Is it possible to separate the binding and catalysis of an enzyme in two steps?

Is it possible to separate the binding and catalysis of an enzyme in two steps?

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Is it possible to do the following:

  1. Enzyme E binds to its substrate S without catalysis;
  2. Add a controllable stimulus, such as light, adding or removing chemicals;
  3. The enzymatic reaction is triggered by the stimulus.

The word controllable means I can add the stimulus at any time I want. Before I add the stimulus, the enzyme keeps binding to the substrate specifically but no reaction takes place.

This is what I mean by separating binding and catalysis in two steps.

In the case of allosteric regulation, some chemicals will inhibit the activity of an enzyme. For example, ATP will inhibit the activity of phosphofructokinase 1 (PFK1). But I'm not sure whether this allosteric inhibition also hinders PFK1's binding to the substrate, which does'nt satisfy my description above.

4.1: Basic Principles of Catalysis

  • Contributed by Kevin Ahern, Indira Rajagopal, & Taralyn Tan
  • Professor (Biochemistry and Biophysics) at Oregon State University

A printable version of this section is here: BiochemFFA_4_1.pdf. The entire textbook is available for free from the authors at

If there is a magical component to life, an argument can surely be made for it being catalysis. Thanks to catalysis, reactions that can take hundreds of years to complete in the uncatalyzed &ldquoreal world,&rdquo occur in seconds in the presence of a catalyst. Chemical catalysts, such as platinum, can speed reactions, but enzymes (which are simply super-catalysts with a &ldquotwist,&rdquo as we shall see) put chemical catalysts to shame (Figure 4.1). To understand enzymatic catalysis, it is necessary first to understand energy. Chemical reactions follow the universal trend of moving towards lower energy, but they often have a barrier in place that must be overcome. The secret to catalytic action is reducing the magnitude of that barrier.

Figure 4.1 - Rate enhancement for several enzymes Image by Aleia Kim

Before discussing enzymes, it is appropriate to pause and discuss an important concept relating to chemical/biochemical reactions. That concept is equilibrium and it is very often misunderstood. The &ldquoequi" part of the word relates to equal, as one might expect, but it does not relate to absolute concentrations. What happens when a biochemical reaction is at equilibrium is that the concentrations of reactants and products do not change over time. This does not mean that the reactions have stopped. Remember that reactions are reversible, so there is a forward reaction and a reverse reaction: if you had 8 molecules of A, and 4 of B at the beginning, and 2 molecules of A were converted to B, while 2 molecules of B were simultaneously converted back to A, the number of molecules of A and B remain unchanged, i.e., the reaction is at equilibrium. However, you will notice that this does not mean that there are equal numbers of A and B molecules.

What are Catalysts?

Catalysts have no effect on the equilibrium constant and thus on the equilibrium composition. Catalysts are substances that speed up a reaction but which are not consumed by it and do not appear in the net reaction equation. Also &mdash and this is very important &mdash catalysts affect the forward and reverse rates equally this means that catalysts have no effect on the equilibrium constant and thus on the composition of the equilibrium state . Thus a catalyst (in this case, sulfuric acid) can be used to speed up a reversible reaction such as ester formation or its reverse, ester hydrolysis:

Figure (PageIndex<1>): An acid catalyzed reactions

The catalyst has no effect on the equilibrium constant or the direction of the reaction. The direction can be controlled by adding or removing water (Le Chatelier principle).

Catalysts function by allowing the reaction to take place through an alternative mechanism that requires a smaller activation energy. This change is brought about by a specific interaction between the catalyst and the reaction components. You will recall that the rate constant of a reaction is an exponential function of the activation energy, so even a modest reduction of (E_a) can yield an impressive increase in the rate.

Catalysts provide alternative reaction pathways

Catalysts are conventionally divided into two categories: homogeneous and heterogeneous. Enzymes, natural biological catalysts, are often included in the former group, but because they share some properties of both but exhibit some very special properties of their own, we will treat them here as a third category.


Cytochromes P450 are ubiquitous enzymes accepting a tremendous number of substrates and catalyzing a broad range of reactions with potential applications in biotechnology and synthetic biology.

P450s were engineered to catalyze abiotic reactions such as carbene or nitrene transfers, opening up completely new perspectives in synthetic chemistry.

Lately, P450s have successfully been introduced into artificial multi-enzyme cascades, both in vitro and in vivo, providing alternative routes for retro-synthetic production of high-value oxyfunctionalized compounds.

Harnessing the synthetic potential of P450s in chemo-enzymatic processes or as part of reconstituted biosynthetic pathways in microbial hosts provides promising strategies for de novo synthesis of synthons and complex natural products, even though there are still some obstacles to overcome.

Cytochromes P450 (P450 or CYP) are heme-containing enzymes that catalyze the introduction of one atom of molecular oxygen into nonactivated C–H bonds, often in a regio- and stereoselective manner. This ability, combined with a tremendous number of accepted substrates, makes P450s powerful biocatalysts. Sixty years after their discovery, P450 systems are recognized as essential bio-bricks in synthetic biology approaches to enable production of high-value complex molecules in recombinant hosts. Recent impressive results in protein engineering led to P450s with tailored properties that are even able to catalyze abiotic reactions. The introduction of P450s in artificial multi-enzymatic cascades reactions and chemo-enzymatic processes offers exciting future perspectives to access novel compounds that cannot be synthesized by nature or by chemical routes.

Structure And Function Of Enzymes

What are enzymes and what do they do in our bodies? Enzymes are basically proteins that are produced by living organisms to bring about certain metabolic and biochemical reactions in the body. They are biological catalysts that speed up reactions inside the body.

What Is The Structure Of An Enzyme?

Enzymes, as mentioned above, are biological catalysts. While they hasten or speed up a process, they are actually providing an alternative pathway for the process. But, in the process, the structure or composition of the enzymes remain unaltered.

Enzymes are actually made up of thousands of amino acids that are linked in a specific way to form different enzymes. The enzyme chains fold over to form unique shapes and it is these shapes that provide the enzyme with its characteristic chemical potential. Most enzymes also contain a non-protein component known as the co-factor.

An enzyme’s function is intrinsically linked to its three-dimensional structure, determining how it performs substrate binding, catalysis, and regulation. X-ray crystallography has been the most important technique in the development of our understanding of enzyme structure and function. Nuclear magnetic resonance (NMR) has also been used successfully to study many structures, but crystallography remains the principle technique for structure elucidation. The first enzyme to be crystallised and have its structure successfully solved was chicken egg lysozyme in 1965. Importantly, as well as the structure of the free enzyme, it was possible to crystallise lysozyme with a substrate analogue bound in the active site. This structure, allowed the proposal of a chemical mechanism for the enzyme, based on positioning of groups around the site of substrate cleavage. The use of crystal structures with bound substrate and transition state analogues has helped to reveal the catalytic mechanisms of countless enzymes since.


Larger proteins tend to fold into a series of smaller domains, each of which forms a self-contained structural unit. These domains are often described as the units of evolution because they can often be swapped between proteins without disturbing the folding of other parts of the protein and thus novel functions can be created by novel combinations of domains within a single protein. In enzymes, certain functions are often contained within a domain. For instance, the nucleotide-binding Rossmann domain is found combined with a diverse range of separate catalytic domains, allowing each enzyme to bind similar nucleotide cofactors such as nicotinamide adenine dinucleotide (NADH), nicotinamide adenine dinucleotide phosphate (NADPH) and flavin mono-nucleotide (FMN), but perform quite different chemistry. Figure 1.9 shows two different Rossmann domain-containing enzymes: glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and 1-deoxy-d-xylulose-5-phosphate reductoisomerase (DXR). Both enzymes contain the Rossmann domain with a common 3 parallel strand β sheet flanked by α helices. This sheet binds to the cofactor NAD in the case of GAPDH and NADP in the case of DXR. The remainder of the enzyme structure and functon is completely unrelated and contain quite different catalytic residues which allow them to catalyse their different reactions.

Active Sites And Clefts

Although enzymes are often large molecules comprising many hundreds of amino acids, the functional regions of an enzyme are generally restricted to clefts on the surface that comprise only a small part of the enzyme’s overall volume. The most important of these regions is the active site – the pocket or cleft in which the enzyme binds the substrate and in which the catalytic chemistry of the enzyme is performed. Analysis of enzyme structure and function have shown that active sites tend to be formed from the largest cleft on the surface of the protein.

Phosphofructokinase catalyses the phosphorylation of Dfructose 6-phosphate, converting ATP into ADP in the process. It is regulated by binding of ATP to an allosteric site, quite distinct from the active site, that inhibits the enzyme. These regulatory clefts as well as being able to bind regulatory molecules, also require the ability to transmit binding information from themselves to the active site, so that catalytic activity can be regulated.

How Do Enzymes Work?

For any reaction to occur in the universe, there is an energy requirement. In cases where there is no activation energy provided, a catalyst plays an important role to reduce the activation energy and carried forward the reaction. This works in animals and plants as well. Enzymes help reduce the activation energy of the complex molecules in the reaction. The following steps simplify how an enzyme works to speed up a reaction:

Step 1: Each enzyme has an ‘active site’ which is where one of the substrate molecules can bind to. Thus, an enzyme- substrate complex is formed.

Step 2: This enzyme-substrate molecule now reacts with the second substrate to form the product and the enzyme is liberated as the second product.

There are many theories that explain how enzymes work. But, there are two important theories that we will discuss here.

Theory 1: Lock and Key Hypothesis

This is the most accepted of the theories of enzyme action.

This theory states that the substrate fits exactly into the active site of the enzyme to form an enzyme-substrate complex. This model also describes why enzymes are so specific in their action because they are specific to the substrate molecules.

Theory 2: Induced Fit Hypothesis

This is similar to the lock and key hypothesis. It says that the shape of the enzyme molecule changes as it gets closer to the substrate molecule in such a way that the substrate molecule fits exactly into the active site of the enzyme.

Structure of Archaeal and Eukaryal RPRs

Although no high-resolution structures are available for archaeal and eukaryal RPRs, identification of at least 50 sequences from each domain has permitted phlylogenetic sequence analysis that in turn has allowed refinement of secondary structure models (Harris et al. 2001 Li and Altman 2004a Marquez et al. 2005). Despite the marked reduction in size of the archaeal and eukaryal RPRs (at least 10&ndash20% smaller than typical bacterial RPRs), at least 13 nucleotides are universally conserved in identity and possibly in spatial location. In terms of differences, the archaeal and eukaryal RPRs are clearly missing some sequence/structure elements present in bacterial RPR that are either important for tertiary contacts or for direct interactions with the substrate (Fig. 1). For instance, the tertiary contacts in the smaller layer 2 of bacterial RPR (between P8 and L14/L18) are not possible in either archaeal or eukaryal RPR because they lack these elements and compensatory structural motifs are not evident. The L15 loop that base-pairs with the CCA sequence at the 3&prime end of ptRNAs is also absent in all eukaryal and some archaeal RPRs.

Expanded acyl-coenzyme specificity of GCN5

Recent advances in proteomics have revealed that lysine residues on histones and non-histone proteins can undergo other forms of acylation, including propionylation, butyrylation, succinylation, glutarylation, malonylation, crotonylation, and β-hydroxybutyrylation [57,[70], [71], [72]]. Current data suggests that the addition of these posttranslational modifications are catalyzed by HATs and are subject to metabolic regulation based on the cellular acyl-CoA levels.

Initial Velocity Measurement of a Chemical Reaction (With Diagram)

To measure the velocity of a reaction, it is necessary to follow a signal that reports product forma­tion or substrate depletion over time.

The type of signal that is followed varies from assay to assay but usually relies on some unique physicochemical property of the substrate or product, and/or the analyst’s ability to separate the substrate from the product.

Generally, most enzyme assays rely on one or more of the following broad classes of detection and separation methods to follow the course of the reaction:

Chromatographic separation and

Direct Assay:

These methods can be used in direct assay, the direct measurement of the substrate or product concentration as a function of time. For example, the enzyme cytochrome c oxidase catalyzes the oxidation of the heme-containing protein cytochrome c. In its reduced (ferrous iron) form, cyto­chrome c displays a strong absorption band at 550 nm, which is significantly diminished in intensity when the heme iron is oxidized (ferric form) by the oxidase.

One can thus measure the change in light absorption at 550 nm for a solution of ferrous cytochrome c as a function of time after addition of cytochrome c oxidase the diminution of absorption at 550 nm that is observed is a direct measure of the loss of substrate (ferrous cytochrome c) concentration (Fig. 7.1).

In some cases the substrate and product of an enzymatic reaction do not provide a distinct signal for convenient measurement of their concentrations. Often, however, product generation can be coupled to another, non-enzymatic, reaction that does produce a convenient signal such a strategy is referred to as an indirect assay.

Indirect Assays:

Dihydroorotate dehydrogenase (DHODase) provides an example of the use of indirect assays. This enzyme catalyzes the conversion of dihydroorotate to orotic acid in the presence of the exogenous cofactor ubiquinone. During enzyme turnover, elec­trons generated by the conversion of dihydroorotate to orotic acid are transferred by die enzyme to a ubiquinone cofactor to form ubiquinol.

It is difficult to measure this reaction directly, but the reduction of ubiquinone can be coupled to other non-enzymatic redox reactions. Several redox-active dyes are known to change colour upon oxidation or reduction. Among these, 2, 6- dichlorophenolindophenol (DCIP) is a convenient dye with which to follow the DHODase reac­tion. In its oxidized form DCIPs bright blue, absorbing light strongly at 610 nm.

Upon reduction, however, this absorption band is completely lost. DCIP is reduced stoichiometrically by ubiquinol, which is formed during DHODase turnover. Hence, it is possible to measure enzymatic turnover by having an excess of DCIP present in a solution of substrate (dihydroorotate) and cofactor (ubiquinone), then following the loss of 610 nm absorption with time after addition of enzyme to initiate the reaction.

A third way of following the course of an enzyme-catalyzed reaction is referred to as the coupled assays method. Here the enzymatic reaction of interest is paired with a second enzymatic reaction, which can be conveniently measured. In a typical coupled assay, the product of the enzyme reaction of interest is the substrate for the enzyme reaction to which it is coupled for convenient measure­ment.

An example of this strategy is the measurement of activity for hexokinase, the enzyme that catalyzes the formation of glucose 6-phosphate and ADP from glucose and ATP. None of these products or substrates provides a particularly convenient means of measuring enzymatic activity.

However, the product glucose 6-phosphate is the substrate for the enzyme glucose 6-phosphate dehydrogenase, which, in the presence of NADP, converts this molecule to 6-phosphogluconolactone. In the course of the second enzymatic reaction, NADP is reduced to NADPH, and this cofactor reduction can be monitored easily by light absorption at 340 nm.

This example can be generalized to the following scheme:

where A is the substrate for the reaction of interest, v1 is the velocity for this reaction, B is the product of the reaction of interest and also the substrate for the coupling reaction, v2 is the velocity for the coupling reaction, and C is the product of the coupling reaction being measured. Although we are measuring C in this scheme, it is the steady state velocity v1 that we wish to study.

To accomplish this we must achieve a situation in which v1 is rate limiting (i.e., v1 ˃˃ v2) and B has reached a steady state concentration. Under these conditions B is converted to C almost instantaneously, and the rate of C production is a reflection of v1. The measured rate will be less than the steady state rate v1, however, until [B] builds up to its steady state level.

Hence, in any coupled assay there will be a lag phase prior to steady state production of C (Fig. 7.2), which can interfere with the measurement of the initial velocity. Thus to measure the true initial velocity of the reaction of interest, conditions must be sought to minimize the lag phase that precedes steady state product formation, and care must be taken to ensure that the velocity is measured during the steady state phase.

The velocity of the coupled reac­tion, v2, follows simple Michaelis-Menten kinetics as follows:

where K 2 m refers to the Michaelis con­stant for enzyme E2, not the square of the Km. Early in the reaction, v1 is con­stant for a fixed concentration of E1. Hence, the rate of B formation is given by:

This equation was evaluated by integration by Storer and Cornish-Bowden (1974), who showed that the time required for [B] to reach some percentage of its steady state level [B]ss can be defined by the following equation:

where t99% is the time required for [B] to reach 99% [B]ss and Ф is a dimensionless value that depends on the ratio v1/V2 and v2/v1. It is known that maximal velocity V2 is the product of kcat for the coupling enzyme and the concentration of coupling enzyme [E2]. The values of kcat and Km for the coupling enzyme are constants that cannot be experimentally adjusted without changes in reaction conditions.

The maximal velocity V2, however, can be controlled by the researcher by adjusting the concentration [E2]. Thus by varying [E2] one can adjust V2, hence the ratio v1/V2, and also the lag time for the coupled reaction.

Let us say that we can measure the true steady state velocity v1 after [B] has reached 99% of [B]ss. How much time is required to achieve this level of [B]ss? We can calculate this if we know the values of v1 and Ф. Storer and Cornish-Bowden tabulated the ratios v1/V2 that yield different values of Ф for reaching different percentages of [B]ss. Table 7.1 lists the values for [B]=99% [B]ss.

This percentage is usually considered to be optimal for measuring v1 in a coupled assay. In certain cases this requirement can be relaxed. For example, [B] = 90% [B]ss would be adequate for use of a coupled assay to screen column fractions for the presence of the enzyme of interest.

In this situation we are not attempting to define kinetic parameters, but merely wish a relative measure of primary enzyme concentration among different samples. The reader should consult the original paper by Storer and Cornish-Bowden (1974) for additional tables of Ф for different percentages of [B]ss.

Easterby (1973) and Cleland (1979) have presented a slightly different method for determining the duration of the lag phase for a coupled reaction. From their treatments we find that as long as the coupling enzyme(s) operate under first-order conditions (i.e., [B]ss << K 2 m), we can write:

where τ is the lag time. The time required for [B] to approach [B]ss is exponentially related to τ so that [B] is 92% [B]ss at 2.5τ, 95% [B]ss at 3τ, and 99% [B]ss at 4.6τ (Easterby, 1973). Product (C) formation as a function of time (t) is dependent on the initial velocity and the lag time (τ) as follows:

If more than one enzyme is used in the coupling steps, the overall lag time can be calculated as ∑(K i m/Vi). For example, if one uses two consecutive coupling enzymes, A and B to follow the reaction of the primary enzyme of interest, the overall lag time would be given by:

Because coupled reactions entail multiple enzymes, these assays present a number of potential problems that are not encountered with direct or indirect assays. For example, to obtain meaningful data on the enzyme of interest in coupled assays, it is imperative that the reaction of interest remains rate limiting under all reaction conditions.

Otherwise, any velocity changes that accompany changes in reaction conditions may not accurately reflect effects on the target enzyme. For example, to use a coupled reaction scheme to determine kcat and Km for the primary enzyme of interest, it is necessary to ensure that v1 is still rate lim­iting at the highest values of [A] (i.e., substrate for the primary enzyme of interest).

Coupled Assay:

Use of a coupled assay to study inhibition of the primary enzyme might also seem problematic. The presence of multiple enzymes could introduce ambiguities in interpret­ing the results of such experiments: for example, which enzyme(s) are really being inhibited? Easterby (1973) points out, however, that using coupled assays to screen for inhibitors makes it relatively easy to distinguish between inhibitors of the primary enzyme and the cou­pling enzyme(s).

Inhibitors of the primary enzyme would have the ef­fect of diminishing the steady state velocity v1 (Fig. 7.3A), while inhibi­tors of the coupling enzyme(s) would extend the lag phase with­out affecting v1 (Fig. 7.3B). In prac­tice these distinctions are clear-cut only when one measures product formation over a range of time points covering significant portions of both the lag phase and the steady state phase of the progress curves (Fig. 7.3). Rudolph et al. (1979), Cleland (1979), and Tipton (1992) provide more detailed dis­cussions of coupled enzyme assays.


The simplest way to describe the influence of the relative diffusion of the reactants on the time course of bimolecular reactions is to modify or renormalize the phenomenological rate constants that enter into the rate equations of conventional chemical kinetics. However, for macromolecules with multiple inequivalent reactive sites, this is no longer sufficient, even in the low concentration limit. The physical reason is that an enzyme (or a ligand) that has just modified (or dissociated from) one site can bind to a neighboring site rather than diffuse away. This process is not described by the conventional chemical kinetics, which is only valid in the limit that diffusion is fast compared with reaction. Using an exactly solvable many-particle reaction-diffusion model, we show that the influence of diffusion on the kinetics of multisite binding and catalysis can be accounted for by not only scaling the rates, but also by introducing new connections into the kinetic scheme. The rate constants that describe these new transitions or reaction channels turn out to have a transparent physical interpretation: The chemical rates are scaled by the appropriate probabilities that a pair of reactants, which are initially in contact, bind rather than diffuse apart. The theory is illustrated by application to phosphorylation of a multisite substrate.

For bimolecular reactions in solution, the formalism of chemical kinetics is valid only in the limit that the reactants come together many times before reacting. This means that the intrinsic reaction rate must be slower than the rate at which the partners diffuse together. Starting with the seminal work of Smoluchowski (1), it has been shown that the relative diffusion of the reactants, even in a macroscopically homogeneous solution, can lead to deviations from the predictions of conventional chemical kinetics. For example, for reversible reactions, the concentrations decay to their equilibrium values not exponentially, but rather as a power law (2, 3). However, for biochemically relevant concentrations, such effects are small. Even in the crowded environment of a cell, although the total concentration of all macromolecules is of course high, the concentrations of specific molecules that can react with each other are typically low. Although it is interesting and challenging to develop a theory of reversible diffusion-influenced reactions that is accurate at all times and concentrations, in many cases the concentrations are so low that all one has to do is to replace the phenomenological rate constants by their diffusion-influenced values.

In this paper we consider a class of reactions involving macromolecules with multiple sites where, even at low concentrations, it is not enough to replace the rate constants with diffusion-influenced ones. Our interest in such problems was stimulated by the important work of Takahashi et al. (4) on the role of diffusion in a dual phosphorylation–dephosphorylation cycle that can exhibit ultrasensitive (5) and bistable behavior (6). Based on many-particle stochastic simulations, it was shown that slowing down diffusion can speed up response and lead to the loss of ultrasensitivity and bistability (4). These results were attributed to “spatio-temporal correlations between the enzyme and the substrate molecules.” The physical idea is illustrated in Fig. 1 for dual phosphorylation. For the sake of simplicity, we have assumed that the binding and catalytic sites are the same and adopted a reference frame where the substrate is fixed. After modifying the first site, the enzyme dissociates and (i) diffuses away and another enzyme binds and modifies the second site (lower pathway) or (ii) binds to the second site and modifies it (upper pathway). In other words, in the upper pathway both sites are phosphorylated by the same enzyme molecule, whereas in the lower pathway the sites are phosphorylated by different molecules. In the fast diffusion limit, only the lower pathway is in play. In the phosphorylation field, the mechanism is called distributive when the enzyme and substrate dissociate after each modification, whereas in a processive mechanism all sites are phosphorylated before dissociation (7, 8). Thus, when the rate of diffusion is finite, the mechanism inevitably contains both distributive and processive features (4, 9, 10).

A substrate S with two sites (yellow) that can be modified (red) by an enzyme E at concentration [E]. Lower pathway: After modifying one site, the enzyme diffuses away and another enzyme binds and phosphorylates the unmodified site. Upper pathway: The enzyme that has just modified one site dissociates, binds to the unmodified site, and then phosphorylates it.

The goal of this paper is to develop a simple theory that can quantitatively describe such phenomena for physically relevant concentration ranges without having to resort to many-particle computer simulations. In a nutshell, not only does one need to replace the existing phenomenological rate constants by their diffusion-influenced counterparts, but also one has to introduce new transitions into the kinetic scheme. The rates of these new reaction channels are determined by the probability that a reactant released from one site binds to another rather than diffusing away. Even for complex geometries, such capture and escape probabilities can be found by numerically solving or simulating only a time-independent, two-particle problem.

The outline of the paper is as follows. We start with arguably the simplest model of multisite modification that can be solved exactly on the many-particle level. In this model, the lifetime of the enzyme–substrate complex is assumed to be so short that a site can be modified when the enzyme simply comes in contact with the substrate. When the enzyme concentration is sufficiently low, it is found that the exact time dependence of the concentrations is well described by ordinary rate equations corresponding to the standard kinetic scheme with the crucial difference that new transitions have been allowed. The corresponding rate constants turn out to have such a simple physical interpretation that the formalism can be readily generalized to treat more realistic cases (e.g., intermediate bound complexes, enzyme reactivation, and binding to inequivalent sites). The rate constants in the modified kinetic schemes can be expressed in terms of the capture and escape probabilities of an isolated pair of reactants. In simple cases, these can be found by solving a time-independent equation subject to the appropriate boundary conditions and, for realistic geometries, by simulating the dynamics of an isolated pair of reactants. Illustrative calculations for dual phosphorylation show that our formalism reproduces the speeding up of the response discovered using stochastic many-particle simulations (4).


Science is difficult, but the satisfaction of reaching some new understanding of the extraordinary chemical and physical processes that are responsible for the functioning of a living organism, whether it be an amoeba or an Einstein, is a more than adequate incentive to pursue this understanding, which has undergone an extraordinary increase during my lifetime. The progress that has been made in increasing this understanding has gone far beyond what was thought possible in the 1960s, as is apparent from the reviews that are published in this volume.

Watch the video: How Mendels pea plants helped us understand genetics - Hortensia Jiménez Díaz (January 2023).