It can also suggest the best modification that can serve for the developing potent inhibitor from the existing drugs. By using data from various sources such as structure of inhibitors from the various crystallographic databases and crystal structures of enzymes, enzyme-substrate and enzyme-inhibitor complex from the various PBD databases can be imported and analysed for the prediction of inhibition capacities of the various molecules [113]. Various ab initio and drawing softwares are used for the prediction of the structure of the inhibitors which are not present in the database. There spatial arrangement and group and chain positions are studied and model is minimized to confirm with lowest energy status. This is then docked inside the active site of the enzyme and positioned to have a maximum favourable interaction and tried for the energy minimization of the system. Thus, the finalized inhibitor then modified by various methods discussed earlier (Section 7.1) and analysed again in the software [77, 84, 114]. The use of high-resolution NMR studies or by homology modelling (minimum 30%) can give the relative desired protein structure. This can be used for the further docking experiments against the library of the inhibitors using computerized modelling software. The prediction of the active site on the surface of enzyme (pharmacophore) is done by docking the multiple inhibitor molecules. Because of the basic assumption of the rigid structure of the protein, the predicted inhibitor may differ in activity with the dynamic enzymes molecule [115, 116]. Thus, the developed lead compounds then can be applied in pharmaceutical, agrichemical industries and in the study of metabolic flux,

Activators are the molecules that enhance the rate of reaction by multi-fold which may or may not get utilized during the catalytic reaction progress. Depending upon their interaction with the enzymes, they are classified into various groups. The prosthetic groups generally bind covalently with the enzyme and act as a source of hydrogen or phosphorus group. Prosthetic

1 H-transfer reaction (vitamin-based activators) (Vitamin-based activators) NAD, NADP, FMN, FAD

4 Group transfer ATP, CDP, VDP, phosphoadenosine phosphosulfate 5 Transfer (non-vitamin-based activators) (PAPs), heme-group, s-adenosylmethionine

3 Group transfer (vitamin based activators) CoA, CoASH, TPP, pyridoxal phosphates, tetrahydrofolic acid

(FH4), biotin, cobamide coenzyme, vitamin K, vitamins C

Ca2+—requires in functioning of muscle and blood clotting,

Fe2+ and Fe3+—heme-nonheme containing enzymes Cu1+ and Cu2+—electron transport systems Zn2+—present in dehydrogenase, polymerase Mo6+—required for functioning of xanthanine oxidase

essential for formation of cAMP

2 H-transfer (non-vitamin-based activators) Lipoic acid, biopterin, coenzyme Q

6 Metals Mg2+—ATP utilizing enzymes

genetic engineering and molecular biology for the betterment of life.

Sr. no. Reaction type Activators used

Table 6. Different types of enzyme activator and their examples.

6. Enzyme activators

112 Enzyme Inhibitors and Activators

In the 1970s and 1980s, the stopped flow and continuous flow experiments brought about the major experimental advancement in enzyme kinetics field by allowing the process to reach steady state. The complicated enzyme kinetics and intermediates formed during the process are decoded using rapid sample mixing and high time resolution monitoring [50, 117, 118]. The application of single-molecule fluorescence imaging at room temperature for singlemolecule manipulation has been applied to study the single molecule enzyme in 1990s [119, 120]. It gave a major breakthrough in the field of enzyme kinetics. Single-molecule enzymology has elaborated on molecular level insights on molecular motors and nucleic acid enzymes. In single molecule experiments, wherein the time pattern of enzymatic turnovers was analysed, it is observed that the catalytic activity is not consistent over time. The reaction follows parallel reaction pathway through different enzymatic conformation with different rate constants and rate constant for the rate-limiting step might become a function of time. This phenomenon is called dynamic disorder [120–123]. Single molecule experiments have shown that the stochastic waiting time of an enzymatic reaction exhibits a distribution of an exponential rise followed by an exponential decay [124, 125]. For a single molecule with slowly interconverting conformational states with different kcat and Km, it follows that

$$\frac{1}{\langle T \rangle} = \frac{k\_{\text{cat}}[S]}{[S] + K\_{\text{m}}} \tag{74}$$

Where 〈T〉 is the mean of the stochastic waiting time and the overbars denote the weighted averages of kcat and K<sup>m</sup> of different conformational state.

In case of reversible reactions, Hill showed that forward and backward reaction fluxes (J <sup>+</sup> and J �, respectively) can be related to the chemical potential difference, Δμ, between product and the substrate:

$$
\Delta \mu = -\mathbf{k} T \ln \left( \frac{\mathbf{J} + }{\mathbf{J} -} \right) \tag{75}
$$

where k is the Boltzmann constant and T is the absolute temperature. It also serves as bridge between the thermodynamic driving force and enzymatic kinetics.

A most commonly used fluorogenic substrate, resorufin â-D-galactopyranoside (RGP), is also hydrolysed by the enzyme, yielding a fluorescent product, resorufin. The fluorescent burst released during the process is used for the prediction of the single enzyme kinetics. The location, brightness and spectral properties of the fluorophore-labelled molecule affect the measurement of the signal significantly. This resolution directly yields kinetic information, for example, when measuring: (a) diffusion coefficients with respect to changes in the position of molecule (b) timelapse experiments to analyse the systematic change in the brightness of fluorogenic substrate turnover with time or (c) temporal changes in molecule conformation or configuration when observing changes in FRET between a judiciously placed donor-acceptor pair.

The microscopic validity of chemical master equation (CME) has also been tested and verified by molecular dynamics for dilute chemical systems and using Brownian dynamics simulations for non-dilute crowded systems. The major assumption underlying the CME is that reactions are occurring in well-mixed environments. The characteristics of reactivity fluctuations in individual enzyme molecules relate to the second moment of turnover time statistics which can be defined by the randomness parameter R and time statistics. The randomness parameter R tends to become 1, when the waiting time distribution is a single exponential decay function. Any deviation of R from this predicted value is an indication of dynamic disorder [121]. When this is applied for the inhibition reaction, the expressions for the waiting time distributions for inhibition reactions became cumbersome. If more than one intermediate steps are present in the given set of reactions, then the chemical master equations become more and more complex. To avoid such complications, Chaudhary has used a simple analytical model based on the first passage time distribution between successive catalytic turnover events. This probability distribution function (PDF) is the moment of one monitored transition. If ϕ(t)dt is the probability of observing the next monitored transition between time t and (t+ dt) after this time moment. The assumption made is that there is formation of product molecules with regeneration of the free enzyme. Such events are actually detectable in single-molecule fluorescence experiments [126]. These experiments have given the final expression for competitive inhibition can be given as

$$\langle t\_{\text{compressible}} \rangle = \frac{[\mathcal{S}] + [I]\frac{k\_3(k\_{-1} + k\_2)}{k\_1 k\_{-3}} + \frac{(k\_{-1} + k\_2)}{k\_1}}{k\_2 [\mathcal{S}]} \tag{76}$$

$$\left< t\_{\text{uncompetitive}} \right> = \frac{[\text{S}] + [I][\text{S}]\frac{k\_3}{k\_{-3}} + \frac{(k\_{-1} + k\_2)}{k\_1}}{k\_2[\text{S}]} \tag{77}$$

Various researchers are applying various approaches to derive rate expression for the enzymatic reaction, which are under continuous evaluation to finalize more generalized and simplistic equations.

#### 8. Conclusion

Biocatalysis has evolved as a promising lead to make the chemical process more sustainable, green and environment friendly. The main challenge in biocatalysed reactions is their industrial viability and economical aspects. The advancement in genetic engineering, medium engineering and immobilization technology has made them more robust to sustain the industrial environment. To transform the lab scale process to industrial scale, the understanding of the enzyme kinetics, inhibition and activation becomes very essential. The fragile nature of the enzymes makes them more sensitive towards the changes in medium and physical parameters of the surrounding environment. The various physical parameters such as temperature, pH, microwave and other radiations exposure, immobilization on different support affect the activity of the enzyme and in turn the kinetics of the reaction. The kinetics of the enzymes become more complex when the reaction becomes multi-substrate compared to single substrate reactions. The different kinds of methodologies and plots are used to predict the reaction kinetics of the multi-substrate reactions. The pattern observed during the analysis of the obtained experimental data is used to predict the model for the reactions such as ping-pong bi-bi or ternary complex model and mechanism of the reaction. The obtained model is then solved using various non-linear regression softwares available for the prediction of kinetic constants for the reaction. The inhibition or activation of the enzyme with the chemical entities or the reactant itself further modifies the reaction kinetics and in turn model of the reaction. To study these phenomena, a systematic research methodology needs to be followed to predict the exact reaction kinetics. The finding then can be used to design new enzyme inhibitors, activators which can be applied as possible drug molecules or for the prediction of the mechanism of the enzyme from the same family. This opens up the new area of the application such as pharmaceutical, molecular modelling, genetics studies and industrial production of fine and bulk chemicals. The use of the continuous and stopped flow experiments is becoming a new field to explore and understand enzyme kinetics and its inhibition to better extend.
