**5. Enzyme models utilized for the design of potential bitterless prodrugs for bitter drugs such as atenolol, amoxicillin, cephalexin, paracetamol and guaiphenesin**

Scholar studies of enzyme mechanisms by several chemists and biochemists, over the past five decades, have had a significant contribution for understanding the mode and scope of enzymes catalysis.

Nowadays, the scientific community has reached to the conclusion that enzyme catalysis is based on the combined effects of the catalysis by functional groups and the ability to reroute intermolecular reactions through alternative pathways by which substrates can bind to preorganized active sites. It is believed that rate accelerations by enzymes can be proceed by (i) covalently enforced proximity, as seen in the case of chymotrypsin, [57] (ii) non-covalently enforced proximity, as represented in the catalysis of metallo-enzymes, [58] (iii) covalently enforced strain, [59], and (iv) non-covalently enforced strain, which has been extensively studied on models mimicking the lysozyme enzyme which is most closely associated with rate acceleration due to this kind of strain [60].

Rates for the majority of enzymatic reactions ranges between 1010 and 1018 fold their nonenzymatic bimolecular counterparts. For instance, biochemical reactions involving the catalysis of the enzyme cyclophilin are enhanced by105 and those by the enzyme oroti‐ dine monophosphate decarboxylase are accelerated by 1017 [61]. The significant enhance‐ ment in rate manifested by enzymes is a result of the substrate binding within the confines of the enzyme active site. The substrate-enzyme binding energy is the dominant driving force and the major contributor to catalysis. A consensus has been reached that in all enzymatic processes binding energy is used to overcome physical and thermodynamic factors that make barriers to the reaction (free energy). These factors are: (1) the change in entropy (ΔS˚), in the form of the freedom of motions of the reactants in solution; (2) the hydrogen bonding net around bio-molecules in aqueous solution; (3) a proper alignment of catalytic functional groups on the enzyme; and (4) the distortion of a substrate that must occur before the reaction takes place [62,63].

Scholarly studies have been done by Bruice, Cohen, Menger, Kirby and others to design enzyme models having the potential to reach rates comparable to rates of biochemical reactions catalyzed by enzymes. Examples for such models are those based on rate enhancements driven by covalently enforced proximity. The most cited example is the intramolecular cyclization of dicarboxylic semi esters to anhydrides advocated by Bruice *et al.*[64,65]. Bruice et al. has demonstrated that a relative rate of anhydride formation can reach 5 x 107 upon cyclization of a dicarboxylic semi ester when compared to a similar counterpart's bimolecular process.

Other examples of rate acceleration based on proximity orientation include: (a) acid-catalyzed lactonization of hydroxy-acids as studied by Cohen et al.[66-68] and Menger [63, 69-75], (b) intramolecular SN2-based cyclization reactions as researched by Brown et al. [76] and Mando‐ lini's group [77], (c) proton transfer between two oxygens in Kirby's acetals [78-84], and proton transfer between nitrogen and oxygen in Kirby's enzyme models [78-84], (d) proton transfer

function of the major enzymes activating prodrugs, and these can pose some obstacles in the

**Paracetamol (30) Cephalexin (31)**

preclinical optimization phase.

**Figure 4.** Chemical structures for 24-33.

**O**

**<sup>O</sup> H3C**

**Phenacetin (32)**

**N**

**Cl**

**HO**

**HN**

410 Application of Nanotechnology in Drug Delivery

**Chloroquine (24)**

**O**

**HO**

**H3C**

**O**

**HO**

**S**

**OH**

**HN O**

**Clindamycin (26)**

**<sup>H</sup> <sup>H</sup> <sup>N</sup>**

**O**

**OH**

**N**

**S**

**O OH**

**O NH2 O**

**N**

**H N**

**O**

**H N**

**O**

**O**

**Cefuroxime (28)**

**N O** **N**

**N O**

**HO**

**HN Cl**

**O**

**O**

**OH**

**Chloramphenicol (25)**

**HO**

**H**

**O**

**H**

**Triamcinolone (27)**

**Atenolol (29)**

**F**

**Cl**

**OH**

**H N**

**S**

**O OH**

**N**

**<sup>H</sup> <sup>H</sup> <sup>N</sup>**

**O**

**H N**

**Acetanilide (33)**

**O**

**O**

**NH2**

**OH**

**O**

**O**

**H2N**

**O**

between two oxygens in rigid systems as investigated by Menger [63, 69-75],and (e) proton transfer from oxygen to carbon in some of Kirby's enol ethers [78-84]. The conclusions emerged from these studies are (1) the driving force for enhancements in rate for intramolecular processes are both entropy and enthalpy effects. In the cases by which enthalpy effects were predominant such as ring-closing and proton transfer reactions proximity or/and steric effects were the driving force for rate accelerations. (2) The nature of the reaction being intermolecular or intramolecular is determined on the distance between the two reacting centers. (3) In SN2 based ring-closing reactions leading to three-, four-and five-member rings the *gem*-dialkyl effect is more dominant in processes involving the formation of an unstrained five-member ring, and the need for directional flexibility decreases as the size of the ring being formed increases. (4) Accelerations in the rate for intramolecular reactions are a result of both entropy and enthalpy factors. (5) An efficient proton transfer between two oxygens and between nitrogen and oxygen in Kirby's acetal systems were affordable when a strong hydrogen bonding was developed in the products and the transition states leading to them [85-103].

a number of approximations. Ab initio electronic structure methods have the advantage that they can be made to converge to the exact solution, when all approximations are sufficiently small in magnitude and when the finite set of basis functions tends toward the limit of a complete set. The convergence is usually not monotonic, and sometimes the smallest calcula‐ tion gives the best result for some properties. The disadvantage of ab initio methods is their enormous computational cost. They take a significant amount of computer time, memory, and disk space [109-112]. On the other hand, empirical or semi-empirical methods are less accurate because they employ experimental results, often from acceptable models of atoms or related molecules, to approximate some elements of the underlying theory. Example for such methods is the semi-empirical quantum chemistry methods based on the Hartree–Fock formalism, but make many approximations and obtain some parameters from empirical data. These methods are especially important for calculating large molecules where the full Hartree–Fock method without the approximations is too expensive. Semi-empirical calculations are much faster than their ab initio counterparts. Their results, however, can be imprecise if the molecule being computed is not similar enough to the molecules in the database used to parameterize the method. Among the commonly used semiempirical methods are MINDO, MNDO, MINDO/3, AM1, PM3 and SAM1. Calculations of molecules exceeding 60 atoms can be

Prodrugs for Masking the Bitter Taste of Drugs

http://dx.doi.org/10.5772/58404

413

Another widely used quantum mechanical method is the density functional theory (DFT). With this theory, the properties of many-electron systems can be determined by using functionals, i.e. functions of another function, which in this case is the spatially dependent electron density. Therefore, the name density functional theory comes from the use of functionals of the electron density. DFT is among the most popular and versatile methods available in condensed-matter physics, computational physics, and computational chemistry. The DFT method is adequate for calculating structures and energies for medium-sized systems (30-60 atoms) of biological, pharmaceutical and medicinal interest and is not restricted to the

Although the use of DFT method is significantly increasing some difficulties still encountered when describing intermolecular interactions, especially van der Waals forces (dispersion); charge transfer excitations; transition states, global potential energy surfaces and some other strongly correlated systems. Incomplete treatment of dispersion can adversely affect the DFT

On the other hand, molecular mechanics is a mathematical approach used for the computation of structures, energy, dipole moment, and other physical properties. It is widely used in calculating many diverse biological and chemical systems such as proteins, large crystal structures, and relatively large solvated systems. However, this method is limited by the determination of parameters such as the large number of unique torsion angles present in

Molecular mechanics simulations, for example, use a single classical expression for the energy of a compound, for instance the harmonic oscillator. The database of compounds used for parameterization, i.e., the resulting set of parameters and functions is called the force field, is crucial to the success of molecular mechanics calculations. A force field parameterized against

degree of accuracy in the treatment of systems which are dominated by dispersion.

handled using semiempirical methods [113-116].

second row of the periodic table [43].

structurally diverse molecules [117].

In the past few years some prodrugs based on the trimethyl lock system have been reported. Borchardt et al. has shown that the pro–prodrug 3-(2'-acetoxy-4', 6'-dimethyl dimethyl) phenyl-3, 3-dimethylpropionamide is capable of releasing the biologically active amine drug upon acetate hydrolysis by enzyme triggering. Another successful example exploiting a stereopopulation control model is the prodrug Taxol which enhances the drug water solubility and hence affords it to be administered to the human body *via* intravenous injection. Taxol is the brand name for paclitaxel, a natural diterpene, approved in the USA for use to treat cancer [104-108].
