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Genetic Polymorphism Governing the CYP2D6 Cytrochrome

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Published: Tue, 20 Feb 2018

Genetic Polymorphism Governing the CYP2D6 Cytrochrome P450 Enzyme Subfamily in Drug Metabolism

I. Abstract

The decoding of the human genome has opened up an immense opportunity for further research in designing treatment plans that can be more personalized. The composition of a person’s genome varies amongst individuals and also within populations. Individual responses to drug are inherited. The clinical implication of inter-individual variations is implicit in Cytochrome P450 enzymes that are prominent in drug metabolism. Polymorphism of over 20 enzymes involved in drug metabolism has been characterized and most of these involve the Cytochrome P450 enzymes. The Cytochrome P450 enzymes have been subjected to numerous evolutionary pressures over time, consequently producing various isoforms. The frequency of variant alleles can alter the pharmacokinetic parameters of the drug, especially of a drug with a narrow therapeutic index. These alleles can either have heightened responses to certain drugs causing toxicity or show very low compliance leading to therapeutic failure. Specifically, CYP2D6 is known to vary tremendously amongst different ethnic groups. Polymorphism of drug metabolizing enzymes such as CYP2D6 can severely affect the clinical outcome in regards to drug response. CYP2D6 gene is shown to have 74 variant alleles, when expressed in homozygous or heterozygous manners give rise to four distinct phenotypes. In this new era of genomic advancements, there is much hope to decipher variations pertaining to drug metabolism and gear the focus towards individualized medicine. Patient selection can be drastically improved by the employment of genotyping. Innovative technologies have made genotyping prevalent and we have come a long way since the advent of pharmacogenetic in the early 19th century.

Sir William Osler (1849-1919) documented that “variability is the law of life, and as no two faces are the same, no two bodies are alike, and no two individuals react alike, and behave alike under the abnormal conditions we know as disease.”

II. Personalized Medicine and Pharmacogenomics

A. Pharmacogenomics

The human genome project has it made possible for researchers to comprehend the complexity of biological pathways involved in disease states and focus on variations amongst individuals in regards to drug regimens (Ginsburg and Willard, 2009). The pharmacokinetic aspect of the body’s way of dealing with the drug such as adsorption, distribution, metabolism and elimination of the substrate factors into the variability of individual drug response (Kroemer and Meyer zu Schwabedissen, 2010). The pharmacogenetic variation in absorption and elimination are quite rare compared to the variation seen in drug elimination (Nebert, 1999). According to Nebert et al. (2004) “Clinical pharmacology is any particular response seen after a drug is administered”. However, this phenotypical drug response is rather ambiguous and has various biological and environmental influences as illustrated in Fig.1, which can lead to a gradient in drug efficacy and toxicity (D. R. Nelson et al., 2004). The phenomenon of genetic variability causing different reactions to drugs has been recognized for awhile as seen in Fig 2 but only recently has the idea become prevalent (March, 2000). In 1902, Sir Archibold Garrard regarded enzymes as vital endogenous biochemical substances required for detoxification in alkaptonuria (Hood, 2003). Sir Archibold Garrard later exemplified the enzyme deficit leading to adverse drug reactions as “in born errors of metabolism” (Hood, 2003). An inherited difference in tasting ability of phenylthiocarbamide was first discovered by a chemist, Arthur Fox in 1931. Arthur Fox’s finding in 1931 on genetic variability was considered a breakthrough finding in the field of pharmacogenetic (Hood, 2003). During World War II, the antimalarial drug such as primaquine showed differing results in Caucasian soldiers compared to the African American soldiers; African American soldiers showed greater occurrences of hemolytic anemia when administered drug (March, 2000). Metabolism as a concept became prevalent in mid 19th century when scientists began to decipher the excretory metabolites of consumed substances (Nebert and Vesell, 2004).

Pharmacogenomics, the term coined in 1995, focuses on a person’s genetic composition, gene and respective gene products, and illustrates how this variability affects drug metabolism (Nebert and Vesell, 2004)(Maria Almira Correia, 2009). The two major aspects of pharmacogenomics are a) To recognize the genes that are affected in a disease state; and b) To focus on the variant alleles that alter our response to the drugs (Wolf, Smith, and Smith, 2000).

Figure 1 Factors influencing individual drug response.

Reprinted from “Pharmacology, pharmacogenetics, and pharmacoepidemiology: three Ps of individualized therapy” By S. Dawood , 2009, Cancer Investigation, 27, 809-815

Figure 2 Favism is implicit in certain population that consume fava beans

A Greek philosopher Pythagoras first noted this phenomenon that was later found to be associated with acute hemolytic anemia in people who consume the legumes. These people have deficiency in glucose-6-phospahte dehydrogenase and can show altered response to antimalarial drug Reprinted from “Pharmacogenomics: the promise of personalized medicine” by Hood Emily, 2003, Environ Health Perspect.; Aug;111(11):A581-9.

Pharmacogenomics encompasses the whole human genome, DNA, RNA and the associated gene products involved in the study of drug metabolism, drug transport, “target proteins (receptor, ion channels, enzymes)” and links these gene products to their affects on xenobiotics (Mini and Nobili, 2009). A drug that exhibits reduced efficacy does not always correlate with reduced levels of toxicity since remedial values and noxious side effects of a drug are often exerted via diverse biochemical pathways (Mini and Nobili, 2009). The study of pharmacogenomics, therefore, has vital therapeutic value because most disease states entail some sort of drug treatment (Kroemer and Meyer zu Schwabedissen, 2010). The study of genomics is now made it possible to predict safety, toxicity and efficacy of drugs and opt for a personalized treatment plan by targeting variant alleles (Dawood, 2009). The empirical notion of patients with a certain disease state reacting to drugs homogenously is flawed (Dawood, 2009). This conviction, however, does not account for genetic variation, which unfortunately leads to over 40% of patients either getting the incorrect drug or wrong dosage of the drug (Bordet, Gautier, Le Louet, Dupuis, and Caron, 2001). A Meta analysis study done in 1994, estimated that more than 2 million patients hospitalized in the US had fatalities related to adverse drug reactions (Lazarou, Pomeranz, and Corey, 1998). These results concluded that in 1994, the 106,000 fatalities associated with adverse drug effects ranked between fourth to sixth leading causes of death in the US(Lazarou et al., 1998). Regardless of strict and regulated standards for drug efficacy and prevention of toxicity, adverse drug reactions are prominent and a drug is never equivalently effective on a general population (Roses, 2000). Financially, neither the patients and/or the health insurance companies find it feasible to pay for drugs that are either ineffective or cause adverse effects (Roses, 2000). If a patient has blunted ability to metabolize a drug that is administered to them in normal doses this could easily lead to mortality due to toxic levels of the exogenous substance left in the system (Hood, 2003). Patients react to drugs in a heterogeneous manner compared to the notion of homogenous efficacy, which is particularly imminent in chemotherapeutic drugs (Dawood, 2009). Most chemotherapeutic drugs have narrow therapeutic index and any variability in metabolism of this drug can lead to adverse drug reaction (Dawood, 2009). The approach employed currently often leads to therapeutic failure and waste of time leading to expensive health care costs and valuable time (Hood, 2003). Therapeutic failure related to drug metabolism in diseases such as cancer, psychiatric disorders, and hypertension can be severely detrimental if the drugs do not take effect due to the presence of variantions in enzymes leading to high and low metabolizers (Hood, 2003). Although, genetic variability alone does not account for all the adverse effects of drugs seen in a patient, pinpointing the altered gene can be beneficial in tailoring a more precise therapy that involves less adverse effects (Hood, 2003). Therefore, understanding the complex interaction of individuals with their environment and underlying genetic variation will allow for a gradual shift from “one drug fits all” perception to an embodiment of individualized medicine (Dawood, 2009).

B. Individualized Medicine

Individualized medicine encompasses many attributes such as clinical, genetic, and environmental factors all intertwined in a complex meshwork affecting a disease state (Ginsburg and Willard, 2009). Thorough understanding of these various attributes can aid in development of personalized treatment plans and medication types/dosages leading to an effective patient care, reduction in drug toxicity and increase in drug efficacy (Ginsburg and Willard, 2009).

The ultimate goal of the drug is to have the most efficacious and least toxic effect on the patient (Dawood, 2009). However, clinical variables such as drug-drug interaction and metabolism of drug and drug transport show pronounced differences accounting for toxicity (Dawood, 2009). The statistics reveal that a certain drug is known to produce therapeutic effect only in 30% of the patients, whereas 30% of the patient show little or no advantageous effect to the drug, 10% are shown to have only deleterious effects (Maitland-van der Zee, de Boer, and Leufkens, 2000). For example if a patient is on an antidepressant, which usually take two weeks to take effect, predicting drug response for patients with a variant allele is advantageous in regards to predicting efficacy (Kirchheiner and Seeringer, 2007). Predicting drug response poses just as many challenges as do the study of inherited diseases related to genes (McCarthy and Hilfiker, 2000). The variant gene products involved in drug metabolism are related to regulation at the level of gene expression, post translational modification and drug-drug interaction, all of which affects individual responses to xenobiotics (McCarthy and Hilfiker, 2000).Typically, drug doses are determined by body surface area and for certain group of individuals the systemic exposure is presumed to be homogenous if the surface area is similar The surface area is mainly determined based on height and weight (Dawood, 2009). The variation however stems not necessarily from differences in physical factors but rather from discrepancy in drug metabolism and drug clearance (Galpin and Evans, 1993). Although, systemic monitoring for drugs with low therapeutics indicies has been employed, it still is not efficient enough to prevent therapeutic failure (Nebert and Vesell, 2004).

II. Genetic Polymorphism

A. Introduction

Genetic polymorphism is the variation in allele that is present at a locus and occurs in more than 1% of the population (Phillips, Veenstra, Oren, Lee, and Sadee, 2001). The allele is considered a mutation when it occurs in less than 1% of the population (Mini and Nobili, 2009). The human genome is 3 billion base pair long and the variation in one nucleotide sequence in the DNA occurs in every 100-300 bases (Hood, 2003). Single nucleotide polymorphism (SNP) is the most extensively studied genetic polymorphism, which accounts for most of the variation in drug metabolism (Schmith et al., 2003). The human genome has over 1.4 million single nucleotide polymorphisms 60, 000-100,000 is associated with drug effects ((Dawood, 2009)(Schmith et al., 2003). These SNP can gives rise to polygenic gene variants that can alter the pharmacokinetic and the pharmacodynamic portfolio of a drug leading to innate deviation in metabolism (W. E. Evans and McLeod, 2003). The gene loci that encodes for proteins involved in drug metabolism are inherently shown to have about 47-61% polymorphism, which in turn correlates to the immense differences in substrate breakdown (Nebert, 1999). Genes that have SNPs in the coding region usually change the amino acid sequence of the protein whereas the SNP in the regulatory region are known to control the concentration of the proteins (McCarthy and Hilfiker, 2000). An exogenous substance relays its effect by interacting either on the cell membrane, cytoplasm or in the plasma (Mini and Nobili, 2009). However, a substance that is known to be efficacious in most individuals can cause detrimental effects in some if they are homozygous for the variant alleles as seen in Fig 3. This variation can affect any of the compartment of interaction a drug asserts its effects (Mini and Nobili, 2009). These alterations can manifest into phenotypes that can cause adverse effects by enhancing or inhibiting normal physiological activity (Mini and Nobili, 2009). The human genome project has simplified the identification of roughly 100,000 SNP’s in the human genome, which can be employed to acquire accurate information on individual drug responses (Schmith et al., 2003). A haplotype is regarded as a blueprint in which not one but many SNP occur on the same chromosome (Hood, 2003). Although a single SNP may cause altered response to drugs, it is more likely the combination of SNPs on a single chromosome that may play a role in drug metabolism leading to polygenic phenotype (Hood, 2003). In the near future, clinical trials might be required to incorporate genotyping for potential drugs. The cost of genotyping for clinical trials has been predicted to cost approximately 1 million dollars (McCarthy and Hilfiker, 2000). Even though the additional cost to the trial is of concern, the overall end results might provide valuable information on drug metabolism amongst different ethnic groups, which would be beneficial in the long run.

Characterization of genes of enzymes involved in drug metabolism are shown to have considerable variations; about 3 to 10 variant alleles are considered to be of the common type and over 12 to 100 variant alleles that are uncommon and occur rarely (Nebert and Vesell, 2004). Initially, when the Human Genome Project was undertaken, there was little concern about the difference in sequencing of chromosome amongst different ethnic groups (Nebert, 1999). Most scientists at the time believed there would be no substantial discrepancy between chromosomes of an individual who is of an Asian descent compared to an individual of European descent (Nebert, 1999). Graham and Smith in the 1999 study showed that there is significant variation in drug metabolism amongst individuals of different ethnic backgrounds, which effects the pharmacokinetic variability of the enzyme that are involved in drug metabolism (Graham and Peterson, 1999)(Maitland-van der Zee et al., 2000). Recent study on Asian, Whites and Blacks showed that different ethnic populations differ in the frequency of alleles of a gene and this variant can result in altered drug responses (Limdi et al., 2010). The functional consequence on drug metabolism of the variant allele depends on the extension of mutation and frequency of occurrence in an individual subgroup (Maitland-van der Zee et al., 2000). To establish an accurate overall picture of variant alleles in different ethnic subgroups, an extensive SNP genotyping is needed, with an average group size of 1000 individuals in each subgroup (Nebert, 1999). The information derived from this can then be utilized for an extensive genotype-phenotype linkage study (Nebert, 1999).

Figure 3 Polymorphism affecting the concentration of a drug leading to toxic doses and low efficacy in individuals who are homozygous for the variant gene.

Reprinted from “Pharmacogenetics: implementing personalized medicine” By Enrico Mini; Stefania Nobili, Clinical Cases in Mineral and Bone Metabolism 2009; 6(1): 17-24

B. Adverse Drug Reaction

Drug-drug interactions are common when numerous drugs are ingested simultaneously (Wolf et al., 2000). These drug-drug interactions can induce or inhibit enzymes in the common pathway of metabolism causing adverse effects (Oesch, 2009). An individual who has reduced ability to metabolize a substrate can easily accumulate the drug if an alternative route is not accessible (Oesch, 2009). The pharmacokinetic differences in individuals can cause poor metabolizers to have increased amounts of systemic exposure to the drug and fast metabolizers having less than normal amounts resulting in therapeutic failure or even toxicity. (Bailey, Bondar, and Furness, 1998). Comprehending this inherited genetic variability in drug metabolism can herald a new era in individualized therapy (Dawood, 2009)(Oesch, 2009)(Wolf et al., 2000). Study of pharmacogenomics allows for ways to reduce adverse drug reactions by identifying the nature of the drug, reaction to the drug and metabolic targets of the drug (Phillips et al., 2001). All of the above can be utilized to create an extensive biomarker, which can then be employed by physicians to make appropriate dosing changes for individuals with variant alleles (Ginsburg, Konstance, Allsbrook, and Schulman, 2005). Alternatively, if reducing the dose is not a viable option, physicians can alter the treatment to include drugs that can by pass the deficient biochemical pathway (Ginsburg et al., 2005; Phillips et al., 2001). In order to utilize genotyping as a beneficial tool, physicians need to quantify variant drug responses to the specific gene unambiguously (Nebert, 1999). It is imperative that the candidate locus that is affected by the drug is identified and positive tests are employed for the variant alleles (Holmes et al., 2009). The

Genetic polymorphism plays a major role in drug efficacy and also in adverse drug reactions (Dawood, 2009). Pharmacogenomic studies are hard to conduct because the variation in drug metabolism is only known after the administration of the exogenous substance, as compared to inherited diseases which have clear family linkage (McCarthy and Hilfiker, 2000). It is highly unlikely that an entire family would be prescribed a certain drug at the same time so the variation in the allele is only known under clinical trials (McCarthy and Hilfiker, 2000). SNP profiling can be beneficial if it can predict the drug response in patients and the demographics of people affected (McCarthy and Hilfiker, 2000). For example, a study by Drazen in 1999 showed that variation in ALOX5 was correlated 100% of the time with patients being non-receptive to an antiasthmatic drug (Drazen et. al, 1999). However, the prevalence of the non-variant gene in ALOX5 occurs in only 6-10 % of the patients; therefore, for a drug to be efficacious, the percent frequency of variant allele needs to be determined (Drazen et. al, 1999;McCarthy and Hilfiker, 2000). The major questions to be addressed then is how prevalent is the variant gene? How often are patients in a certain demographic group prescribed a drug that can cause adverse effects (Maitland-van der Zee et al., 2000)?

A potential drug is marketed and distributed worldwide, however, most of the clinical trials are never encompass a broad range of population and most polymorphisms go undetected (McCarthy and Hilfiker, 2000). The clinical trials mainly consist of the Caucasian population in America and Europe, but a wider range of population is needed to pinpoint major variation amongst different ethnic groups (McCarthy and Hilfiker, 2000). Consequently, polymorphisms that are relevant in certain populations need to be studied and the target must be to address variant genes that are prevalent in drug metabolism (Maitland-van der Zee et al., 2000). Currently, there is little to no information on most of the drugs that are already in the market regarding genetic variability in drug metabolism (Maitland-van der Zee et al., 2000). In the future, potential drugs should include such “population based studies” in their clinical trials so fewer drugs would conform to one drug fits all motto (Maitland-van der Zee et al., 2000). Polymorphism profiling can have major implication in drug safety because a drug that poses adverse effects on a large subgroup could be restricted from being launched into the market (Ginsburg et al., 2005). Genotyping can permit physicians to detect different polymorphism in individuals and allow them to create drug regimens that are not only efficacious but pose least toxic effects (Oesch, 2009). Preferential genotyping by clinicians for variant alleles could drastically reduce drug related adverse effects and in turn will be economically feasible and productive in the long run (March, 2000; Nebert and Vesell, 2004). Patient selection could be drastically improved by employment of genotyping.

C. When is Genotyping Appropriate?

Most drug targets are not key candidates for genotyping (Kirchheiner and Seeringer, 2007). The blood sample is collected from the patient after a day or two of administration of the drug. Therefore, drugs that require an immediate attention to dose adjustment or drugs that have a high therapeutic index may not be feasible for genotyping (Kirchheiner and Seeringer, 2007). In addition drugs that are metabolized via more than one overlying biochemical pathway pose extreme difficulties in pinpointing the variant allele and do not benefit from genotyping. However there are enzymes that have variant alleles such as the Cytochrome P450 enzymes which metabolize drugs such as warfarin, morphine, tamoxifen etc. and this polymorphism can lead to altered response to a drug (Kirchheiner and Seeringer, 2007). Adjusting the dose based on plasma level concentration of the drug is not always adequate for these patients (Dawood, 2009). Genotyping in these cases can lead to increased efficacy by identification of polymorphism, which can reduce the costly and time-consuming dose adjustment period. For example, CYP2D6 is a major enzyme involved in the breakdown of antidepressants. The therapeutic effects of antidepressants are only seen after a few weeks of treatment (Kirchheiner and Seeringer, 2007). Therefore, if a patient is a poor metabolizer they will accumulate the drug vs. a person who is an ultra rapid metabolizer, who will show no therapeutic value. In the case of antidepressants, genotyping for the CYP2D6 polymorphism may be beneficial prior to the start of therapy.

Innovative technologies have made genotyping prevalent and we have come a long way since the advent of pharmacogenetic in the early 19th century. Pharmacogenetic disciplines if employed in pharmaceutical industry can aid in development of drugs that cater to the individual; this will allow for prospective drugs to be well suited for fewer people in comparison to drugs that assert mediocre efficacy in a vast group of individual. Food and Drug administration in 2004 permitted the employment of Chip technology known as AmpliChip by Rosche for identification of variant genes in the Cytochrome P450 pathway (http://www.roche-diagnostics.us/press_room/2005/011105.htm); (Ginsburg et al., 2005) Companies like Genelex Corporation of Seattle, Washington and Gentris are now enabling pharmaceutical companies and patients respectively to utilize Cytochrome P450 genotype profiling for CYP 2D6, CYP 2C9 and CYP2C19 enzymes (Hood, 2003). The marriage of genetics and medicine is going to become prominent in the years to come and by the year 2020 pharmacogenomics will become a vital tool utilized to market drugs. The information derived from these test will allow patients to be on customized “designer drugs”(Collins and McKusick, 2001), allow physicians to set appropriate prescription amount for initial dosing and establish monitoring system for individuals with variant alleles (Tweardy and Belmont, 2009).

III Cytochrome P450 Enzyme

A. Background

Variant alleles that lead to functional changes of gene product can have therapeutic consequences. These alleles can either have heightened responses to certain drugs causing toxicity or show none to very low compliance (Wolf et al., 2000). Polymorphism of over 20 enzymes involved in drug metabolism has been characterized and most of these involve the Cytochrome P450 enzymes (CYP) (Wolf et al., 2000). Cytochrome P450 enzymes are involved in metabolism of over 60% of drugs currently in the market today (Hood, 2003). Polymorphisms in the CYP enzymes are known to alter the pharmacokinetic aspects of exogenous substances affecting mainly the biotransformation of the substance (Kirchheiner and Seeringer, 2007). Polymorphism of the Cytochrome P450 enzyme was first discovered in relation to debrisoquine, a hypertension-correcting drug (March, 2000). Bob Smith, of Imperial College in London ingested debrisoquine and experienced severe hypotension after administration. In addition, his blood levels showed 20 fold decreased levels of drug metabolite compared to his colleagues (March, 2000; Nebert 1997). In 1988, Gonzalez and his group characterized and showed that the gene product that was causing the altered response to debrisoquine as CYP2D6; it was also found to be a liver microsomal enzyme. The cloning of this microsomal enzyme was the first look at genetic polymorphism at the molecular level (Gonzalez et al., 1988; Mini and Nobili, 2009). The study by Gonzales et al. and his group paved way for further studies geared to identify genetic polymorphism in a population that linked variant genes to alteration in drug metabolism and drug response (Mini and Nobili, 2009). Cytochrome P450s are mainly found in endoplasmic reticulum and in the mitochondria of a cell, and are copious in the liver (Porter and Coon, 1991). The CYP enzymes consist of about 49 genes that function primarily in drug metabolism (Maitland-van der Zee et al., 2000; Porter and Coon, 1991). In humans the CYP enzymes are major constituents in metabolism of fatty acids, prostoglandins, steroids and xenobiotics (Graham and Peterson, 1999). Daily diet intake of mammals consists of many natural products such as “terpenes, steroids, and alkoloids” and the CYP enzymes are major catalysts in the biotransformation and breakdown of these exogenous substances (Guengerich, 1991). Cytochrome P450 enzymes comprise of a super family of gene that encompass proteins predominantly involved in metabolizing of xenobiotics as well as endogenous substrates such as steroids, fatty acids, prostaglandins and arachidonate metabolites as shown in Table 1, therefore genetic polymorphism in the CYP enzymes can lead to many health related risks such as hypertension and cancer (Graham and Peterson, 1999; Jiang et al., 2005; Mayer et al., 2005). CYP enzymes are monooxygenases that catalyze non-specific oxidations of many substrates (Guengerich, 1991), (Porter and Coon, 1991). The synthetic exogenous substrates of the cytochrome enzymes range to approximately 200,000 entities, which can all have complex interplay amongst each other in inducing or inhibiting the various isoforms of the CYP enzymes (Porter and Coon, 1991). These enzymes however are capable of catalyzing novel substrates as well and therefore one cannot cap an upper limit on the number of possible potential substrates (Porter and Coon, 1991). Therefore, the evolutionary advantage in the immensity of the CYP isoform is a crucial survival tool for our cultivating environment as well as our dynamically changing physiological system.

Table 1. Exogenous and endogenous substrates of Cytochrome P450 enzymes

The substrate for the CYP enzymes are just as diverse for endogenous substance as they are for exogenous substances. The CYP enzymes are prominent catalytic enzymes involved in biotransformation of various substances.

Reprinted from “Miniereview: Cytochrome P450” By Todd D. Porter and Minor J. Coon, The Journal of Biological Chemistry, 1991; 266(21): 13649-13472

The rates of catalyzation of the CYP enzymes are relatively slow and this can provide further explanation into their pivotal role in drug disposition (Guengerich, 1991). In addition, most of the CYP enzymes are involved in rate-limiting steps of drug metabolism and this is a key determinant of the in vivo kinetics of the drug (Pelkonen, 2002). CYP enzymes are key players in the systemic exposure of a drug and the time period a drug can assert its action (Brockmoller, Kirchheiner, Meisel, and Roots, 2000). The CYP enzymes are involved in either forming the active metabolite of the drug from a prodrug or in metabolizing the drug into inactive by-products,both of which can influence the functional temporal aspect of a drug (Brockmoller et al., 2000). Metabolites created by the CYP enzymes can also be toxic; exerting their own mutagenic and allergenic effects (Brockmoller et al., 2000). The FDA requires pharmaceutical companies to identify on the product brochure one of twenty CYP enzymes that are involved in the biotransformation of the drug (Brockmoller et al., 2000). Interactions of different drugs concerning CYP enzymes are good predictor of drug-drug interaction, therefore marketed drugs are required to indicate the CYP enzyme involved in biotransformation of the drug on the product information (Andersson, 1991)(Brockmoller et al., 2000). However, this information does not include the polymorphism prominent within these CYP enzymes. The need for such information is crucial since these enzymes are notorious for genetic polymorphism (Brockmoller et al., 2000). Functional variations in the CYP enzymes are known to show a gradient in efficacy and variation in the quantity of the substrate present in the subject (Maitland-van der Zee et al., 2000; Wolf et al., 2000). Allelic variants causing poor, fast and ultrarapid metabolizing enzymes have been identified in most of the CYP enzymes. Most of the CYP enzymes in the liver show some degree of polymorphism (Anzenbacherova et al., 2000).

B. Cytochrome Gene Family Evolution

CYP enzymes are ubiquitous as they are found in every domain of living organism from Bacteria, Archaea and Eukarya and known to have originated from an ancestral gene approximately three and half billion years ago. The modern cytochrome probably originated with the Prokaryotes 1.5 billion years before the prevalence of atmospheric oxygen (Graham and Peterson, 1999; Nebert and Gonzalez, 1987; Werck-Reichhart and Feyereisen, 2000). In early eukaryotes, these enzymes not only maintained membrane veracity but also were primarily involved in the biosynthesis of endogenous hydrophobic substances such as fatty acids, cholesterol (Nebert and Gonzalez, 1987). The CYP mutilgene family diverged again 900 hundred million years later giving rise to enzymes predominantly involved in biosynthesis of steroids (Nebert and Gonzalez, 1987). This expansion lead to the another divergence of the two most important mammalian CYP families implicit in drug and carcinogen metabolizing enzymes currently known as CYP1 and CYP2 gene family (Nebert and Gonzalez, 1987). Finally, 400 million years ago dramatic expansion ensued primarily in CYP2, CYP3 and CYP4 families (Nebert and Gonzalez, 1987). This current expansion correlates to the time frame when aquatic animals merged onto the terrestrial land and were exposed to many hydrocarbon-based combustion material in the environment along with toxic plant products in their diet (Gonzalez and Nebert, 1990; D. R. Nelson and Strobel, 1987)

The generation of this multigene family is due to the multiple mechanistic changes over time that reflect the complexity and diversity of the CYP enzymes. Most of the changes are related to lack of intron conservation (Werck-Reichhart and Feyereisen, 2000), exon shuffling (Doolittle, 1985; Patthy, 1985), expression of redundant genes (Anderson et al., 1981; Barrell, Air, and Hutchison, 1976), alternative splicing, frame shit mutations and RNA editing (Andreadis, Gallego, and Nadal-Ginard, 1987; Atkins, Weiss,


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