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     1 Designing Drugs to Avoid Toxicity                                                                   2
3                                                                                                          3
4                                                                                                          4
5    GRAHAM F. SMITH                                                                                       5
6                                                                                                          6
7    Central Chemistry Team Lead, Merck Research Laboratories Boston,                                      7
8    33 Avenue Louis Pasteur, Boston, MA 02115, USA                                                        8
9                                                                                                          9
10                                                                                                         10
11                                                                                                         11
12   INTRODUCTION                                                                                     1    12
13                                                                                                         13
     THE SAFETY WINDOW                                                                                2
14                                                                                                         14
15   COMMON SAFETY RISKS AND THEIR SAR                                                                2    15
16   Toxicity associated with the liver                                                               2    16
17   Cardiovascular toxicity ( h ERG, ETC.)                                                          13    17
18   Genotoxicity/mutagenicity                                                                       16    18
19   Phospholipidosis                                                                                39    19
     Phototoxicity                                                                                   40
20                                                                                                         20
     Idiosyncratic toxicity                                                                          42
21                                                                                                         21
22   CONCLUSIONS                                                                                     42    22
23                                                                                                         23
24   REFERENCES                                                                                      43    24
25                                                                                                         25
26                                                                                                         26
27                                                                                                         27
                                            INTRODUCTION
28                                                                                                         28
29                                                                                                         29
     Two thousand four data from the Centre for Medicines Research show that toxicity is now
30                                                                                                         30
     the leading cause of failure of compounds in clinical development. With the improved
31                                                                                                         31
     systemic exposure, which came with better understanding of drug metabolism and phar-
32                                                                                                         32
     macokinetics (DMPK), came increased observations of dose-limiting toxicity [1]. The
33                                                                                                         33
     leading causes of drug failure are now tied at 30%, with toxicity as likely to be the demise
34                                                                                                         34
     of a drug’s development as lack of efficacy, (PK-related attrition now stands at 10%).
35                                                                                                         35
     Nevertheless, most safety-related attrition (70%) occurs pre-clinically following candidate
36                                                                                                         36
     selection, suggesting that we are still in need of better predictive models of in vivo toxicity.
37                                                                                                         37
     Where in vitro assays, or simple in vivo experiments, are predictive of adverse events in
38                                                                                                         38
     humans, then these are increasingly carried out earlier in the drug discovery cycle.
39                                                                                                         39
        The structure–toxicity relationships for mutagenicity and hepatotoxicity are already well
40                                                                                                         40
     established owing to robust in vitro assays which translate well to clinical outcomes. These
41                                                                                                         41
     assays have frequently been used to implicate common alerting structures or so-called
42                                                                                                         42
     ‘structure alerts’. Identifying structural alerts for toxicity, and high-throughput assays for
43                                                                                                         43
     early indicators of toxicity issues in vivo, have become a normal part of early drug discovery.
44                                                                                                         44
     Regulatory authorities require that these robust assays be run on all new chemical entities
45                                                                                                         45
     before entering first-in-human trials.
46                                                                                                         46

     Progress in Medicinal Chemistry – Vol. 50      1                             Ó 2011, Elsevier B.V.
     Edited by G. Lawton and D.R. Witty                                             All rights reserved.
     DOI: 10.1016/B978-0-12-381290-2.00001-X
2                          DESIGNING DRUGS TO AVOID TOXICITY


1       Sometimes, inadvertently, medicinal chemists do introduce toxicophores into drug mole-          1
2    cules. Most often their reactive nature is produced or enhanced in vivo during normal meta-        2
3    bolic processes. Wherever possible this review elaborates the biochemical mechanism attrib-        3
4    uted to this type of toxicity. This allows medicinal chemists to validate the mechanism in their   4
5    own case and also to contextualize their own molecules in terms of their likelihood to undergo     5
6    similar biotransformation. Some successfully marketed drugs are positive in glutathione            6
7    binding assays [2], however, it is well established that the toxicities of known compounds         7
8    with chemically reactive metabolites can be correlated with the generation of hepatic protein      8
9    adducts and/or the detection of stable phase II metabolites such as glutathione conjugates.        9
10      The genotoxic carcinogens have the unifying feature that they are either electrophiles per se   10
11   or can be activated to form electrophilic reactive intermediates. Hard electrophiles generally     11
12   react with hard nucleophiles such as functional groups in DNA and lysine residues in proteins.     12
13   Soft electrophiles react with soft nucleophiles, which include cysteine residues in proteins and   13
14   in glutathione. Glutathione has a concentration of approximately 10 mM in the liver. Free          14
15   radicals can also react with lipids and initiate lipid peroxidative chain reactions [3]. The       15
16   presence of a toxicity risk, or even the confirmation of a metabolic pathway to known toxicity,    16
17   does not preclude a molecule from entering development. The risks are evaluated in the             17
18   context of the body’s highly developed ability to clear toxic molecules from circulation and to    18
19   recover from damage.                                                                               19
20                                                                                                      20
21                                                                                                      21
22                                   THE SAFETY WINDOW                                                  22
23                                                                                                      23
24   All drugs are toxic at some level and so a major challenge in drug discovery is to find a          24
25   margin of efficacy, over adverse events or toxicities, sufficient to provide clinical benefit to   25
26   patients whilst avoiding putting them at unnecessary risk. The therapeutic index (TI) is           26
27   commonly used in the pharmaceutical industry and is the ratio of the no observable adverse         27
28   event level (NOAEL) divided by the human efficacious exposure level (Ceff) or exposure at          28
29   the maximum anticipated human dose (Cmax).                                                         29
30      To determine margin, it is recommended to compare plasma Cmax from animal pharma-               30
31   cology and toxicity studies with (predicted) human pharmacokinetic Cmax data using                 31
32   unbound free fraction [4]. Depending on the disease target and nature of toxicity Ctrough          32
33   or area under the curve (AUC) can also be used to determine margins. Ideally these margins         33
34   would be around 10-fold or more over a reversible toxicity outcome which is observed in            34
35   animal testing, but which can also be clinically monitored easily in humans.                       35
36                                                                                                      36
37                                                                                                      37
38                      COMMON SAFETY RISKS AND THEIR SAR                                               38
39                                                                                                      39
40                              TOXICITY ASSOCIATED WITH THE LIVER                                      40
41                                                                                                      41
42   CYP inhibition                                                                                     42
43                                                                                                      43
44   One of the liver’s main physiological roles is the clearance and metabolism of xenobiotics         44
45   into hydrophilic metabolites in order to facilitate their excretion. The liver has an abundance    45
46   of xenobiotic metabolizing enzymes and a high capacity for both phase I and phase II               46
GRAHAM F SMITH                                        3


1                        biotransformation. It receives more than 80% of its blood flow from the portal vein into          1
2                        which drugs are absorbed from the gastrointestinal tract and therefore liver is often a primary   2
3                        target for chemical-induced toxicity. There is the possibility that reactions catalysed by        3
4                        cytochrome p450 (CYP) enzymes may generate metabolites that are not only more toxic but           4
5                        also more reactive than the original xenobiotic. Drug-induced liver injury is the most            5
6                        frequent reason for the withdrawal of an approved drug from the market. Drug-induced              6
7                        liver injury has now become the leading cause of liver failure in the Unites States and results   7
8                        in at least 2700 deaths per annum [5].                                                            8
9                           Time-dependent inhibition (TDI) of CYPs refers to a change in potency during an in vitro       9
10                       incubation or dosing period in vivo, as opposed to a normal reversible inhibitor dose             10
11                       response. Inhibition of specific CYP enzymes by a drug can lead to pharmacokinetic                11
12                       changes in another drug, or so-called drug–drug interactions [6]. When inhibition affects         12
13                       the major metabolic route of another enzyme, and therefore alters (usually increases)             13
14                       exposure, this leads to unpredictable exposure levels and often to unacceptable risks to          14
15                       patients. In common with other proteins, CYPs are eventually metabolized and replaced if          15
16                       they are irreversibly inhibited. CYP enzymes have a turnover of the order of 1–2 days.            16
17                       However, TDI is often associated with bioactivation to electrophilic species which have the       17
18                       potential for a number of toxic pathways beyond the simple inhibition of CYPs.                    18
19                          There are several known mechanisms of CYP inhibition:                                          19
20                                                                                                                         20
21                       *   Competing enzyme substrates affecting the turnover of other drugs.                            21
22                       *   Competitive inhibitors such as quinidine which are not substrates.                            22
23                       *   Haem ligands: non-selective metal chelators such as the imidazole antifungals.                23
24                       *   Metal inhibitor complex forming drugs such as erythromycin.                                   24
25                       *   Inactivation or suicide inhibitors such as tienilic acid.                                     25
26                                                                                                                         26
27   There are good methods of in vitro assessment of CYP inhibition and induction. The                                    27
28   outcome of this is that common motifs and SAR for these toxic mechanisms exist.                                       28
29   The following structure classes have well-established mechanisms for CYP inhibition.                                  29
30                                                                                                                         30
31                       Alkynes                                                                                           31
32                       Mechanism-based CYP inhibition (MBI) can arise from the covalent attachment of alkyne             32
33                       metabolites to the CYP protein. The formation of these adducts is described in Scheme 1.1.        33
34   [(Schem_1)TD$FIG]                                                                                                     34
35                                                                                                                         35
36                                                                                                                         36
37                                                                                                                         37
38                                                                                                                         38
39                                                                                                                         39
40                                                                                                                         40
41                                                                                                                         41
42                                                                                                                         42
43                                                                                                                         43
44                                                                                                                         44
45                                                                                                                         45
46                                             Scheme 1.1   Oxidation of alkynes to electrophilic species                  46
4                         DESIGNING DRUGS TO AVOID TOXICITY


1    Reactive metabolites can also be generated which may form covalent adducts with CYP            1
2    proteins or other proteins leading to toxicity [7–10]. Generation of alkyne-CYP intermediate   2
3    (A) can lead directly to the haem-bound product (B). For example, oxirene (C) (derived         3
4    from ring closure of A) can react with a CYP haem nitrogen generating B, and can also react    4
5    with other nucleophilic sites in the CYP protein. Ketene D (formed by the migration of the     5
6    R2 group in intermediate A) can also react with CYP and other proteins to form potentially     6
7    toxic conjugates.                                                                              7
8       Gestodene (1) is one of many synthetic steroid drugs, including oral contraceptives,        8
9    which contain an acetylene moiety. This drug was shown to be a mechanism-based inhibitor       9
10   of CYP3A4 and 3A5. A variety of other alkyne-containing steroids have also been evaluated      10
11   and show differing degrees of activity [11]. 17a-Ethynylestradiol (2) is a common compo-       11
12   nent of oral contraceptives and taken by millions of women worldwide. This steroid has         12
13   been shown to be a mechanism-based inhibitor of CYP3A4 in vitro[12]. However, admin-           13
14   istration of 17a-ethynylestradiol to women has been shown to have no impact on either          14
15   intestinal or hepatic CYP3A4 activity [13]. This is most likely to be due to the very low      15
16   doses required to achieve effective contraception, thereby mitigating the potential drug–      16
17   drug interaction risk.[(Fig._1)TD$IG]                                                          17
18                                                                                                  18
19                                                                                                  19
20                                                                                                  20
21                                                                                                  21
22                                                                                                  22
23                                                                                                  23
24                                                                                                  24
25                                                                                                  25
26                                                                                                  26
27                                                                                                  27
28      CYP inhibition is the most common toxicity associated with alkyne-containing                28
29   drugs. Therefore, early investigation of metabolic routes (in vitro and in vivo), coupled      29
30   with reactive metabolite screening, is warranted for medicinal chemists studying               30
31   alkynes. Compounds should be evaluated across a range of CYP enzymes/species                   31
32   (with and without pre-incubation) to ensure that the potential for inhibition is fully         32
33   evaluated.                                                                                     33
34                                                                                                  34
35   Thiophenes                                                                                     35
36   The thiophene ring is susceptible to hepatic oxidation by CYP and undergoes epoxida-           36
37   tion, followed by epoxide ring opening with nucleophilic biomolecules, to give adducts         37
38   [14–22] (Scheme 1.2). Alternatively the epoxide can open to give a (-thionoenal which          38
39   can also undergo adduct formation. The thiophene sulphur can also undergo oxidation,           39
40   thus activating the ring towards nucleophilic addition of biomolecules. Peroxidase addi-       40
41   tion of chlorine to the thiophene sulphur can also activate the ring towards nucleophilic      41
42   addition. Both the epoxide and the S-oxides have been postulated as reactive intermedi-        42
43   ates. Identification of any of these metabolites therefore implies formation of reactive       43
44   intermediates.                                                                                 44
45      Tienilic acid (3), a diuretic, is a mechanism-based inhibitor of CYP2C9 and seems           45
46   to inactivate it stoichiometrically. The molecule was launched onto the market and             46
GRAHAM F SMITH                                     5
     [(Schem_2)TD$FIG]
1                                                                                               1
2                                                                                               2
3                                                                                               3
4                                                                                               4
5                                                                                               5
6                                                                                               6
7                                                                                               7
8                                                                                               8
9                                                                                               9
10                                                                                              10
11                                                                                              11
12                                                                                              12
13                                                                                              13
14                                                                                              14
15                                                                                              15
16                                                                                              16
17                                                                                              17
18                               Scheme 1.2   Metabolism of thiophenes                          18
19                                                                                              19
20                                                                                              20
21                                                                                              21
22                                                                                              22
23   then subsequently withdrawn in 1982 due to a link with hepatitis [23–25]. The non-         23
24   steroidal anti-inflammatory suprofen (4) showed nephrotoxicity in the clinic and is a      24
25   mechanism-based inhibitor of CYP2C9. It was marketed and subsequently withdrawn            25
26   due to cases of acute renal failure [26, 27]. The antiplatelet drug panaldine              26
27   (Ticlopidine) (5) shows TDI of CYP2B6; because it is linked with increased risk of         27
28   agranulocytosis its use has been replaced by clopidogrel (Plavix) (6) [28]. OSI-930 (7)    28
29   was being developed for oncology when it was discovered that the molecule reacted          29
30   via the sulphoxide to form adducts with CYPs 3A4 and 2D6 [29]. In all of these cases       30
31   sulphoxide and glutathione adducts of the thiophene moiety have been detected and          31
32   are postulated to cause the time-dependent inhibition of CYP enzymes and further           32
33   related toxicities.                                                                        33
34      One way to reduce or inactivate this pathway is to introduce 2,5-substitution on the    34
35   thiophene ring. Alternatively, the ring can be deactivated towards nucleophilic attack     35
36   through introduction of adjacent functionality. Introduction of an alternative metabolic   36
37   weak point elsewhere in the molecule may also reduce toxic exposure overall.               37
38   Examples of these strategies can be seen in Zyprexa (8) and Plavix (6) [31–35],            38
39   two commercially successful, widely marketed drugs. It appears that a small structural     39
40   change between panaldine (5) and Plavix, which introduces an additional metabolic          40
41   route, reduces thiophene-related hepatotoxicity. Panaldine generates about 20 metabo-      41
42   lites, some of which covalently bind to proteins, while the primary metabolic fate of      42
43   Plavix is hydrolysis of the methyl ester and some glucuronidation of the resulting         43
44   acid. Plavix is dosed at 75 mg QD, while panaldine is dosed at 250 mg BID, so the          44
45   dose difference between panaldine and Plavix may also be a potential mitigating            45
46   factor.[(Fig._1)TD$IG]                                                                     46
6                         DESIGNING DRUGS TO AVOID TOXICITY


1                                                                                                 1
2                                                                                                 2
3                                                                                                 3
4                                                                                                 4
5                                                                                                 5
6                                                                                                 6
7                                                                                                 7
8                                                                                                 8
9                                                                                                 9
10                                                                                                10
11                                                                                                11
12                                                                                                12
13                                                                                                13
14                                                                                                14
15                                                                                                15
16                                                                                                16
17                                                                                                17
18                                                                                                18
19                                                                                                19
20                                                                                                20
21                                                                                                21
22                                                                                                22
23                                                                                                23
24                                                                                                24
25                                                                                                25
26   [(Fig._1)TD$IG]                                                                              26
27                                                                                                27
28                                                                                                28
29                                                                                                29
30                                                                                                30
31                                                                                                31
32                                                                                                32
33                                                                                                33
34                                                                                                34
35                                                                                                35
36                                                                                                36
37                                                                                                37
38   Furans                                                                                       38
39   In a similar manner to that for thiophenes, furan toxicity occurs via furan epoxidation      39
40   followed by epoxide ring opening to a g-keto aldehyde which in turn forms adducts with       40
41   biomolecules and induces toxicity [36, 37] (Scheme 1.3). Alternatively, the epoxide can      41
42   ultimately give rise to a lactone which can also form adducts. The epoxide has been          42
43   postulated as the reactive intermediate common to all observed metabolites. Identification   43
44   of any of these metabolites therefore implies formation of the epoxide.                      44
45      The clinical development of the 5-lipoxygenase inhibitor L-739,010 (9) was discontinued   45
46   by Merck due to hepatotoxicity; the compound is a mechanism-based inhibitor of CYP3A4        46
GRAHAM F SMITH                                        7


1                      [38–40]. Upon incubation with recombinant CYP3A4, a covalently bound adduct of the              1
2                      compound was formed, which was identified using mass spectrometry.                              2
3                         The HIV protease inhibitor L-754,394 (10) showed hepatotoxicity via potent mechanism-        3
4                      based inhibition of CYP3A4 and its clinical development was discontinued. It also has been      4
5                      shown subsequently for L-756,423 (11) that attachment of benzofuran through the 2-              5
6                      position, potentially blocking epoxidation, results in the removal of the furan-associated      6
7                      toxicity [41–43]. The fungal pneumotoxin Ipomeanol (12) was also developed for oncology         7
8                      and then halted due to hepatotoxicity. Upon activation of Ipomeanol with rabbit CYP4B1 in       8
9                      the presence of N-acetyl cysteine and N-acetyl leucine a major product (13) consistent with     9
10                     furan epoxide formation was observed and characterized [44–46].                                 10
11                        It is interesting to note that there are examples of 2,5-disubstituted benzofurans such as   11
12                     ranitidine (14) [47] which do not undergo typical furan metabolism. This is probably due to     12
13                     their low lipophilicity, low dose and additional substitution. Substituted benzofurans have     13
14                     been observed to undergo metabolism. Benzofuran itself undergoes the typical furan              14
15                     hydroxylation at the 2-position, possibly through direct hydroxylation and also potentially     15
16                     through epoxidation, followed by ring opening to generate 2-hydroxyphenylacetic acid [48].      16
17   [(Fig._1)TD$IG]                                                                                                   17
18                                                                                                                     18
19                                                                                                                     19
20                                                                                                                     20
21                                                                                                                     21
22                                                                                                                     22
23                                                                                                                     23
24                                                                                                                     24
25                                                                                                                     25
26                                                                                                                     26
27                                                                                                                     27
28                                                                                                                     28
29                                                                                                                     29
30                                                                                                                     30
31                                                                                                                     31
32                                                                                                                     32
33                                                                                                                     33
34                                                                                                                     34
35                                                                                                                     35
36                                                                                                                     36
37                                                                                                                     37
38                                                                                                                     38
39                                                                                                                     39
40                                                                                                                     40
41                                                                                                                     41
42                                                                                                                     42
43                                                                                                                     43
44                                                                                                                     44
45                                                                                                                     45
46                                                                                                                     46
8                         DESIGNING DRUGS TO AVOID TOXICITY

     [(Schem_3)TD$FIG]
1                                                                                                 1
2                                                                                                 2
3                                                                                                 3
4                                                                                                 4
5                                                                                                 5
6                                                                                                 6
7                                                                                                 7
8                                                                                                 8
9                                                                                                 9
10                                                                                                10
11                                                                                                11
12                               Scheme 1.3    Furan oxidative metabolism                         12
13                                                                                                13
14   Benzodioxolanes                                                                              14
15   The benzodioxolane moiety is associated with mechanism-based irreversible inhibition         15
16   and/or induction of CYPs. In addition some compounds that contain the benzodioxolane         16
17   moiety are associated with hepatotoxicity. CYP-dependent oxidation of the methylene          17
18   leads to both a reactive carbene intermediate (A) which can form irreversible adducts with   18
19   the haem of CYPs (metal inhibitor complex) or the catechol (B) which is an ortho-            19
20   quinone precursor and known toxin through redox chemistry. The mechanism of toxicity         20
21   and CYP inhibition of benzodioxolane compounds has been discussed in detail [49–51]          21
22   (Scheme 1.4).                                                                                22
23      Paroxetine (15) is a marketed selective seratonin reuptake inhibitor (SSRI) with a        23
24   known CYP2D6 inhibition profile; it is both a reversible and a time-dependent                24
25   CYP2D6 inhibitor. This results in significantly increased exposure to co-medications         25
26   that are metabolized by CYP2D6. Metabolism of the benzodioxolane group has been              26
27   strongly implicated in the CYP2D6 inhibition shown by paroxetine [52–56] and recent          27
28   studies have shown that the potency of paroxetine as a CYP2D6 inhibitor in vitro             28
29   increases eightfold following pre-incubation [57]. The increase in potency was asso-         29
30   ciated with the formation of a CYP mechanism-based inhibitor complex.                        30
31   Administration of paroxetine has been shown to convert some volunteers who are               31
32   extensive CYP2D6 metabolisers to a poor metaboliser phenotype [58]. In addition              32
33   paroxetine inhibits its own metabolism leading to non-linear time-dependent pharma-          33
34   cokinetics. The half-life of paroxetine after single doses of 20 mg/day is 10 h but after    34
35                                                                                                35
36                                                                                                36
37   [(Schem_4)TD$FIG]                                                                            37
38                                                                                                38
39                                                                                                39
40                                                                                                40
41                                                                                                41
42                                                                                                42
43                                                                                                43
44                                                                                                44
45                                                                                                45
46                              Scheme 1.4    Metabolism of benzodioxolane                        46
GRAHAM F SMITH                                         9


1    multiple doses of 20 mg/day this increases to 24 h [59]. While, the fate of the benzo-           1
2    dioxolane is well established in vitro, it is of note that most SSRIs are relatively potent,     2
3    reversible inhibitors of CYP2D6.                                                                 3
4       Niperotidine (16) is an H2 antagonist structurally related to ranitidine. Twenty-five cases   4
5    of acute hepatitis (including one death from fulminant hepatitis) associated with niperotidine   5
6    use were reported in Italy between March and August 1995 and the drug was withdrawn              6
7    from the market. The methylenedioxy group of niperotidine (absent in ranitidine) is known        7
8    to undergo metabolism to catechol and quinone metabolites [60, 61].                              8
9       Methylenedioxymethamphetamine (MDMA) (17) has been shown to inhibit CYP2D in a                9
10   time-dependent manor through a mechanism producing a UV absorption spectrum consis-              10
11   tent with a carbene formation [6]. MDMA causes liver damage in humans.[(Fig._1)TD$IG]            11
12                                                                                                    12
13                                                                                                    13
14                                                                                                    14
15                                                                                                    15
16                                                                                                    16
17                                                                                                    17
18                                                                                                    18
19                                                                                                    19
20                                                                                                    20
21                                                                                                    21
22                                                                                                    22
23                                                                                                    23
24                                                                                                    24
25                                                                                                    25
26                                                                                                    26
27                                                                                                    27
28                                                                                                    28
29      Fortunately, several viable isosteric replacements are available for the benzodioxo-          29
30   lane structure. Replacement of one of the oxygen atoms with a methylene results in a             30
31   dihydrobenzofuran moiety, which may often show similar pharmacology to a benzo-                  31
32   dioxolane. The dihydrobenzofuran system can be rather susceptible to oxidative metab-            32
33   olism, and this should be checked promptly when this group is employed (Scheme 1.5).             33
34   The difluorobenzodioxolane group is a metabolically blocked at the ‘methylene’ car-              34
35   bon, and this does not undergo the same metabolic reactions as the methylenedioxy                35
36   group. The difluorobenzodioxolane group is rather unusual as it is considerably more             36
37   lipophilic than the methylenedioxy group. There are no drugs in the MDDR (molecular              37
38   detection of drug resistance) drug database containing this moiety. The methylene                38
39   carbon may also be blocked with other groups, for example as a dimethylketal, although           39
40   the stability of such groups towards acid-catalysed hydrolysis needs to be carefully             40
41   assessed.                                                                                        41
42      There are many additional groups that have the potential to mimic a benzodioxolane.           42
43   Owing to their instability towards hydrolysis in dilute aqueous acid, benzoxazoles should        43
44   also be employed with caution, if at all. The benzodioxane ring-expanded system appears          44
45   not to be implicated in the same kinds of toxicity/mechanism-based CYP inhibition as the         45
46   benzodioxolane group.                                                                            46
10                                         DESIGNING DRUGS TO AVOID TOXICITY
     [(Schem_5)TD$FIG]
1                                                                                                   1
2                                                                                                   2
3                                                                                                   3
4                                                                                                   4
5                                                                                                   5
6                                                                                                   6
7                                                                                                   7
8                                                                                                   8
9                                                                                                   9
10                                                                                                  10
11                                                                                                  11
12                                                                                                  12
13                                                                                                  13
14                                                                                                  14
15                                                                                                  15
16                                                                                                  16
17                                                                                                  17
18                                                                                                  18
19                                                                                                  19
20                                                                                                  20
                                             Scheme 1.5   Some potential benzodioxolane isosteres
21                                                                                                  21
22                                                                                                  22
23                                                                                                  23
24                                                                                                  24
25
     Haem Ligands                                                                                   25
     The previous examples of potential liver toxins all form covalent inhibitor complexes with
26                                                                                                  26
     CYPs and other proteins. Another commonly encountered class of inhibitors is the haem
27                                                                                                  27
     ligands which offer lone pair donation, usually from nitrogen, to stabilize the iron in the
28                                                                                                  28
     haem complex. These molecules have an affinity for the active site of CYPs in both the
29                                                                                                  29
     oxidized and reduced forms but are reversible inhibitors (Scheme 1.6). Many heterocycles
30                                                                                                  30
31                                                                                                  31
32                       [(Schem_6)TD$FIG]                                                          32
33                                                                                                  33
34                                                                                                  34
35                                                                                                  35
36                                                                                                  36
37                                                                                                  37
38                                                                                                  38
39                                                                                                  39
40                                                                                                  40
41                                                                                                  41
42                                                                                                  42
43                                                                                                  43
44                                                                                                  44
45                                                                                                  45
46                                                        Scheme 1.6   Haem ligands                 46
GRAHAM F SMITH                                         11


1    frequently used in drug-like molecules are capable of performing this role, for example            1
2    pyridines, azines and azoles [62].                                                                 2
3       The 11-b-hydroxylase inhibitor metyrapone (18) is an inhibitor of cortisol synthesis and        3
4    of CYP3A4 [63, 64]. Metyrapone also causes induction of CYP3A4 synthesis in hepato-                4
5    cytes. The HIV protease inhibitor ritonavir (19) [65, 66] contains two 5-substituted thia-         5
6    zoles. Ritonavir is a potent inhibitor of CYP3A-mediated biotransformations (e.g. nifedi-          6
7    pine oxidation and terfenadine hydroxylation). Ketoconazole (20) is a member of the                7
8    antifungal imidazole drugs. Ketoconazole strongly inhibits CYP3A4 selectively [67].                8
9    Sulconazole (21), another member of the antifungal imidazole derivatives, strongly inhibits        9
10   most CYPs (1A2, 2A6, 2B6, 2C9, 2C19, 2D6, 2E1, 3A4).[(Fig._1)TD$IG]                                10
11                                                                                                      11
12                                                                                                      12
13                                                                                                      13
14                                                                                                      14
15                                                                                                      15
16                                                                                                      16
17                                                                                                      17
18                                                                                                      18
19                                                                                                      19
20                                                                                                      20
21                                                                                                      21
22                                                                                                      22
23                                                                                                      23
24                                                                                                      24
25                                                                                                      25
26                                                                                                      26
27                                                                                                      27
28                                                                                                      28
29                                                                                                      29
30   CYP induction                                                                                      30
31                                                                                                      31
32   CYP induction occurs when a drug or chemical causes an increase in enzyme activity,                32
33   usually via increased gene transcription [68–70]. In many cases, inducers are also hepato-         33
34   toxic. CYP induction can lead to a reduction in efficacy of co-medications and also to an          34
35   increase in reactive metabolite-induced toxicity. CYP induction is therefore a metabolic           35
36   liability in drug therapy and it is highly desirable to develop new drug candidates that are not   36
37   potent CYP inducers.                                                                               37
38      Most commonly, ligand activation of key receptor transcription factors leads to                 38
39   increased transcription. In the human liver, some of these enzymes, but not all, are               39
40   inducible. Human CYP1A, CYP2A, CYP2B, CYP2C, CYP2E and CYP3A enzymes                               40
41   are currently known to be inducible. CYP gene families 2 and 3 have a similar                      41
42   mechanism of gene activation through a ligand-activated nuclear receptor constitutive              42
43   androstane receptor or constitutively active receptor CAR and/or pregnane X receptor               43
44   (PXR). CYP3A4 is the most highly expressed CYP enzyme representing up to 28% of                    44
45   all CYPs and is highly inducible by a wide variety of xenobiotics. CYP3A4 has been                 45
46   implicated in the metabolism of more than 50% of prescribed pharmaceuticals [71].                  46
12                           DESIGNING DRUGS TO AVOID TOXICITY


1    CYP1A genes belong to the Per-Arnt-Sim (PAS) family of transcription factors and                       1
2    require the aliphatic hydrocarbon receptor (AhR). CYP1A2 is also one of the major                      2
3    CYPs in human liver, accounting for approximately 10% of total amount of hepatic                       3
4    CYPs.                                                                                                  4
5      There are four main mechanisms of CYP induction [72]:                                                5
6                                                                                                           6
7    1. PXR upregulates the important CYP3A and 2C enzymes. PXR is referred to as the                       7
8       master regulator of CYP enzymes. The classic substrate for PXR is the antibiotic                    8
9       rifampicin (22). Similarly, the glucocorticoid anti-inflammatory and immunosuppres-                 9
10      sant dexamethasone (23) has been reported to be a substrate [73]. It has been hypoth-               10
11      esized that unwanted activation of the PXR is responsible for approximately 60% of all              11
12      observed drug–drug interactions [74]. Today, many drug companies routinely include                  12
13      the PXR reporter gene assay at the drug discovery stage as part of the selection processes          13
14      of drug candidates for clinical development.                                                        14
15   2. Aliphatic hydrocarbon (Ah) or aryl hydrocarbon receptor (AhR) induces CYP1A                         15
16      enzymes 1 and 2; certain polycyclic aromatic hydrocarbons in the diet and environ-                  16
17      ment induce their own metabolism, for example hydrocarbons in cigarette smoke,                      17
18      charbroiled meats and cruciferous vegetables. 2,3,7,8-Tetrachlorodibenzo-p-dioxin                   18
19      (TCDD) (24) and the related TCDF (25) are the prototypical CYP1A inducers.                          19
20      Tryptophan derivatives, caffeine, eicosanoids and some prostaglandins are also                      20
21      AhR substrates.                                                                                     21
22   3. CAR induces CYP2B and CYP3A enzymes. Typical substrates are barbiturates such as                    22
23      phenobarbital (26).                                                                                 23
24   4. Peroxisome proliferator-activated receptors (PPARs) upregulate CYP4A. Typical exam-                 24
25      ples include the fibrates, PPAR alpha receptor agonists such as clofibrate (27). The                25
26      thiazolidinedione antidiabetic agents such as rosiglitazone (28) act as PPAR gamma                  26
27      agonists.                                                                                           27
28                                                                                                          28
29   Transcription factors such as HNF4a are also involved and there is also significant post-              29
30   translational regulation of protein half-life, especially of CYP2E1. The glucocorticoid                30
31   receptor (GR) and estrogen receptor (ER) may also be involved. Two other nuclear                       31
32   receptors, designated LXR and FXR, which are respectively activated by oxysterols                      32
33   and bile acids, also play a role in liver CYP7A1 induction [75]. Together all of these                 33
34   receptors are able to sense a great variety of xenobiotics and consequently regulate                   34
35   numerous phase I and phase II drug-metabolizing enzymes and drug transporters. In this                 35
36   way they attempt to adjust the body’s metabolic response to the challenges of the                      36
37   chemical environment.                                                                                  37
38                   To avoid toxicity associated with potential CYP induction, it is important to divert   38
39   the structure–activity relationship of interest from that of the nuclear receptor which is             39
40   also being activated. The screening approaches to avoiding CYP induction are                           40
41   reviewed by Pelkonen et al.[75]. It is possible to establish in vitro assays for AhR,                  41
42   CAR, PPAR gamma and PXR, and SAR from these assays may be used to refine a                             42
43   QSAR model. In this way in silico models have been developed for all of these                          43
44   receptors using QSAR and docking approaches, some of which reach up to 80%                             44
45   successful prediction.                                                                                 45
46   [(Fig._1)TD$IG]                                                                                        46
GRAHAM F SMITH                                      13


1                                                                                                   1
2                                                                                                   2
3                                                                                                   3
4                                                                                                   4
5                                                                                                   5
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28                                                                                                  28
29                                                                                                  29
30                                                                                                  30
31                                                                                                  31
32                                                                                                  32
33                                                                                                  33
34                            CARDIOVASCULAR TOXICITY (hERG, ETC.)                                  34
35                                                                                                  35
36   Virtually all cases of extended QT interval are traced to the inward rectifying potassium      36
37   ion channel (IKr) related gene known as hERG (human ether-a-go-go-related gene),               37
38   which encodes the protein Kv 11.1. Inhibition of the cardiac IKr current leads to pro-         38
39   longation of the QT interval and to a risk of lethal ventricular arrhythmia (torsade de        39
40   pointes (TdP)) [76–78]. The electrocardiogram (ECG) traces in Figure 1.1 show the              40
41   prolongation of QT leading to TdP. Once hERG involvement in inherited long QT was              41
42   established, QT-prolonging TdP-prone drugs began to be tested on hERG. This showed             42
43   hERG to be a major contributor to drug-acquired QT prolongation. This phenomenon               43
44   was once considered a trivial finding, in fact IKr was a valid drug target for the class III   44
45   arrhythmic drugs, but more recently QT prolongation has become a major regulatory              45
46                                                                                                  46
14                                         DESIGNING DRUGS TO AVOID TOXICITY
     [(Fig._1)TD$IG]
1                                                                                                                       1
2                                                                                                                       2
3                                                                                                                       3
4                                                                                                                       4
5                                                                                                                       5
6                                                                                                                       6
7                                                                                                                       7
8                                                                                                                       8
9                                                                                                                       9
10                                                                                                                      10
11                                                                                                                      11
12                                                                                                                      12
13                                                                                                                      13
14                                                                                                                      14
15                                                                                                                      15
16                                                                                                                      16
17                                                                                                                      17
18                                                                                                                      18
19                                                                                                                      19
20                                                                                                                      20
21                     Fig. 1.1   A: Normal ECG. B: Long QT syndrome. C: Ventricular arrhythmia (torsade de pointes).   21
22                                                                                                                      22
23                                                                                                                      23
24                                                                                                                      24
25   issue. Since 2005, the FDA has required that all new drug candidates are evaluated to                              25
26   determine the drug’s effect on the QT interval. Other channels which may play a more                               26
27   minor role include Nav1.5 and Ca2+.                                                                                27
28      QT prolongation can routinely lead to a drug being withdrawn from the market or from                            28
29   development as happened in the cases of the antihistamine terfenadine (29) and the gastric                         29
30   prokinetic cisapride (30). Astemizole (31) a long duration antihistamine drug, the anti-                           30
31   psychotic sertindole (32) and the quinolone antibacterial grepafloxacin (33) were also all                         31
32   withdrawn post-launch over concerns about life threatening TdP.                                                    32
33      Today nearly all drug discovery programmes include an early assessment of hERG                                  33
34   liabilities, including an in vitro primary radioligand binding assay in the IKr ion channel                        34
35   [79]. In addition to IKr, early assessment of Nav1.5 and Cav1.2 channels is also being                             35
36   conducted earlier. Functional alternatives to these binding assays are patch clamp and patch                       36
37   express. Apart from an earlier and cheaper alert to hERG toxicity these high-throughput                            37
38   assay data provide excellent data for validating structure–activity relationships and building                     38
39   computational models.                                                                                              39
40      Cavalli et al.[80] was able to build a 3D QSAR model (Figure 1.2) based on                                      40
41   known drugs. This model is often used as a first pass design tool to avoid hERG                                    41
42   activity. The empirically based model has been validated and enhanced by homology                                  42
43   models related to known crystal structures of four other bacterial potassium channels                              43
44   [81–83]. These models have been used successfully in the development of drugs such                                 44
45   as maraviroc (34) to overcome hERG binding issues encountered in the discovery                                     45
46   phase [84].                                                                                                        46
GRAHAM F SMITH                                       15
                         [(Fig._2)TD$IG]
1                                                                                                                                             1
2                                                                                                                                             2
3                                                                                                                                             3
4                                                                                                                                             4
5                                                                                                                                             5
6                                                                                                                                             6
7                                                                                                                                             7
8                                                                                                                                             8
9                                                                                                                                             9
10                                                                                                                                            10
11                                                                                                                                            11
12                                                                                                                                            12
13                                                                                                                                            13
14                                                                                                                                            14
15                                                                                                                                            15
16                                                                                                                                            16
17                                                                                                                                            17
18                                                                                                                                            18
19                                                                   Fig. 1.2   The Cavalli hERG pharmacophore model.                         19
20                                                                                                                                            20
21                                            Workers from Merck showed that bio-isosteres which might improve IKr profile based on           21
22                                         previous pairwise analysis of molecules assayed can be used to computationally point the           22
23                                         way towards reduced hERG affinity [85]. Bell and Bilodeau [86] recently gave a good                23
24                                         overview of medicinal chemistry tricks to avoid hERG SAR. Techniques usually involve               24
25                                         reducing basicity and lipophilicity (Scheme 1.7). The IKr channel seems to have high affinity      25
26                                         for many types of lipophilic bases, therefore adding polar groups, for example alcohols or         26
27                                         ethers, removing hydrophobic groups, reducing Pi-stacking interactions and removing or             27
28                                         modifying aryl rings are all good approaches chemically.[(Fig._1)TD$IG]                            28
29                                                                                                                                            29
30                                                                                                                                            30
31   [(Schem_7)TD$FIG]                                                                                                                        31
32                                                                                                                                            32
33                                                                                                                                            33
34                                                                                                                                            34
35                                                                                                                                            35
36                                                                                                                                            36
37                                                                                                                                            37
38                                                                                                                                            38
39                                                                                                                                            39
40                                                                                                                                            40
41                                                                                                                                            41
42                                                                                                                                            42
43                                                                                                                                            43
44                                                                                                                                            44
45                                                                                                                                            45
46                                                      Scheme 1.7   Simple modifications which often reduce the risk of hERG activity        46
16                        DESIGNING DRUGS TO AVOID TOXICITY


1                                                                                                  1
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23                                                                                                 23
24                                                                                                 24
25                                                                                                 25
26                                                                                                 26
27                                                                                                 27
28                                 GENOTOXICITY/MUTAGENICITY                                       28
29                                                                                                 29
30   Genotoxicity describes a deleterious action on a cell’s genetic material affecting its        30
31   integrity. The term genotoxicity includes DNA reactivity, resulting in mutation, and also     31
32   interaction with various protein targets, for example spindle microtubules, leading to        32
33   numerical chromosome changes or aneuploidy. It is regulatory practice to view DNA-            33
34   reactive effects as having no acceptable threshold (or no-effect level), whereas reaction     34
35   with protein targets might have an acceptable threshold and potential to establish a safety   35
36   margin as is the case for other toxicities. Genotoxic substances are potentially mutagenic    36
37   or carcinogenic. This definition includes both some classes of chemical compounds and         37
38   certain types of radiation.                                                                   38
39      Typical genotoxins such as aromatic amines are believed to cause mutations because they    39
40   are nucleophilic and form strong covalent bonds with DNA, resulting in the formation of       40
41   aromatic amine-DNA adducts and preventing accurate replication. Genotoxins affecting          41
42   sperm and eggs can pass genetic changes to descendants who have never been exposed to         42
43   the genotoxin. As many mutations can contribute to the development of cancer, many            43
44   mutagens are carcinogens. So-called spontaneous mutations are also known to occur due         44
45   to errors in DNA replication, repair and recombination, and the many endogenous products      45
46   of cellular metabolism such as oxygen radicals.                                               46
GRAHAM F SMITH                                       17


1       The international test guidelines require a bacterial mutagenicity test (the Ames test)      1
2    and an in vitro test for chromosome aberrations or for mutation in a mouse lymphoma cell        2
3    line, before the first human clinical trials. An in vivo test for chromosome damage             3
4    (typically a micronucleus test) must be done before phase II clinical trials [87]. Many         4
5    companies also use early versions of these regulatory assays for screening, or some of the      5
6    wide range of relatively high-throughput screening assays available for early detection of      6
7    genotoxicity. The Ames test is a bacterial assay that allows the detection of strong early      7
8    signals of mutagenicity [88–90]. Ames tests use a histidine-free medium with a genet-           8
9    ically engineered strain of bacteria that can only proliferate into colonies after certain      9
10   mutations restore their ability to synthesize histidine. It has been established that the       10
11   predictive power of positive Ames test results for rodent carcinogenicity is high, ranging      11
12   from 60 to 90% depending on the compound set examined. An assay is also used that               12
13   identifies chromosomal damage, either visible as chromosome breaks at metaphase, or as          13
14   micronuclei (chromatin that is left outside the main nucleus and comprises either frag-         14
15   ments of broken chromosomes (clastogenicity), or whole chromosomes, indicating                  15
16   potential for aneuploidy). An in vitro and in vivo chromosomal aberration assay is              16
17   required before first-in-human studies; these studies are often conducted in the presence       17
18   of metabolic activation in order to assess the toxicity of any metabolites which may be         18
19   formed.                                                                                         19
20      Following extensive testing, the validation of structural types leading to mutagenicity is   20
21   well established. The development of the so-called ‘structure alerts’ related to mutage-        21
22   nicity from the 1950s to the current day is well reviewed by Benigni and Bossa [91].            22
23   In general the alkylation of DNA by electrophilic chemicals leads to mutagenicity. The          23
24   other mechanism is via molecules which intercalate with DNA, changing its tertiary              24
25   structure, and interfering with normal DNA function and replication. In this section            25
26   biochemical pathways which explain the reactivity of these groups are elaborated, so            26
27   that they might be more appropriately used and modified by medicinal chemists to reduce         27
28   the risk of mutagenicity.                                                                       28
29                                                                                                   29
30   Electrophiles not requiring metabolic activation                                                30
31                                                                                                   31
32                                                                                                   32
     During the course of in vitro testing in research programmes, certain chemical inter-
33                                                                                                   33
     mediates and mild electrophiles find their way into the screening cascade by design or
34                                                                                                   34
     by accident. Despite some of these being perfectly stable chemicals in buffered
35                                                                                                   35
     solution, it must be noted that the body is perfectly able to find nucleophiles with
36                                                                                                   36
     sufficient potency such as amines and thiols which will unselectively react with
37                                                                                                   37
     these electrophiles. The toxicity of these functional groups will in general be related
38                                                                                                   38
     to their chemical reactivity. Figure 1.3 shows a set of common electrophiles which
39                                                                                                   39
     should be avoided unless targeting a specific drug–protein covalent interaction is the
40                                                                                                   40
     desired goal.
41                                                                                                   41
42                                                                                                   42
43   Alkyl halides and sulphonates                                                                   43
44                                                                                                   44
45   Alkyl halides and sulphonates are susceptible to nucleophilic attack by a cysteine-SH or        45
46   other bio-molecule nucleophiles to form adducts [92]. Their toxicity is directly related to     46
18                                            DESIGNING DRUGS TO AVOID TOXICITY
     [(Fig._3)TD$IG]
1                                                                                                                   1
2                                                                                                                   2
3                                                                                                                   3
4                                                                                                                   4
5                                                                                                                   5
6                                                                                                                   6
7                                                                                                                   7
8                                                                                                                   8
9                                                                                                                   9
10                                                                                                                  10
11                                                                                                                  11
12                                                                                                                  12
13                                                                                                                  13
14                                   Fig. 1.3   Some common electrophiles encountered in medicinal chemistry.       14
15                                                                                                                  15
16                                                                                                                  16
17   their chemical reactivity. Leaving groups beta to an electron-withdrawing group (EWG                           17
18   such as carbonyls, aryl groups, nitriles, etc.) are also of concern due to possible elimi-                     18
19   nation to form a Michael acceptor molecule. Mammalian response to such agents in-                              19
20   volves elevation of activity of phase II detoxifying enzymes [93, 94]. An SN1 mechanism                        20
21                   for the substitution is also possible. For example mono alkyl fluorides are less susceptible   21
22                   to nucleophilic attack, but are likely to be converted via cationic (SN1-like) mechanisms      22
23   where possible.                                                                                                23
24                      Toremifene (Fareston) (35) is an oral anti-estrogen drug for the treatment of metastatic    24
25   breast cancer. There are numerous adverse events and toxicities reported with the use of                       25
26   toremifene as described in the pharmaceutical documentation ring (PDR) entry. However,                         26
27   many of these may be due to its estrogenic activity rather than the presence of an alkyl                       27
28   halide. Many alkyl halides and sulphates have been reported as anticancer agents. Their                        28
29   designed mode of action is alkylation of DNA, and hence they are cytotoxic with many side                      29
30   effects. In these cases, the genetic toxicity is incorporated by design and part of the risk                   30
31   analysis for development and usage.                                                                            31
32   [(Fig._1)TD$IG]                                                                                                32
33                                                                                                                  33
34                                                                                                                  34
35                                                                                                                  35
36                                                                                                                  36
37                                                                                                                  37
38                                                                                                                  38
39                                                                                                                  39
40                                                                                                                  40
41                                                                                                                  41
42                                                                                                                  42
43                                                                                                                  43
44                                                                                                                  44
45                       In addition to mechanisms seen for the other halides, organic iodides can cause hypo-      45
46                     thyroidism, hyperthyroidism, phototoxicity, photosensitivity and skin sensitization.         46
Designing Drugs to Avoid Toxicity
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Designing Drugs to Avoid Toxicity

  • 1. 1 1 2 1 Designing Drugs to Avoid Toxicity 2 3 3 4 4 5 GRAHAM F. SMITH 5 6 6 7 Central Chemistry Team Lead, Merck Research Laboratories Boston, 7 8 33 Avenue Louis Pasteur, Boston, MA 02115, USA 8 9 9 10 10 11 11 12 INTRODUCTION 1 12 13 13 THE SAFETY WINDOW 2 14 14 15 COMMON SAFETY RISKS AND THEIR SAR 2 15 16 Toxicity associated with the liver 2 16 17 Cardiovascular toxicity ( h ERG, ETC.) 13 17 18 Genotoxicity/mutagenicity 16 18 19 Phospholipidosis 39 19 Phototoxicity 40 20 20 Idiosyncratic toxicity 42 21 21 22 CONCLUSIONS 42 22 23 23 24 REFERENCES 43 24 25 25 26 26 27 27 INTRODUCTION 28 28 29 29 Two thousand four data from the Centre for Medicines Research show that toxicity is now 30 30 the leading cause of failure of compounds in clinical development. With the improved 31 31 systemic exposure, which came with better understanding of drug metabolism and phar- 32 32 macokinetics (DMPK), came increased observations of dose-limiting toxicity [1]. The 33 33 leading causes of drug failure are now tied at 30%, with toxicity as likely to be the demise 34 34 of a drug’s development as lack of efficacy, (PK-related attrition now stands at 10%). 35 35 Nevertheless, most safety-related attrition (70%) occurs pre-clinically following candidate 36 36 selection, suggesting that we are still in need of better predictive models of in vivo toxicity. 37 37 Where in vitro assays, or simple in vivo experiments, are predictive of adverse events in 38 38 humans, then these are increasingly carried out earlier in the drug discovery cycle. 39 39 The structure–toxicity relationships for mutagenicity and hepatotoxicity are already well 40 40 established owing to robust in vitro assays which translate well to clinical outcomes. These 41 41 assays have frequently been used to implicate common alerting structures or so-called 42 42 ‘structure alerts’. Identifying structural alerts for toxicity, and high-throughput assays for 43 43 early indicators of toxicity issues in vivo, have become a normal part of early drug discovery. 44 44 Regulatory authorities require that these robust assays be run on all new chemical entities 45 45 before entering first-in-human trials. 46 46 Progress in Medicinal Chemistry – Vol. 50 1 Ó 2011, Elsevier B.V. Edited by G. Lawton and D.R. Witty All rights reserved. DOI: 10.1016/B978-0-12-381290-2.00001-X
  • 2. 2 DESIGNING DRUGS TO AVOID TOXICITY 1 Sometimes, inadvertently, medicinal chemists do introduce toxicophores into drug mole- 1 2 cules. Most often their reactive nature is produced or enhanced in vivo during normal meta- 2 3 bolic processes. Wherever possible this review elaborates the biochemical mechanism attrib- 3 4 uted to this type of toxicity. This allows medicinal chemists to validate the mechanism in their 4 5 own case and also to contextualize their own molecules in terms of their likelihood to undergo 5 6 similar biotransformation. Some successfully marketed drugs are positive in glutathione 6 7 binding assays [2], however, it is well established that the toxicities of known compounds 7 8 with chemically reactive metabolites can be correlated with the generation of hepatic protein 8 9 adducts and/or the detection of stable phase II metabolites such as glutathione conjugates. 9 10 The genotoxic carcinogens have the unifying feature that they are either electrophiles per se 10 11 or can be activated to form electrophilic reactive intermediates. Hard electrophiles generally 11 12 react with hard nucleophiles such as functional groups in DNA and lysine residues in proteins. 12 13 Soft electrophiles react with soft nucleophiles, which include cysteine residues in proteins and 13 14 in glutathione. Glutathione has a concentration of approximately 10 mM in the liver. Free 14 15 radicals can also react with lipids and initiate lipid peroxidative chain reactions [3]. The 15 16 presence of a toxicity risk, or even the confirmation of a metabolic pathway to known toxicity, 16 17 does not preclude a molecule from entering development. The risks are evaluated in the 17 18 context of the body’s highly developed ability to clear toxic molecules from circulation and to 18 19 recover from damage. 19 20 20 21 21 22 THE SAFETY WINDOW 22 23 23 24 All drugs are toxic at some level and so a major challenge in drug discovery is to find a 24 25 margin of efficacy, over adverse events or toxicities, sufficient to provide clinical benefit to 25 26 patients whilst avoiding putting them at unnecessary risk. The therapeutic index (TI) is 26 27 commonly used in the pharmaceutical industry and is the ratio of the no observable adverse 27 28 event level (NOAEL) divided by the human efficacious exposure level (Ceff) or exposure at 28 29 the maximum anticipated human dose (Cmax). 29 30 To determine margin, it is recommended to compare plasma Cmax from animal pharma- 30 31 cology and toxicity studies with (predicted) human pharmacokinetic Cmax data using 31 32 unbound free fraction [4]. Depending on the disease target and nature of toxicity Ctrough 32 33 or area under the curve (AUC) can also be used to determine margins. Ideally these margins 33 34 would be around 10-fold or more over a reversible toxicity outcome which is observed in 34 35 animal testing, but which can also be clinically monitored easily in humans. 35 36 36 37 37 38 COMMON SAFETY RISKS AND THEIR SAR 38 39 39 40 TOXICITY ASSOCIATED WITH THE LIVER 40 41 41 42 CYP inhibition 42 43 43 44 One of the liver’s main physiological roles is the clearance and metabolism of xenobiotics 44 45 into hydrophilic metabolites in order to facilitate their excretion. The liver has an abundance 45 46 of xenobiotic metabolizing enzymes and a high capacity for both phase I and phase II 46
  • 3. GRAHAM F SMITH 3 1 biotransformation. It receives more than 80% of its blood flow from the portal vein into 1 2 which drugs are absorbed from the gastrointestinal tract and therefore liver is often a primary 2 3 target for chemical-induced toxicity. There is the possibility that reactions catalysed by 3 4 cytochrome p450 (CYP) enzymes may generate metabolites that are not only more toxic but 4 5 also more reactive than the original xenobiotic. Drug-induced liver injury is the most 5 6 frequent reason for the withdrawal of an approved drug from the market. Drug-induced 6 7 liver injury has now become the leading cause of liver failure in the Unites States and results 7 8 in at least 2700 deaths per annum [5]. 8 9 Time-dependent inhibition (TDI) of CYPs refers to a change in potency during an in vitro 9 10 incubation or dosing period in vivo, as opposed to a normal reversible inhibitor dose 10 11 response. Inhibition of specific CYP enzymes by a drug can lead to pharmacokinetic 11 12 changes in another drug, or so-called drug–drug interactions [6]. When inhibition affects 12 13 the major metabolic route of another enzyme, and therefore alters (usually increases) 13 14 exposure, this leads to unpredictable exposure levels and often to unacceptable risks to 14 15 patients. In common with other proteins, CYPs are eventually metabolized and replaced if 15 16 they are irreversibly inhibited. CYP enzymes have a turnover of the order of 1–2 days. 16 17 However, TDI is often associated with bioactivation to electrophilic species which have the 17 18 potential for a number of toxic pathways beyond the simple inhibition of CYPs. 18 19 There are several known mechanisms of CYP inhibition: 19 20 20 21 * Competing enzyme substrates affecting the turnover of other drugs. 21 22 * Competitive inhibitors such as quinidine which are not substrates. 22 23 * Haem ligands: non-selective metal chelators such as the imidazole antifungals. 23 24 * Metal inhibitor complex forming drugs such as erythromycin. 24 25 * Inactivation or suicide inhibitors such as tienilic acid. 25 26 26 27 There are good methods of in vitro assessment of CYP inhibition and induction. The 27 28 outcome of this is that common motifs and SAR for these toxic mechanisms exist. 28 29 The following structure classes have well-established mechanisms for CYP inhibition. 29 30 30 31 Alkynes 31 32 Mechanism-based CYP inhibition (MBI) can arise from the covalent attachment of alkyne 32 33 metabolites to the CYP protein. The formation of these adducts is described in Scheme 1.1. 33 34 [(Schem_1)TD$FIG] 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 Scheme 1.1 Oxidation of alkynes to electrophilic species 46
  • 4. 4 DESIGNING DRUGS TO AVOID TOXICITY 1 Reactive metabolites can also be generated which may form covalent adducts with CYP 1 2 proteins or other proteins leading to toxicity [7–10]. Generation of alkyne-CYP intermediate 2 3 (A) can lead directly to the haem-bound product (B). For example, oxirene (C) (derived 3 4 from ring closure of A) can react with a CYP haem nitrogen generating B, and can also react 4 5 with other nucleophilic sites in the CYP protein. Ketene D (formed by the migration of the 5 6 R2 group in intermediate A) can also react with CYP and other proteins to form potentially 6 7 toxic conjugates. 7 8 Gestodene (1) is one of many synthetic steroid drugs, including oral contraceptives, 8 9 which contain an acetylene moiety. This drug was shown to be a mechanism-based inhibitor 9 10 of CYP3A4 and 3A5. A variety of other alkyne-containing steroids have also been evaluated 10 11 and show differing degrees of activity [11]. 17a-Ethynylestradiol (2) is a common compo- 11 12 nent of oral contraceptives and taken by millions of women worldwide. This steroid has 12 13 been shown to be a mechanism-based inhibitor of CYP3A4 in vitro[12]. However, admin- 13 14 istration of 17a-ethynylestradiol to women has been shown to have no impact on either 14 15 intestinal or hepatic CYP3A4 activity [13]. This is most likely to be due to the very low 15 16 doses required to achieve effective contraception, thereby mitigating the potential drug– 16 17 drug interaction risk.[(Fig._1)TD$IG] 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 CYP inhibition is the most common toxicity associated with alkyne-containing 28 29 drugs. Therefore, early investigation of metabolic routes (in vitro and in vivo), coupled 29 30 with reactive metabolite screening, is warranted for medicinal chemists studying 30 31 alkynes. Compounds should be evaluated across a range of CYP enzymes/species 31 32 (with and without pre-incubation) to ensure that the potential for inhibition is fully 32 33 evaluated. 33 34 34 35 Thiophenes 35 36 The thiophene ring is susceptible to hepatic oxidation by CYP and undergoes epoxida- 36 37 tion, followed by epoxide ring opening with nucleophilic biomolecules, to give adducts 37 38 [14–22] (Scheme 1.2). Alternatively the epoxide can open to give a (-thionoenal which 38 39 can also undergo adduct formation. The thiophene sulphur can also undergo oxidation, 39 40 thus activating the ring towards nucleophilic addition of biomolecules. Peroxidase addi- 40 41 tion of chlorine to the thiophene sulphur can also activate the ring towards nucleophilic 41 42 addition. Both the epoxide and the S-oxides have been postulated as reactive intermedi- 42 43 ates. Identification of any of these metabolites therefore implies formation of reactive 43 44 intermediates. 44 45 Tienilic acid (3), a diuretic, is a mechanism-based inhibitor of CYP2C9 and seems 45 46 to inactivate it stoichiometrically. The molecule was launched onto the market and 46
  • 5. GRAHAM F SMITH 5 [(Schem_2)TD$FIG] 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 Scheme 1.2 Metabolism of thiophenes 18 19 19 20 20 21 21 22 22 23 then subsequently withdrawn in 1982 due to a link with hepatitis [23–25]. The non- 23 24 steroidal anti-inflammatory suprofen (4) showed nephrotoxicity in the clinic and is a 24 25 mechanism-based inhibitor of CYP2C9. It was marketed and subsequently withdrawn 25 26 due to cases of acute renal failure [26, 27]. The antiplatelet drug panaldine 26 27 (Ticlopidine) (5) shows TDI of CYP2B6; because it is linked with increased risk of 27 28 agranulocytosis its use has been replaced by clopidogrel (Plavix) (6) [28]. OSI-930 (7) 28 29 was being developed for oncology when it was discovered that the molecule reacted 29 30 via the sulphoxide to form adducts with CYPs 3A4 and 2D6 [29]. In all of these cases 30 31 sulphoxide and glutathione adducts of the thiophene moiety have been detected and 31 32 are postulated to cause the time-dependent inhibition of CYP enzymes and further 32 33 related toxicities. 33 34 One way to reduce or inactivate this pathway is to introduce 2,5-substitution on the 34 35 thiophene ring. Alternatively, the ring can be deactivated towards nucleophilic attack 35 36 through introduction of adjacent functionality. Introduction of an alternative metabolic 36 37 weak point elsewhere in the molecule may also reduce toxic exposure overall. 37 38 Examples of these strategies can be seen in Zyprexa (8) and Plavix (6) [31–35], 38 39 two commercially successful, widely marketed drugs. It appears that a small structural 39 40 change between panaldine (5) and Plavix, which introduces an additional metabolic 40 41 route, reduces thiophene-related hepatotoxicity. Panaldine generates about 20 metabo- 41 42 lites, some of which covalently bind to proteins, while the primary metabolic fate of 42 43 Plavix is hydrolysis of the methyl ester and some glucuronidation of the resulting 43 44 acid. Plavix is dosed at 75 mg QD, while panaldine is dosed at 250 mg BID, so the 44 45 dose difference between panaldine and Plavix may also be a potential mitigating 45 46 factor.[(Fig._1)TD$IG] 46
  • 6. 6 DESIGNING DRUGS TO AVOID TOXICITY 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 [(Fig._1)TD$IG] 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 Furans 38 39 In a similar manner to that for thiophenes, furan toxicity occurs via furan epoxidation 39 40 followed by epoxide ring opening to a g-keto aldehyde which in turn forms adducts with 40 41 biomolecules and induces toxicity [36, 37] (Scheme 1.3). Alternatively, the epoxide can 41 42 ultimately give rise to a lactone which can also form adducts. The epoxide has been 42 43 postulated as the reactive intermediate common to all observed metabolites. Identification 43 44 of any of these metabolites therefore implies formation of the epoxide. 44 45 The clinical development of the 5-lipoxygenase inhibitor L-739,010 (9) was discontinued 45 46 by Merck due to hepatotoxicity; the compound is a mechanism-based inhibitor of CYP3A4 46
  • 7. GRAHAM F SMITH 7 1 [38–40]. Upon incubation with recombinant CYP3A4, a covalently bound adduct of the 1 2 compound was formed, which was identified using mass spectrometry. 2 3 The HIV protease inhibitor L-754,394 (10) showed hepatotoxicity via potent mechanism- 3 4 based inhibition of CYP3A4 and its clinical development was discontinued. It also has been 4 5 shown subsequently for L-756,423 (11) that attachment of benzofuran through the 2- 5 6 position, potentially blocking epoxidation, results in the removal of the furan-associated 6 7 toxicity [41–43]. The fungal pneumotoxin Ipomeanol (12) was also developed for oncology 7 8 and then halted due to hepatotoxicity. Upon activation of Ipomeanol with rabbit CYP4B1 in 8 9 the presence of N-acetyl cysteine and N-acetyl leucine a major product (13) consistent with 9 10 furan epoxide formation was observed and characterized [44–46]. 10 11 It is interesting to note that there are examples of 2,5-disubstituted benzofurans such as 11 12 ranitidine (14) [47] which do not undergo typical furan metabolism. This is probably due to 12 13 their low lipophilicity, low dose and additional substitution. Substituted benzofurans have 13 14 been observed to undergo metabolism. Benzofuran itself undergoes the typical furan 14 15 hydroxylation at the 2-position, possibly through direct hydroxylation and also potentially 15 16 through epoxidation, followed by ring opening to generate 2-hydroxyphenylacetic acid [48]. 16 17 [(Fig._1)TD$IG] 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46
  • 8. 8 DESIGNING DRUGS TO AVOID TOXICITY [(Schem_3)TD$FIG] 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 Scheme 1.3 Furan oxidative metabolism 12 13 13 14 Benzodioxolanes 14 15 The benzodioxolane moiety is associated with mechanism-based irreversible inhibition 15 16 and/or induction of CYPs. In addition some compounds that contain the benzodioxolane 16 17 moiety are associated with hepatotoxicity. CYP-dependent oxidation of the methylene 17 18 leads to both a reactive carbene intermediate (A) which can form irreversible adducts with 18 19 the haem of CYPs (metal inhibitor complex) or the catechol (B) which is an ortho- 19 20 quinone precursor and known toxin through redox chemistry. The mechanism of toxicity 20 21 and CYP inhibition of benzodioxolane compounds has been discussed in detail [49–51] 21 22 (Scheme 1.4). 22 23 Paroxetine (15) is a marketed selective seratonin reuptake inhibitor (SSRI) with a 23 24 known CYP2D6 inhibition profile; it is both a reversible and a time-dependent 24 25 CYP2D6 inhibitor. This results in significantly increased exposure to co-medications 25 26 that are metabolized by CYP2D6. Metabolism of the benzodioxolane group has been 26 27 strongly implicated in the CYP2D6 inhibition shown by paroxetine [52–56] and recent 27 28 studies have shown that the potency of paroxetine as a CYP2D6 inhibitor in vitro 28 29 increases eightfold following pre-incubation [57]. The increase in potency was asso- 29 30 ciated with the formation of a CYP mechanism-based inhibitor complex. 30 31 Administration of paroxetine has been shown to convert some volunteers who are 31 32 extensive CYP2D6 metabolisers to a poor metaboliser phenotype [58]. In addition 32 33 paroxetine inhibits its own metabolism leading to non-linear time-dependent pharma- 33 34 cokinetics. The half-life of paroxetine after single doses of 20 mg/day is 10 h but after 34 35 35 36 36 37 [(Schem_4)TD$FIG] 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 Scheme 1.4 Metabolism of benzodioxolane 46
  • 9. GRAHAM F SMITH 9 1 multiple doses of 20 mg/day this increases to 24 h [59]. While, the fate of the benzo- 1 2 dioxolane is well established in vitro, it is of note that most SSRIs are relatively potent, 2 3 reversible inhibitors of CYP2D6. 3 4 Niperotidine (16) is an H2 antagonist structurally related to ranitidine. Twenty-five cases 4 5 of acute hepatitis (including one death from fulminant hepatitis) associated with niperotidine 5 6 use were reported in Italy between March and August 1995 and the drug was withdrawn 6 7 from the market. The methylenedioxy group of niperotidine (absent in ranitidine) is known 7 8 to undergo metabolism to catechol and quinone metabolites [60, 61]. 8 9 Methylenedioxymethamphetamine (MDMA) (17) has been shown to inhibit CYP2D in a 9 10 time-dependent manor through a mechanism producing a UV absorption spectrum consis- 10 11 tent with a carbene formation [6]. MDMA causes liver damage in humans.[(Fig._1)TD$IG] 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 Fortunately, several viable isosteric replacements are available for the benzodioxo- 29 30 lane structure. Replacement of one of the oxygen atoms with a methylene results in a 30 31 dihydrobenzofuran moiety, which may often show similar pharmacology to a benzo- 31 32 dioxolane. The dihydrobenzofuran system can be rather susceptible to oxidative metab- 32 33 olism, and this should be checked promptly when this group is employed (Scheme 1.5). 33 34 The difluorobenzodioxolane group is a metabolically blocked at the ‘methylene’ car- 34 35 bon, and this does not undergo the same metabolic reactions as the methylenedioxy 35 36 group. The difluorobenzodioxolane group is rather unusual as it is considerably more 36 37 lipophilic than the methylenedioxy group. There are no drugs in the MDDR (molecular 37 38 detection of drug resistance) drug database containing this moiety. The methylene 38 39 carbon may also be blocked with other groups, for example as a dimethylketal, although 39 40 the stability of such groups towards acid-catalysed hydrolysis needs to be carefully 40 41 assessed. 41 42 There are many additional groups that have the potential to mimic a benzodioxolane. 42 43 Owing to their instability towards hydrolysis in dilute aqueous acid, benzoxazoles should 43 44 also be employed with caution, if at all. The benzodioxane ring-expanded system appears 44 45 not to be implicated in the same kinds of toxicity/mechanism-based CYP inhibition as the 45 46 benzodioxolane group. 46
  • 10. 10 DESIGNING DRUGS TO AVOID TOXICITY [(Schem_5)TD$FIG] 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 Scheme 1.5 Some potential benzodioxolane isosteres 21 21 22 22 23 23 24 24 25 Haem Ligands 25 The previous examples of potential liver toxins all form covalent inhibitor complexes with 26 26 CYPs and other proteins. Another commonly encountered class of inhibitors is the haem 27 27 ligands which offer lone pair donation, usually from nitrogen, to stabilize the iron in the 28 28 haem complex. These molecules have an affinity for the active site of CYPs in both the 29 29 oxidized and reduced forms but are reversible inhibitors (Scheme 1.6). Many heterocycles 30 30 31 31 32 [(Schem_6)TD$FIG] 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 Scheme 1.6 Haem ligands 46
  • 11. GRAHAM F SMITH 11 1 frequently used in drug-like molecules are capable of performing this role, for example 1 2 pyridines, azines and azoles [62]. 2 3 The 11-b-hydroxylase inhibitor metyrapone (18) is an inhibitor of cortisol synthesis and 3 4 of CYP3A4 [63, 64]. Metyrapone also causes induction of CYP3A4 synthesis in hepato- 4 5 cytes. The HIV protease inhibitor ritonavir (19) [65, 66] contains two 5-substituted thia- 5 6 zoles. Ritonavir is a potent inhibitor of CYP3A-mediated biotransformations (e.g. nifedi- 6 7 pine oxidation and terfenadine hydroxylation). Ketoconazole (20) is a member of the 7 8 antifungal imidazole drugs. Ketoconazole strongly inhibits CYP3A4 selectively [67]. 8 9 Sulconazole (21), another member of the antifungal imidazole derivatives, strongly inhibits 9 10 most CYPs (1A2, 2A6, 2B6, 2C9, 2C19, 2D6, 2E1, 3A4).[(Fig._1)TD$IG] 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 CYP induction 30 31 31 32 CYP induction occurs when a drug or chemical causes an increase in enzyme activity, 32 33 usually via increased gene transcription [68–70]. In many cases, inducers are also hepato- 33 34 toxic. CYP induction can lead to a reduction in efficacy of co-medications and also to an 34 35 increase in reactive metabolite-induced toxicity. CYP induction is therefore a metabolic 35 36 liability in drug therapy and it is highly desirable to develop new drug candidates that are not 36 37 potent CYP inducers. 37 38 Most commonly, ligand activation of key receptor transcription factors leads to 38 39 increased transcription. In the human liver, some of these enzymes, but not all, are 39 40 inducible. Human CYP1A, CYP2A, CYP2B, CYP2C, CYP2E and CYP3A enzymes 40 41 are currently known to be inducible. CYP gene families 2 and 3 have a similar 41 42 mechanism of gene activation through a ligand-activated nuclear receptor constitutive 42 43 androstane receptor or constitutively active receptor CAR and/or pregnane X receptor 43 44 (PXR). CYP3A4 is the most highly expressed CYP enzyme representing up to 28% of 44 45 all CYPs and is highly inducible by a wide variety of xenobiotics. CYP3A4 has been 45 46 implicated in the metabolism of more than 50% of prescribed pharmaceuticals [71]. 46
  • 12. 12 DESIGNING DRUGS TO AVOID TOXICITY 1 CYP1A genes belong to the Per-Arnt-Sim (PAS) family of transcription factors and 1 2 require the aliphatic hydrocarbon receptor (AhR). CYP1A2 is also one of the major 2 3 CYPs in human liver, accounting for approximately 10% of total amount of hepatic 3 4 CYPs. 4 5 There are four main mechanisms of CYP induction [72]: 5 6 6 7 1. PXR upregulates the important CYP3A and 2C enzymes. PXR is referred to as the 7 8 master regulator of CYP enzymes. The classic substrate for PXR is the antibiotic 8 9 rifampicin (22). Similarly, the glucocorticoid anti-inflammatory and immunosuppres- 9 10 sant dexamethasone (23) has been reported to be a substrate [73]. It has been hypoth- 10 11 esized that unwanted activation of the PXR is responsible for approximately 60% of all 11 12 observed drug–drug interactions [74]. Today, many drug companies routinely include 12 13 the PXR reporter gene assay at the drug discovery stage as part of the selection processes 13 14 of drug candidates for clinical development. 14 15 2. Aliphatic hydrocarbon (Ah) or aryl hydrocarbon receptor (AhR) induces CYP1A 15 16 enzymes 1 and 2; certain polycyclic aromatic hydrocarbons in the diet and environ- 16 17 ment induce their own metabolism, for example hydrocarbons in cigarette smoke, 17 18 charbroiled meats and cruciferous vegetables. 2,3,7,8-Tetrachlorodibenzo-p-dioxin 18 19 (TCDD) (24) and the related TCDF (25) are the prototypical CYP1A inducers. 19 20 Tryptophan derivatives, caffeine, eicosanoids and some prostaglandins are also 20 21 AhR substrates. 21 22 3. CAR induces CYP2B and CYP3A enzymes. Typical substrates are barbiturates such as 22 23 phenobarbital (26). 23 24 4. Peroxisome proliferator-activated receptors (PPARs) upregulate CYP4A. Typical exam- 24 25 ples include the fibrates, PPAR alpha receptor agonists such as clofibrate (27). The 25 26 thiazolidinedione antidiabetic agents such as rosiglitazone (28) act as PPAR gamma 26 27 agonists. 27 28 28 29 Transcription factors such as HNF4a are also involved and there is also significant post- 29 30 translational regulation of protein half-life, especially of CYP2E1. The glucocorticoid 30 31 receptor (GR) and estrogen receptor (ER) may also be involved. Two other nuclear 31 32 receptors, designated LXR and FXR, which are respectively activated by oxysterols 32 33 and bile acids, also play a role in liver CYP7A1 induction [75]. Together all of these 33 34 receptors are able to sense a great variety of xenobiotics and consequently regulate 34 35 numerous phase I and phase II drug-metabolizing enzymes and drug transporters. In this 35 36 way they attempt to adjust the body’s metabolic response to the challenges of the 36 37 chemical environment. 37 38 To avoid toxicity associated with potential CYP induction, it is important to divert 38 39 the structure–activity relationship of interest from that of the nuclear receptor which is 39 40 also being activated. The screening approaches to avoiding CYP induction are 40 41 reviewed by Pelkonen et al.[75]. It is possible to establish in vitro assays for AhR, 41 42 CAR, PPAR gamma and PXR, and SAR from these assays may be used to refine a 42 43 QSAR model. In this way in silico models have been developed for all of these 43 44 receptors using QSAR and docking approaches, some of which reach up to 80% 44 45 successful prediction. 45 46 [(Fig._1)TD$IG] 46
  • 13. GRAHAM F SMITH 13 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 CARDIOVASCULAR TOXICITY (hERG, ETC.) 34 35 35 36 Virtually all cases of extended QT interval are traced to the inward rectifying potassium 36 37 ion channel (IKr) related gene known as hERG (human ether-a-go-go-related gene), 37 38 which encodes the protein Kv 11.1. Inhibition of the cardiac IKr current leads to pro- 38 39 longation of the QT interval and to a risk of lethal ventricular arrhythmia (torsade de 39 40 pointes (TdP)) [76–78]. The electrocardiogram (ECG) traces in Figure 1.1 show the 40 41 prolongation of QT leading to TdP. Once hERG involvement in inherited long QT was 41 42 established, QT-prolonging TdP-prone drugs began to be tested on hERG. This showed 42 43 hERG to be a major contributor to drug-acquired QT prolongation. This phenomenon 43 44 was once considered a trivial finding, in fact IKr was a valid drug target for the class III 44 45 arrhythmic drugs, but more recently QT prolongation has become a major regulatory 45 46 46
  • 14. 14 DESIGNING DRUGS TO AVOID TOXICITY [(Fig._1)TD$IG] 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 Fig. 1.1 A: Normal ECG. B: Long QT syndrome. C: Ventricular arrhythmia (torsade de pointes). 21 22 22 23 23 24 24 25 issue. Since 2005, the FDA has required that all new drug candidates are evaluated to 25 26 determine the drug’s effect on the QT interval. Other channels which may play a more 26 27 minor role include Nav1.5 and Ca2+. 27 28 QT prolongation can routinely lead to a drug being withdrawn from the market or from 28 29 development as happened in the cases of the antihistamine terfenadine (29) and the gastric 29 30 prokinetic cisapride (30). Astemizole (31) a long duration antihistamine drug, the anti- 30 31 psychotic sertindole (32) and the quinolone antibacterial grepafloxacin (33) were also all 31 32 withdrawn post-launch over concerns about life threatening TdP. 32 33 Today nearly all drug discovery programmes include an early assessment of hERG 33 34 liabilities, including an in vitro primary radioligand binding assay in the IKr ion channel 34 35 [79]. In addition to IKr, early assessment of Nav1.5 and Cav1.2 channels is also being 35 36 conducted earlier. Functional alternatives to these binding assays are patch clamp and patch 36 37 express. Apart from an earlier and cheaper alert to hERG toxicity these high-throughput 37 38 assay data provide excellent data for validating structure–activity relationships and building 38 39 computational models. 39 40 Cavalli et al.[80] was able to build a 3D QSAR model (Figure 1.2) based on 40 41 known drugs. This model is often used as a first pass design tool to avoid hERG 41 42 activity. The empirically based model has been validated and enhanced by homology 42 43 models related to known crystal structures of four other bacterial potassium channels 43 44 [81–83]. These models have been used successfully in the development of drugs such 44 45 as maraviroc (34) to overcome hERG binding issues encountered in the discovery 45 46 phase [84]. 46
  • 15. GRAHAM F SMITH 15 [(Fig._2)TD$IG] 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 Fig. 1.2 The Cavalli hERG pharmacophore model. 19 20 20 21 Workers from Merck showed that bio-isosteres which might improve IKr profile based on 21 22 previous pairwise analysis of molecules assayed can be used to computationally point the 22 23 way towards reduced hERG affinity [85]. Bell and Bilodeau [86] recently gave a good 23 24 overview of medicinal chemistry tricks to avoid hERG SAR. Techniques usually involve 24 25 reducing basicity and lipophilicity (Scheme 1.7). The IKr channel seems to have high affinity 25 26 for many types of lipophilic bases, therefore adding polar groups, for example alcohols or 26 27 ethers, removing hydrophobic groups, reducing Pi-stacking interactions and removing or 27 28 modifying aryl rings are all good approaches chemically.[(Fig._1)TD$IG] 28 29 29 30 30 31 [(Schem_7)TD$FIG] 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 Scheme 1.7 Simple modifications which often reduce the risk of hERG activity 46
  • 16. 16 DESIGNING DRUGS TO AVOID TOXICITY 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 GENOTOXICITY/MUTAGENICITY 28 29 29 30 Genotoxicity describes a deleterious action on a cell’s genetic material affecting its 30 31 integrity. The term genotoxicity includes DNA reactivity, resulting in mutation, and also 31 32 interaction with various protein targets, for example spindle microtubules, leading to 32 33 numerical chromosome changes or aneuploidy. It is regulatory practice to view DNA- 33 34 reactive effects as having no acceptable threshold (or no-effect level), whereas reaction 34 35 with protein targets might have an acceptable threshold and potential to establish a safety 35 36 margin as is the case for other toxicities. Genotoxic substances are potentially mutagenic 36 37 or carcinogenic. This definition includes both some classes of chemical compounds and 37 38 certain types of radiation. 38 39 Typical genotoxins such as aromatic amines are believed to cause mutations because they 39 40 are nucleophilic and form strong covalent bonds with DNA, resulting in the formation of 40 41 aromatic amine-DNA adducts and preventing accurate replication. Genotoxins affecting 41 42 sperm and eggs can pass genetic changes to descendants who have never been exposed to 42 43 the genotoxin. As many mutations can contribute to the development of cancer, many 43 44 mutagens are carcinogens. So-called spontaneous mutations are also known to occur due 44 45 to errors in DNA replication, repair and recombination, and the many endogenous products 45 46 of cellular metabolism such as oxygen radicals. 46
  • 17. GRAHAM F SMITH 17 1 The international test guidelines require a bacterial mutagenicity test (the Ames test) 1 2 and an in vitro test for chromosome aberrations or for mutation in a mouse lymphoma cell 2 3 line, before the first human clinical trials. An in vivo test for chromosome damage 3 4 (typically a micronucleus test) must be done before phase II clinical trials [87]. Many 4 5 companies also use early versions of these regulatory assays for screening, or some of the 5 6 wide range of relatively high-throughput screening assays available for early detection of 6 7 genotoxicity. The Ames test is a bacterial assay that allows the detection of strong early 7 8 signals of mutagenicity [88–90]. Ames tests use a histidine-free medium with a genet- 8 9 ically engineered strain of bacteria that can only proliferate into colonies after certain 9 10 mutations restore their ability to synthesize histidine. It has been established that the 10 11 predictive power of positive Ames test results for rodent carcinogenicity is high, ranging 11 12 from 60 to 90% depending on the compound set examined. An assay is also used that 12 13 identifies chromosomal damage, either visible as chromosome breaks at metaphase, or as 13 14 micronuclei (chromatin that is left outside the main nucleus and comprises either frag- 14 15 ments of broken chromosomes (clastogenicity), or whole chromosomes, indicating 15 16 potential for aneuploidy). An in vitro and in vivo chromosomal aberration assay is 16 17 required before first-in-human studies; these studies are often conducted in the presence 17 18 of metabolic activation in order to assess the toxicity of any metabolites which may be 18 19 formed. 19 20 Following extensive testing, the validation of structural types leading to mutagenicity is 20 21 well established. The development of the so-called ‘structure alerts’ related to mutage- 21 22 nicity from the 1950s to the current day is well reviewed by Benigni and Bossa [91]. 22 23 In general the alkylation of DNA by electrophilic chemicals leads to mutagenicity. The 23 24 other mechanism is via molecules which intercalate with DNA, changing its tertiary 24 25 structure, and interfering with normal DNA function and replication. In this section 25 26 biochemical pathways which explain the reactivity of these groups are elaborated, so 26 27 that they might be more appropriately used and modified by medicinal chemists to reduce 27 28 the risk of mutagenicity. 28 29 29 30 Electrophiles not requiring metabolic activation 30 31 31 32 32 During the course of in vitro testing in research programmes, certain chemical inter- 33 33 mediates and mild electrophiles find their way into the screening cascade by design or 34 34 by accident. Despite some of these being perfectly stable chemicals in buffered 35 35 solution, it must be noted that the body is perfectly able to find nucleophiles with 36 36 sufficient potency such as amines and thiols which will unselectively react with 37 37 these electrophiles. The toxicity of these functional groups will in general be related 38 38 to their chemical reactivity. Figure 1.3 shows a set of common electrophiles which 39 39 should be avoided unless targeting a specific drug–protein covalent interaction is the 40 40 desired goal. 41 41 42 42 43 Alkyl halides and sulphonates 43 44 44 45 Alkyl halides and sulphonates are susceptible to nucleophilic attack by a cysteine-SH or 45 46 other bio-molecule nucleophiles to form adducts [92]. Their toxicity is directly related to 46
  • 18. 18 DESIGNING DRUGS TO AVOID TOXICITY [(Fig._3)TD$IG] 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 Fig. 1.3 Some common electrophiles encountered in medicinal chemistry. 14 15 15 16 16 17 their chemical reactivity. Leaving groups beta to an electron-withdrawing group (EWG 17 18 such as carbonyls, aryl groups, nitriles, etc.) are also of concern due to possible elimi- 18 19 nation to form a Michael acceptor molecule. Mammalian response to such agents in- 19 20 volves elevation of activity of phase II detoxifying enzymes [93, 94]. An SN1 mechanism 20 21 for the substitution is also possible. For example mono alkyl fluorides are less susceptible 21 22 to nucleophilic attack, but are likely to be converted via cationic (SN1-like) mechanisms 22 23 where possible. 23 24 Toremifene (Fareston) (35) is an oral anti-estrogen drug for the treatment of metastatic 24 25 breast cancer. There are numerous adverse events and toxicities reported with the use of 25 26 toremifene as described in the pharmaceutical documentation ring (PDR) entry. However, 26 27 many of these may be due to its estrogenic activity rather than the presence of an alkyl 27 28 halide. Many alkyl halides and sulphates have been reported as anticancer agents. Their 28 29 designed mode of action is alkylation of DNA, and hence they are cytotoxic with many side 29 30 effects. In these cases, the genetic toxicity is incorporated by design and part of the risk 30 31 analysis for development and usage. 31 32 [(Fig._1)TD$IG] 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 In addition to mechanisms seen for the other halides, organic iodides can cause hypo- 45 46 thyroidism, hyperthyroidism, phototoxicity, photosensitivity and skin sensitization. 46