**3. State of the art**

Xenobiotics are usually lipophilic and this facilitates their transport in association with lipoproteins in the blood stream and their penetration of lipid membranes and entrance into organs. However, physicochemical properties of drug molecules difficult their removal from the organism by biliary or renal excretion and therefore, these substances require enzymatic conversion to water soluble compounds [1]. The xenobiotics metabolization, often through multiple pathways, can generate metabolites that are more toxic than the substrate and through their interaction with target macromolecules such as DNA, RNA, proteins and receptors, generate the toxic effects. The organ affected is generally that reponsible for drug metaboli‐

The enzyme systems responsible for the biotransformation of many drugs are located in the endoplasmic reticulum of the liver (microsomal fraction). Such enzymes are also present in the kidneys, lungs and gastrointestinal epithelium, although at a lower concentration [1]. The metabolic modification in biotransformation usually takes place in two consecutive steps and results in the loss of biological activity. Phase I reactions convert the xenobiotic into a metab‐ olite with higher polarity by oxidation, reduction or hydrolysis and generates a pharmaco‐ logically inactive or less active, or in the case of a pro-drug, more active molecule. This metabolite is than either eliminated or go through Phase II reactions (so-called synthesis or conjugation reactions), involving binding to a primary metabolite or endogenous substrate such as glucuronate, sulfate, acetate, amino acids or glutathione (tripeptide). Such enzymatic reactions include glucuronidation, methylation, sulfation, acetylation, conjugation with

The risk for developing hepatotoxicity is associated both with genetic and acquired factors. The acquired factors include: age, gender, nutritional habits, drug abuse, pregnancy and extrahepatic disease. Genetic variations in isoenzymes involved in drug biotransformation can result in abnormal reactions leading to toxic effects [14,17]. In the case of INH in particular, advanced age is a risk factor for hepatotoxicity whereas deficiency in the ability of N-acetyla‐

INH is administered orally and rapidly absorbed through the gastrointestinal tract passing through the liver by the portal venous system before reaching the general circulation where is metabolized by a process known as the first pass effect with reduction of its biodiponibility. About 75% to 95% of the INH is excreted by the kidneys during the first 24 hours, mainly as

In the liver, INH is metabolized to acetylisoniazid by N-acetyltransferase 2 (NAT2), followed by hydrolysis to acetylhydrazine and then oxidized by cytochrome P4502E1 (CYP2E1) to hepatotoxic intermediates [18, 19]. These metabolites can destroy hepatocytes either by interfering with cell homeostasis or by triggering immunologic reactions in which reactive metabolites that are bound to hepatocyte plasma proteins may act as haptens [17]. The other metabolic pathway to generate toxic metabolites is direct hydrolysis of INH to hydrazine, a potent hepatotoxin. NAT2 is also responsible for converting acetylhydrazine to diacetylhy‐ drazine, a nontoxic component [18, 20, 21] (Figure 1). Glutathione S-transferase (GST), an important phase II detoxification enzyme, is thought to play a protective role as an intracellular free radical scavenger, which conjugates glutathione with toxic metabolites that are generated

zation or excretion of metabolites [1].

108 Tuberculosis - Current Issues in Diagnosis and Management

glutathione and conjugation with glycine [1].

tion represent a genetic risk factor for liver injury.

the metabolic forms acetyl-isoniazid and isonicotinic acid [1].

#### **3.1. N-acetyltransferase 2**

NAT2, the main enzyme responsible for the metabolism and inactivation of INH in humans, is a Phase II enzyme that catalyzes the transfer of the acetyl group from the cofactor acetyl coenzyme A (acetyl-CoA) to the nitrogen terminal of the drug. Variations in activity of NAT2 were discovered over 50 years ago when observing interindividual differences in the metab‐ olism of INH and the level of drug-induced toxicity in TB patients. NAT2 is encoded by the *NAT2* gene and according family genetic studies, variability of *NAT2* was directly related to the emergence of different phenotypes of acetylation [25].

The molecular study of human N-acetyltransferases revealed the presence of three genetic loci, two very homologous encoding the enzymes NAT1 and NAT2, and a third including the pseudogene *pNAT* (Figure 2). These loci are located on chromosome 8 between 170-360Kb at 8p22 [26]. The *pNAT* is a pseudogene containing a premature stop codon, and is not transcri‐ bed. *NAT1* and *NAT2* genes consist of 873 bp, are intronless, and encode proteins of 34 kDa. Protein sequence homology between both enzymes is 81% while that between their respective genes is 87%. Both enzymes have N-acetylation, O-acetylation and NO-transfer in different xenobiotics and carcinogens but differ considerably in their tissue distribution and expression levels during embryonic development [26-28].

Presence of different SNPs in *NAT2* can be easily determined by genotyping procedures such as PCR-RFLP [37], allele specific PCR [38] or direct sequencing [39]. To achieve the *NAT2* genotype of each individual and predict the phenotype, the haplotype of both chromosomes is usually reconstructed using the statistic software (PHASEv2.1.1[40, 41]). Using haplotype data, many studies have reported the frequencies of the different acetylation profiles among ethnically different populations showing the high diversity around the world. In Asians and Ameridians, the fast acetylator phenotype is more frequent [42-44] whereas in Euro-descend‐ ants slow acetylators account for 50% of the study population [37,45]. The molecular basis for such discrepancy is that the most common *NAT2* allele in Euro-descendants is very rare in Asians and may represent a different selective advantage within the gene pools of these separate populations. Description of new alleles of *NAT2* is still ocurring in recent studies [34]. In an attempt to establish an association between acetylation profiles and development of disease, cohort or case-control studies have been performed using of genotyping and pheno‐ typing tools. Evidence was found for an association between the slow acetylator predicted phenotype and developing urinary bladder cancer, while rapid acetylators seem more

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For many years, INH has been considered the main cause of hepatotoxicity during TB treatment and association studies between the acetylation phenotypes and susceptibility to liver-related ADRs have been performed. Two early studies conducted in oriental populations investigated the association of the acetylator phenotype with INH induced hepatotoxicity and observed an increased risk of developing hepatotoxicity by INH among the slow acetilators [47, 48]. This observation was confirmed in several other studies performed in different

Several studies reported the absence of a relationship between acetylation status and hepato‐ toxicity during TB treatment [53-55] but some, suggested the rapid acetylators as more susceptible to side effects [55, 56]. Reasons for these different findings range from genotyping methods to ethnicity. In some studies, NAT2 acetylation phenotypes were determined by an enzymatic method leading to possible misclassification of the acetylation status [53, 56, 57]. Indeed, it is difficult to compare the accuracy of different NAT phenotyping methods or different cut-off points using the same phenotyping method. In addition, for genotyping, investigators sometimes select a small number of SNPs to define the acetylation status [54, 55]. Since the frequencies of *NAT2* alleles are different among worldwide populations and new alleles are been identified in some countries, investigators need to characterize such alleles in their own study population in order to choose appropriate SNPs for genotyping and classify the acetylation status of individuals, otherwise overestimation of slow acetylators may be

Recently, a study with an admixed population showed that *NAT2* is a genetic factor for predisposition to anti-TB drug-induced hepatitis. In this case, *NAT2* genes were well charac‐ terized by direct sequencing and their genotypes achieved by haplotype reconstruction using the PHASE software. In addition, functional unknown genotypes were disconsidered and others confounding variables for hepatotocixity were taken into account. The incidence of elevated levels of serum transaminases was significantly higher in slow acetylators than those

susceptible to development of colon cancer. For a review, see [27, 46].

obtained, contributing to a spurious results in the association study.

populations [49-52].

Both *NAT1* and *NAT2* are polymorphic genes and SNPs in their coding region can alter the enzymatic activity [29, 30] and are the basis of the three major genetically determined pheno‐ types, being rapid, intermediate and slow acetylators, which are inherited as a codominant trait [31, 32]. The reference *NAT2\*4* allele (without mutations / wild-type) and 66 variants were identified and classified in human populations depending on the combination of up to four SNPs present throughout the *NAT2* coding region [33]. So far, over 30 SNPs have been identified in this region, including several rare mutations described in different populations [34]. Among these, the seven most frequent are the 191 G>A (R64Q), 282 C>T (silent), 341 T>C (I114T), 481 C>T (silent), 590 G>A (R197Q), 803 A>G (K268R) and 857 G>A (G286T) SNPs identified in different human populations [35]. *NAT2* alleles containing the 191G>A, 341T>C, 590G>A or 857G>A SNPs are associated with slow acetylator *NAT2* alleles [33].

**Figure 2.** Schematic representation of *NAT* genes on human chromosome 8p22. Distribution of the seven most com‐ mon SNPs in *NAT2*. D8S21 represents a polymorphic marker situated in the *NAT2* locus [26, 36].

Presence of different SNPs in *NAT2* can be easily determined by genotyping procedures such as PCR-RFLP [37], allele specific PCR [38] or direct sequencing [39]. To achieve the *NAT2* genotype of each individual and predict the phenotype, the haplotype of both chromosomes is usually reconstructed using the statistic software (PHASEv2.1.1[40, 41]). Using haplotype data, many studies have reported the frequencies of the different acetylation profiles among ethnically different populations showing the high diversity around the world. In Asians and Ameridians, the fast acetylator phenotype is more frequent [42-44] whereas in Euro-descend‐ ants slow acetylators account for 50% of the study population [37,45]. The molecular basis for such discrepancy is that the most common *NAT2* allele in Euro-descendants is very rare in Asians and may represent a different selective advantage within the gene pools of these separate populations. Description of new alleles of *NAT2* is still ocurring in recent studies [34].

pseudogene *pNAT* (Figure 2). These loci are located on chromosome 8 between 170-360Kb at 8p22 [26]. The *pNAT* is a pseudogene containing a premature stop codon, and is not transcri‐ bed. *NAT1* and *NAT2* genes consist of 873 bp, are intronless, and encode proteins of 34 kDa. Protein sequence homology between both enzymes is 81% while that between their respective genes is 87%. Both enzymes have N-acetylation, O-acetylation and NO-transfer in different xenobiotics and carcinogens but differ considerably in their tissue distribution and expression

Both *NAT1* and *NAT2* are polymorphic genes and SNPs in their coding region can alter the enzymatic activity [29, 30] and are the basis of the three major genetically determined pheno‐ types, being rapid, intermediate and slow acetylators, which are inherited as a codominant trait [31, 32]. The reference *NAT2\*4* allele (without mutations / wild-type) and 66 variants were identified and classified in human populations depending on the combination of up to four SNPs present throughout the *NAT2* coding region [33]. So far, over 30 SNPs have been identified in this region, including several rare mutations described in different populations [34]. Among these, the seven most frequent are the 191 G>A (R64Q), 282 C>T (silent), 341 T>C (I114T), 481 C>T (silent), 590 G>A (R197Q), 803 A>G (K268R) and 857 G>A (G286T) SNPs identified in different human populations [35]. *NAT2* alleles containing the 191G>A, 341T>C,

**Figure 2.** Schematic representation of *NAT* genes on human chromosome 8p22. Distribution of the seven most com‐

mon SNPs in *NAT2*. D8S21 represents a polymorphic marker situated in the *NAT2* locus [26, 36].

590G>A or 857G>A SNPs are associated with slow acetylator *NAT2* alleles [33].

levels during embryonic development [26-28].

110 Tuberculosis - Current Issues in Diagnosis and Management

In an attempt to establish an association between acetylation profiles and development of disease, cohort or case-control studies have been performed using of genotyping and pheno‐ typing tools. Evidence was found for an association between the slow acetylator predicted phenotype and developing urinary bladder cancer, while rapid acetylators seem more susceptible to development of colon cancer. For a review, see [27, 46].

For many years, INH has been considered the main cause of hepatotoxicity during TB treatment and association studies between the acetylation phenotypes and susceptibility to liver-related ADRs have been performed. Two early studies conducted in oriental populations investigated the association of the acetylator phenotype with INH induced hepatotoxicity and observed an increased risk of developing hepatotoxicity by INH among the slow acetilators [47, 48]. This observation was confirmed in several other studies performed in different populations [49-52].

Several studies reported the absence of a relationship between acetylation status and hepato‐ toxicity during TB treatment [53-55] but some, suggested the rapid acetylators as more susceptible to side effects [55, 56]. Reasons for these different findings range from genotyping methods to ethnicity. In some studies, NAT2 acetylation phenotypes were determined by an enzymatic method leading to possible misclassification of the acetylation status [53, 56, 57]. Indeed, it is difficult to compare the accuracy of different NAT phenotyping methods or different cut-off points using the same phenotyping method. In addition, for genotyping, investigators sometimes select a small number of SNPs to define the acetylation status [54, 55]. Since the frequencies of *NAT2* alleles are different among worldwide populations and new alleles are been identified in some countries, investigators need to characterize such alleles in their own study population in order to choose appropriate SNPs for genotyping and classify the acetylation status of individuals, otherwise overestimation of slow acetylators may be obtained, contributing to a spurious results in the association study.

Recently, a study with an admixed population showed that *NAT2* is a genetic factor for predisposition to anti-TB drug-induced hepatitis. In this case, *NAT2* genes were well charac‐ terized by direct sequencing and their genotypes achieved by haplotype reconstruction using the PHASE software. In addition, functional unknown genotypes were disconsidered and others confounding variables for hepatotocixity were taken into account. The incidence of elevated levels of serum transaminases was significantly higher in slow acetylators than those of the rapid/intermediate type. These results corroborate with the current hypothesis that the acetylator status may be a risk factor for the hepatic side effects of isoniazid [58].

lead to generation of toxic metabolites that contribute to the increased risk of developing

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The complete sequencing of the human genome revealed the presence of about 115 genes of CYP450, including 57 active genes and 58 pseudogenes [67]. They belong to families 1-3 and are responsible for 70-80% of Phase I-dependent metabolism of clinically used drugs. Other families of CYPs are involved in metabolism of endogenous components [66]. The CYP2 constitutes the largest family of isoenzymes and comprises one third of all human CYPs. Genes encoding these enzymes are polymorphic and the frequency distribution of allelic variants in different ethnic groups differs. Overall, four phenotypes based on genotypes can be identified: (i) poor metabolizers who present low enzymatic activity, (ii) intermediate metabolizers, usually heterozygous for a defective allele, (iii) rapid metabolizers, who have two normal

The enzyme CYP2E1 is expressed mainly in the liver but can be found in other organs such as kidney, gastrointestinal tract and brain and involved in oxidation of substrates such as ethanol and the metabolism of many drugs and pre-carcinogens. Besides ethanol, CYP2E1 can be induced by various drugs such as INH but also by hydrocarbons, benzene, chloroform and

The activity of CYP2E1 is also modulated by polymorphisms in several locations of its gene and more activity of this enzyme may increase the synthesis of hepatotoxins. Two polymor‐ phisms upstream of the *CYP2E1* transcriptional start site are characterized by *Pst* I and *Rs*a I digestion and appear to be in complete linkage disequilibrium (Figure 3). These two poly‐ morphisms are located in a putative HNF-q binding site and thus may play a role in the regulation of *CYP2E1* transcription and subsequent protein expression [71]. Genotypes of *CYP2E1* are classified as being \*1A/\*1A, \*1A/\*5 or \*5/\*5 by *Rsa* I based restriction analysis. The polymorphism detectable by *Dra* I (7632 T>A) is located in intron 6 and characterizes the allelic variant *CYP2E1\*6*. The other polymorphism is an insertion/deletion of 96 bp (*CYP2E1\*1D* and *\*1C* alleles) that regulates the expression of the gene [72]. Some studies have shown that allelic variants *CYP2E1 \*5*, *\*6* and *\*1D* would increase enzyme activity [71, 73]. However, other authors did not confirm any relationship with these polymorphisms with CYP2E1 activity [74].

alleles and (iv) ultrarapid metabolizers, who have several gene copies [69].

**Figure 3.** Polymorphic and corresponding restriction enzyme cutting sites at *CYP2E1* [24].

cancers and other toxic effects [68].

various organic solvents [70].

Finally, a meta-analysis was conducted to solve the problem of inadequate statistical power and controversial results based on accumulated data with small sample size [59]. Data from 14 studies performed between 2000 and 2011 were pooled and showed that TB patients with a slow acetylator genotype had a higher risk of anti-tuberculosis drug induced hepatotocixity than patients with rapid or intermediate acetylation (*p* < 0.001). Moreover, subgroup analyses indicate that both Asians and non-Asians slow acetylators develop anti-tuberculosis drug induced hepatotocixity more frequently. Additionally, there were statistically significant associations between NAT2\*5/\*7, NAT2\*6/\*6, NAT2\*6/\*7 and NAT2\*7/\*7 and the risk of anti-TB drug induced hepatotocixity [59].

As a final consideration, NAT acetylates more slowly not only isoniazid but also acetylhydra‐ zine, the immediate precursor of toxic intermediates, to the harmless diacetylhydrazine [60, 61]. This protective acetylation is further suppressed by INH competition. Therefore, slow acetylators may be prone to higher accumulation rates of INH toxic metabolites. Another important route to generate toxic intermediates is the direct hydrolysis of unacetylated INH [62], producing hydrazine that also induces hepatic injury [62, 63]. Pharmacokinetic studies showed that the serum concentration of hydrazine was significantly higher in slow acetylators than in rapid acetylators, probably due to the high INH concentration. The high amount of INH disposed of through this pathway is likely to lead to enhanced hydrolysis to hydrazine, since the rate of metabolic conversion of INH to acetylisoniazid is lower in slow than in rapid acetylators [64, 65]. All of these drug-disposal processes may support the finding that slow acetylators are prone to INH-induced hepatitis. We therefore conclude that screening of patients for the *NAT2* genetic polymorphisms can prove clinically useful for the prediction and prevention of anti-tuberculosis drug induced hepatotoxicity.

#### **3.2. CYP450**

Cytochromes P450 (CYP450) are hemoproteins and form the most important enzymatic group for Phase I biotransformation. The main activity of isozymes of CYP450 system is oxidation and they are located in the smooth endoplasmic reticulum, mainly in liver cells. However, these mono-oxygenases are also localized in the intestine, pancreas, brain, lung, kidney, bone marrow, skin, ovary and testicles [66]. The CYP450 proteins are clustered into families and subfamilies according to the similarity between the amino acid sequences: where family members have ≥ 40% identity in amino acid sequence, members of the same subfamily share ≥ 55% identity [67].

The CYP450s are responsible for the metabolization of several endogenous substrates and the synthesis of hydrophobic lipids such as cholesterol, steroid hormones, bile acids and fatty acids. Moreover, some enzymes of P450 complex metabolize exogenous sub‐ stances including drugs, environmental chemicals and pollutants as well as products de‐ rived from plants. The metabolism of exogenous substances by CYP450 usually results in detoxification of the xenobiotic; however, the reactions triggered by such enzymes can lead to generation of toxic metabolites that contribute to the increased risk of developing cancers and other toxic effects [68].

of the rapid/intermediate type. These results corroborate with the current hypothesis that the

Finally, a meta-analysis was conducted to solve the problem of inadequate statistical power and controversial results based on accumulated data with small sample size [59]. Data from 14 studies performed between 2000 and 2011 were pooled and showed that TB patients with a slow acetylator genotype had a higher risk of anti-tuberculosis drug induced hepatotocixity than patients with rapid or intermediate acetylation (*p* < 0.001). Moreover, subgroup analyses indicate that both Asians and non-Asians slow acetylators develop anti-tuberculosis drug induced hepatotocixity more frequently. Additionally, there were statistically significant associations between NAT2\*5/\*7, NAT2\*6/\*6, NAT2\*6/\*7 and NAT2\*7/\*7 and the risk of anti-

As a final consideration, NAT acetylates more slowly not only isoniazid but also acetylhydra‐ zine, the immediate precursor of toxic intermediates, to the harmless diacetylhydrazine [60, 61]. This protective acetylation is further suppressed by INH competition. Therefore, slow acetylators may be prone to higher accumulation rates of INH toxic metabolites. Another important route to generate toxic intermediates is the direct hydrolysis of unacetylated INH [62], producing hydrazine that also induces hepatic injury [62, 63]. Pharmacokinetic studies showed that the serum concentration of hydrazine was significantly higher in slow acetylators than in rapid acetylators, probably due to the high INH concentration. The high amount of INH disposed of through this pathway is likely to lead to enhanced hydrolysis to hydrazine, since the rate of metabolic conversion of INH to acetylisoniazid is lower in slow than in rapid acetylators [64, 65]. All of these drug-disposal processes may support the finding that slow acetylators are prone to INH-induced hepatitis. We therefore conclude that screening of patients for the *NAT2* genetic polymorphisms can prove clinically useful for the prediction

Cytochromes P450 (CYP450) are hemoproteins and form the most important enzymatic group for Phase I biotransformation. The main activity of isozymes of CYP450 system is oxidation and they are located in the smooth endoplasmic reticulum, mainly in liver cells. However, these mono-oxygenases are also localized in the intestine, pancreas, brain, lung, kidney, bone marrow, skin, ovary and testicles [66]. The CYP450 proteins are clustered into families and subfamilies according to the similarity between the amino acid sequences: where family members have ≥ 40% identity in amino acid sequence, members of the same subfamily share

The CYP450s are responsible for the metabolization of several endogenous substrates and the synthesis of hydrophobic lipids such as cholesterol, steroid hormones, bile acids and fatty acids. Moreover, some enzymes of P450 complex metabolize exogenous sub‐ stances including drugs, environmental chemicals and pollutants as well as products de‐ rived from plants. The metabolism of exogenous substances by CYP450 usually results in detoxification of the xenobiotic; however, the reactions triggered by such enzymes can

and prevention of anti-tuberculosis drug induced hepatotoxicity.

acetylator status may be a risk factor for the hepatic side effects of isoniazid [58].

TB drug induced hepatotocixity [59].

112 Tuberculosis - Current Issues in Diagnosis and Management

**3.2. CYP450**

≥ 55% identity [67].

The complete sequencing of the human genome revealed the presence of about 115 genes of CYP450, including 57 active genes and 58 pseudogenes [67]. They belong to families 1-3 and are responsible for 70-80% of Phase I-dependent metabolism of clinically used drugs. Other families of CYPs are involved in metabolism of endogenous components [66]. The CYP2 constitutes the largest family of isoenzymes and comprises one third of all human CYPs. Genes encoding these enzymes are polymorphic and the frequency distribution of allelic variants in different ethnic groups differs.

The enzyme CYP2E1 is expressed mainly in the liver but can be found in other organs such as kidney, gastrointestinal tract and brain and involved in oxidation of substrates such as ethanol and the metabolism of many drugs and pre-carcinogens. Besides ethanol, CYP2E1 can be induced by various drugs such as INH but also by hydrocarbons, benzene, chloroform and various organic solvents [70].

The activity of CYP2E1 is also modulated by polymorphisms in several locations of its gene and more activity of this enzyme may increase the synthesis of hepatotoxins. Two polymor‐ phisms upstream of the *CYP2E1* transcriptional start site are characterized by *Pst* I and *Rs*a I digestion and appear to be in complete linkage disequilibrium (Figure 3). These two poly‐ morphisms are located in a putative HNF-q binding site and thus may play a role in the regulation of *CYP2E1* transcription and subsequent protein expression [71]. Genotypes of *CYP2E1* are classified as being \*1A/\*1A, \*1A/\*5 or \*5/\*5 by *Rsa* I based restriction analysis. The polymorphism detectable by *Dra* I (7632 T>A) is located in intron 6 and characterizes the allelic variant *CYP2E1\*6*. The other polymorphism is an insertion/deletion of 96 bp (*CYP2E1\*1D* and *\*1C* alleles) that regulates the expression of the gene [72]. Some studies have shown that allelic variants *CYP2E1 \*5*, *\*6* and *\*1D* would increase enzyme activity [71, 73]. However, other authors did not confirm any relationship with these polymorphisms with CYP2E1 activity [74].

**Figure 3.** Polymorphic and corresponding restriction enzyme cutting sites at *CYP2E1* [24].

Several studies have described the involvement of polymorphisms in *CYP2E1* in cancer development but results are controversial. The studies showed that the frequency of SNP -1053 C>T in the promoter region varies significantly in different ethnic groups. The mutant allele is present with a frequency of 2-8% in Euro-descendants but varies in Asia from 25 to 36% [75].

somal location not given) and omega (Ω) on chromosome 10 [80]. This classification is based on amino acid sequences, substrate specificity, chemical affinity, protein structure and enzyme kinetics. These enzymes are highly expressed in the liver and constitute up to 4% of total soluble proteins but can be seen in several other tissues [82]. GSTs have an overlap of specific substrates and the deficiency in one isoform can be compensated by other isoforms. Gluta‐ thione S-transferase mu (GSTM), glutathione S-transferase theta (GSTT) and glutathione S-

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The subfamily GST mu is encoded by five genes arranged in tandem (5\_-*GSTM4-GSTM2- GSTM1-GSTM5-GSTM3*-\_3), forming a 100 kb gene cluster on chromosome 1p13.3 (Figure 4). Polymorphisms have been identified and clinical consequences of genotypes resulting from combinations of alleles *GSTM1\*0*, *GSTM1\*A*, and *GSTM1\*B* have been widely investigated [78, 81, 89, 90]. Individuals who possess the homozygous null for *GSTM1* (GSTM1\*0/GSTM1\*0) do not express this protein. Thus, the absence of this gene can cause an increased accumulation of reactive metabolites in the body, increasing the interaction with cellular macromolecules and tumor initiation process. *GSTM1*\**A* and *GSTM1\*B* differ in only one base in exon 7 and encode monomers that form active dimers. The catalytic activity of these enzymes are very

The *GSTM1* gene is flanked by two almost identical 4.2-kb regions. *GSTM1\*0* originates from homologous recombination between the two repeat regions which results in a 16 Kb deletion containing the entire gene *GSTM1* (Figure 4). *GSTM1* is precisely excised leaving the adjacent *GSTM2* and *GSTM5* genes intact [78]. In a study of liver specimens of 168 autopsied Japanese subjects, observed was that the *GSTM1\*0* null allele was more frequent in livers with hepatitis

**Figure 4.** Structural localization of 100 kb gene cluster encoding the GST mu subfamily (chromosome 1p13.3). The figure indicates the homologous recombination event that can happen causing the null allele (*GSTM1\*0* - no *GSTM1*).

The subfamily GST theta consists of two genes, *GSTT1* and *GSTT2*, located on chromosome 22q11.2 and separated by approximately 50 Kb (Figure 5). Analysis of the 119 Kb portion

transferase Pi (GSTP) have been the most studied isoform [83-88].

and hepatocellular carcinoma compared to control livers [92].

similar [91].

Figure adapted from [78].

In 2003, Huang and coworkers showed an association of the wild-type genotype \*1A/\*1A with risk of developing liver damage induced by isoniazid in adult TB patients, regard‐ less of their profile of acetylation (OR 2.52; 95% CI 1.26 to 5.05) [76]. Later, Vuilleumier and colleagues showed association between this CYP and isoniazid-induced hepatotoxici‐ ty, without hepatitis, during chemoprophylaxis for TB (OR 3.4; 95% CI 1.1 to 12; *p* = 0.02). The risk of having high levels of liver enzymes was 3.4-fold higher when com‐ pared with all other *CYP2E1* genotypes [55]. Another study on Indian children with TB showed association between risk of hepatotoxicity and polymorphisms in *CYP2E1*, de‐ spite of low sample size [77]. However, a study with on a Korean population found no relationship between hepatic adverse effects with genotype \*1A/\*1A of *CYP2E1* during anti-TB treatment [51]. Lack of association between this CYP and antituberculosis druginduced liver injury was also observed in Brazil [58]. The discrepancy of these results may be due to differences in the frequencies of *CYP2E1\*1A* and *CYP2E1\*5* alleles among the populations and the different criteria to define hepatotoxicity used.

Finally, CYP2E1 converts acetyl hydrazine into hepatotoxins like acetyldiazene, ketene and acetylonium ion. The reaction of acetyl hydrazine (at high levels) with CYP2E1 leads to covalent binding of these secondary metabolites with intracellular proteins (Figure 1). As a consequence, intracellular changes occur resulting in loss of ionic gradients and decrease of ATP levels and consequent disruption of actin followed by cell lysis. Further studies in different populations and with a larger sample size are needed to determine the true influence of CYP2E1 gene polymorphisms on the occurrence of liver injury during treatment for TB.


**3. DNA Gyrase: A Validated Drug Target**

Topoisomerases are enzymes that participate in the overwinding or underwinding of DNA. They are commonly split into two classes, depending on the number of DNA strands cut during a single catalysis cycle: class I topoisomerases, which include eukaryotic topoisomerase I, prokaryotic topoisomerase IIIa, or reverse gyrase among others, and class II topoisomerases, whose members include (but are not restricted to) topoisomerase IV and DNA gyrase [76]. In *M. tuberculosis*, DNA gyrase is a heterotetrameric nanomachine, consisting of two GyrB and two GyrA subunits, and is essential for DNA replication, transcription, and repair in living cells [77].

*M. tuberculosis* is an exception in the prokaryotic world because of the presence of only one type I and one type II topoisomerase, whereas most other eubacteria have two enzymes of each type. In the canonical situation, DNA gyrase and topoisomerase IV, both type IIA topoisomerases, have distinct specific activities: DNA gyrase removes positive supercoils that accumulate ahead of

replication forks [78], whereas topoisomerase IV decatenates replication intermediates [79]. Thus, in *M. tuberculosis*, DNA gyrase being the unique topoisomerase IIA, it must be able to carry out both activities in vivo [80]. Furthermore, with no other topoisomerase IIA in *M. tuberculosis*, the DNA gyrase is the unique target of antibiotics from the fluoroquinolones (FQ) family (quinolones with higher cellular penetration efficiency), which bind and stabilize the DNA–DNA gyrase complex. Stabilization of this ternary complex leads to the cytotoxic accumulation of double-strand cleaved DNA fragments within the cell, inducing bacterial death [81]. Crystallographic structures of the isolated domain and the cleavage core, either in its *apo* form or co-crystallized with several FQ, brought crucial information to elucidate the mode of binding of these drugs [82–87]. The ratio FQ/DNA–DNA gyrase in the ternary complex is two FQ molecules per complex, with one molecule binding in each cleavage site, wedging between the two ends of the cleaved DNA strands on both halves of the complex, in a drug-binding pocket whose walls are formed by DNA base stacking (Figure 2A) [82]. The emergence of strains with multidrug resistance (MDR) phenotype, or extensively-drug resistance (XDR) phenotype in which drug resistance includes this family of antibiotics, has made improving the activity of this family of drugs by using structural data to be of utmost importance. The main goals of these studies are to increase specific drug/enzyme interactions, but also to find new molecules that inhibit this validated target without cross-resistance with FQ [88].

**Figure 2.** Inhibitors of DNA gyrase. (**A**) Top view of the X-ray structure of *M. tuberculosis* gyrase cleavage core in complex with DNA and moxifloxacin. Protein is shown in cartoon representation with transparent surfaces, with GyrB in blue and GyrA in pink. DNA is shown in orange, with moxifloxacin as red spheres (pdb: 5BS8). (**B**) Top view of the model of a complex of GSK000 (green spheres) with *M. tuberculosis* gyrase cleavage core and uncleaved DNA (in orange), based on the crystal structure of GSK299423 with *Staphylococcus aureus* gyrase (pdb: 2XCR). The same representation, as in panel A, was used for the protein. (**C**) Ball-and-stick representation of the ligands colored by element. (**D**) Generic chemical structure of the novel bacterial topoisomerase inhibitor (NBTI) series of compounds. Analog 1 is a classical NBTI, whereas analogs 2 and 3 combine the three favorable features for *M. tuberculosis* DNA gyrase inhibitor (MGI).

A significant amount of effort has thus been invested in discovering new *M. tuberculosis* gyrase inhibitors, mostly centered on the ATP- and DNA-binding sites, and particularly using in silico methods based on the emerging gyrase structural information, as extensively reviewed by Nagaraja and coworkers [89]. Although the ATP binding sites have been less successfully exploited as antibacterial targets, with the exception of the natural products, such as coumarins [90,91], it is worth noting that a candidate drug emerged from these studies. SPR720 (Table 3) is an orally bioavailable prodrug of SPR719, an aminobenzimidazole inhibitor of both gyrase and topoisomerase IV. Indeed, this novel class of antimicrobials targets the ATPase subunits of gyrase and topoisomerase IV, and it was optimized using SSBD and structure-activity relationship (SAR) studies of potency against both Gram-positive and some Gram-negative bacterial species [92,93]. Crystal structures of novobiocin (Table 3) bound to *Escherichia coli* GyrB subunit served as a starting point for ligand optimization [94], while further optimization of the metabolic profile led to the identification of SPR720 (formerly VXc-486) [95], whose suitability to be a drug candidate for the treatment of tuberculosis and non-tuberculosis mycobacterial infections was thoroughly evaluated [96,97]. The compound completed Phase I clinical trials in 2019 (study ID NCT03796910, sponsored by Spero Therapeutics, LLC), aimed at evaluating the safety, tolerability, and pharmacokinetics (PK) profile in healthy volunteers. Moreover, an in vivo combination of SPR720 with rifampicin and pyrazinamide (two first-line drugs used in TB treatment) showed comparable efficacy to the combination of three drugs, including moxifloxacin, rifampicin, and pyrazinamide [98].

Work on the DNA-binding site has also been productive, as GlaxoSmithKline (GSK) created a new class of type IIA topoisomerase inhibitors, called novel bacterial topoisomerase inhibitors (NBTIs) (Table 3) [99]. The crystallographic structures of the DNA-bound *Staphylococcus aureus* DNA gyrase with either NBTI or FQ, all obtained at high resolution, revealed that the binding sites for each drug are different [100]. Indeed, the NBTI 'bridges' the DNA and a transient non-catalytic pocket on the two-fold axis at the GyrA dimer interface, remaining close to the active sites and FQs binding sites (Figure 2B). As NBTIs display relatively poor activity against the *M. tuberculosis* DNA gyrase, the antitubercular profiles of 3000 compounds, representative of the chemical diversity of this family, were evaluated by high-throughput phenotypic screenings in vitro and in vivo [101]. MIC determination on *M. tuberculosis* H37Rv showed a high hit rate (68% of compounds with MIC values lower than 10 μM), with the most potent derivatives matching or even improving the MIC values for currently used TB drugs, including last-generation FQs. Overall, 29% of the compounds had MICs of < 1 μM, and 18% had MICs of < 0.1 μM. By using structural data provided by the work of Bax et al., the general structures of these TB-active compounds were divided into three different regions, each of them interacting with one of the three topologically important target-gyrase interacting regions [100]. While a left-hand side (LHS) is responsible for key contacts with the gyrase DNA substrate, a right-hand side (RHS) is embedded into the enzyme, potentially contributing to the protein target selectivity (Figure 2D). Last, a central linker unit (CU) establishes key interactions with the gyrase and offers the opportunity to modulate key physicochemical properties (Figure 2D). These SAR observations helped to schematize synthesis and to rationalize how to balance antimycobacterial potency with oral exposure, safety, and synthetic complexity, leading to the identification of the 7-substituted-1,5-naphthyridin-2-one core as a privileged LHS binder, the N-ethyl-4-aminopiperidines as a linker, and monocyclic aromatic rings with different substitution patterns as the best RHS binding option, in contrast to NBTIs bearing bicyclic rings as the RHS (Figure 2D, analogs 2 and 3) [101]. This work led to the identification of a subclass of naphthytidone/aminopiperidine-containing compounds that displayed activity against *M. tuberculosis*, both in vitro and in the mouse model, known as '*M. tuberculosis* DNA gyrase inhibitors' (MGIs) due to structural and activity differences with respect to NBTIs [101]. More recently, the mechanism of action of two such compounds, i.e., GSK000 and GSK325 (Figure 2C; Table 3), was assessed on the *M. tuberculosis* gyrase, showing that MGIs greatly enhanced DNA cleavage mediated by the bacterial enzyme, but they induced only single-stranded DNA breaks [102]. Their mechanism of action involves stabilizing covalent gyrase-cleaved DNA complexes and appears to suppress the ability of the enzyme to induce double-stranded breaks. Furthermore, these compounds maintained activity against mutant versions of DNA gyrase, bearing the three most commonly observed FQs resistance mutations, but displayed no activity against human topoisomerase IIα [102], suggesting good potential

as candidate drugs, especially in the presence of FQ resistance. Modeling studies were carried out by the authors using the crystal structure of the *M. tuberculosis* gyrase cleavage core and the NBTI crystal structure complex of *S. aureus* gyrase [100] (Figure 2B). Most importantly, these studies allowed to confirm that FQs and MGIs do not share the same binding site and bind in a mutually exclusive manner (Figure 2), considerably reducing the risk of developing cross-resistance phenotypes. μ

**Table 3.** *M. tuberculosis* DNA gyrase inhibitors.

μ

μ

μ

ND: not determined.

#### **4. General Remarks**

Several challenges need to be overcome for therapeutic molecules to be active against *M. tuberculosis.* Due to its metabolic adaptability and its known capabilities to occupy different niches inside the human host, from free aerobic bacteria to granulomas, an ideal molecule should be able to act against bacteria in very different, environmentally adapted states. The unique structure and composition of the *M. tuberculosis* cell wall are also well known to act as a barrier for potentially active compounds. To be active against latent and active infections, an ideal drug candidate should thus be able to reach bacteria in all the tubercular lesions and niches inside the human host [103], permeate the mycobacterial cell wall or be actively internalized, and deliver the desired bioactivity in bacteria under different metabolic states. To overcome these limitations and reduce the risk of further resistance development, TB drugs are delivered in combinations, starting from the standard DOTS (directly observed therapy short-course). Drug combinations, however, have to take in due account the bioavailability and pharmacokinetic properties of the single components and their associations, as extensively treated in this same journal issue [104].

In the course of the last ten years, it has become increasingly clear that some of the criteria commonly used to classify a given *M. tuberculosis* biological process, in many cases, an enzymatic step in a pathway, as a 'good' target for drug development, needed to be revised. This is particularly true for in vitro genetic essentiality. Even targets confirmed to be essential by the construction of specific conditional mutants do not necessarily show a good 'druggability', even when highly potent hits become available. The case of PknB is an emblematic example: despite the gene was early shown to be essential for *M. tuberculosis* growth, first by transposon mutagenesis [43], then through attempts to generate a knock-out mutant [44], yet several research groups, including ours, had to face the problem of the lack of correlation between hit potency in vitro and efficacy in vivo [50–52]. Similar issues were also reported for other *M. tuberculosis* kinase inhibitors, in addition to the cross-reactivity sometimes reported towards eukaryotic kinases, and the cytotoxicity shown by some compounds on human cell lines [105]. In addition, although the availability of crystal structures of both PknB and PknG in complex with hits issued from medium-throughput screens (mitoxantrone and AX20017, respectively) has looked as a promising 'proof-of-concept' [48,58], further structure-based work on these kinases has, so far, failed to produce suitable drug candidates. Many reasons might be evoked to explain the lack of *M. tuberculosis* kinase inhibitors that display significant antibacterial activity, ranging from the poor capacity to penetrate the mycobacterial cell and reach their target to the kinase redundancy in *M. tuberculosis* and their, relatively poor, substrate specificity [46], which prompted groups to seek for multiple kinase inhibition [105]. Yet, the main causes should perhaps be looked for in our, still limited, knowledge of mycobacterial molecular physiology and the regulatory networks in *M. tuberculosis*, in which Ser/Thr kinases are actors of a complex interplay [46,106]. Indeed, the activation mechanisms of both PknB and PknG are still a matter of speculation, and changes to *pknB* expression, either as depletion or overexpression, have been reported to alter the bacterial growth significantly [34]. Given the known *M. tuberculosis* metabolic plasticity, whose complexity has only recently started to be elucidated, thanks to the development of genetic and 'omics' tools [107], and the adaptability of the pathogen in the course of infection, it is now largely accepted that genetic essentiality of a putative target in laboratory conditions is not necessarily an indication of chemical vulnerability [15], and even more in clinical conditions. For these reasons, phenotypic screens have increasingly been employed in TB drug development to the detriment of target and structure-based methods, including for lead optimization [15], and the vast majority of candidate TB drugs that have been able to enter clinical trials in the last years were issued from this kind of screens [17,108].

Nevertheless, structure-based and computer-aided drug design maintain a clear potential for the future development of new anti-tubercular drug candidates. For instance, a recent, very promising success of structure-based and fragment-based approaches in TB drug discovery is the development of the so-called ethionamide boosters directed against the EthR repressor, one of which has been shown to be active both in vitro and in vivo [109]. In addition, the recent developments in X-ray crystallography [110], cryo-EM [4], and integrative structural biology methods [111] will all contribute to increasing the number of tools available to tackle the challenges that lay ahead. These opportunities are well exemplified by the case of mycobacterial DNA gyrase that, considering our capacity to obtain high-resolution structures of an almost full-length form of the *M. tuberculosis* enzyme [112], and the recent, high-resolution cryo-EM structure of *E. coli* gyrase in complex with NBTI [113], let us believe that SBDD will deliver a key contribution to developing new compounds against this 'old' but validated target. High-resolution snapshots of the complete mycobacterial gyrase machinery, especially if in complex with representative members of each known family of inhibitors, might revolutionize our knowledge of this key target and substantially increase chances of improving our therapeutic bullets. For instance, combining crystallographic and cryo-EM data could allow to perform structure-guided drug design to target these flexible complexes and identify new conformations of mycobacterial gyrase that could not, otherwise, be obtained by conventional structural methods. More generally, the integration of biophysical and structural biology data, with the notable contribution of high-resolution EM, will allow the drug discovery pipelines to work on a higher complexity level that was previously not achievable, now looking at targets in their larger biological context (e.g., complexes or cellular compartments). It is, therefore, foreseeable that, despite the technical challenges, target-based and structure-based approaches will have increasing relevance in future drug discovery and will give significant contributions in the search for new tuberculosis drugs.

**Author Contributions:** All authors contributed to conceptualization, the preparation of the draft, and the review of this work. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was partially supported by institutional grants from the Institut Pasteur and the CNRS.

**Acknowledgments:** We are grateful to all our past and present colleagues from the Structural Microbiology Unit, as well as collaborators from the former MM4TB Consortium, for so many fruitful exchanges and insightful discussions.

**Conflicts of Interest:** The authors declare no conflict of interest.


**NOVEL STRATEGIES IN ISCHEMIC HEART DISEASE**

Edited by **Umashankar Lakshmanadoss**

**INTECHOPEN.COM**

http://dx.doi.org/10.5772/1471 Edited by Umashankar Lakshmanadoss

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Nick Castle, Raveen Naidoo, Ajay Suri, Michael Galagudza, Jens Broscheit, John St.Cyr, Linda Shecterle, Mahdi Garelnabi, Javier Horta, Emir Veledar, Nadegda Pozdnyakova, Howard Prentice, Herbert Weissbach, Sandra Lindstedt, Malin Malmsjö, Richard Ingemansson, Joanna Hlebowicz, Ghayath Baroudi, Ghayda Hawat, Guijing Wang, Zefeng Zhang, Carma Ayala, Diane Dunet, Jing Fang, Anastasia Susie Mihailidou, Simone Gusmão Ramos, Elaine M. Floriano, Karina M. Mata, Cleverson R. Fernandes, Marcos Rossi, Antonio Padua Martins, Huirong Liu, Ke Wang, Xiaoliang Wang, Jue Tian, Kehua Bai, Jianqin Jiao, Jie Yang, Haibo Xu, Hyounju Kim, Satoshi Hirrako, Elizabeth Dean, Zhenyi Li, Wai Pong Wong, Michael E. Bodner, Guy Rousseau, Roger Godbout, Nermine Saleh, Magda Youssef, Mette Bjerre, Yue-Sheng Huang, Rong Xiao, Sadip Pant, Ping-Yen Liu, Yi-Heng Li, Jyh-Hong Chen, Umashankar Lakshmanadoss

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