Polypharmacology â Foe or Friend?

Perspective pubs.acs.org/jmc

Polypharmacology − Foe or Friend? Jens-Uwe Peters* F. Hoffmann-La Roche Ltd., pRED, Pharma Research and Early Development, Discovery Chemistry, CH-4070 Basel, Switzerland ABSTRACT: Polypharmacology describes the activity of compounds at multiple targets. Current research focuses on two aspects of polypharmacology: (1) unintended polypharmacology can lead to adverse effects; (2) polypharmacology across several disease-relevant targets can improve therapeutic efficacy, prevent drug resistance, or reduce therapeutic-target-related adverse effects. This perspective reviews these interconnected aspects of polypharmacology. The first part discusses the relevance of polypharmacology for the safety of drugs, the mitigation of safety risks, and methods to identify polypharmacological compounds early in the drug discovery process. The second part discusses the advantages of polypharmacology in the treatment of multigenic diseases and infections, and opportunities for drug discovery and drug repurposing. This perspective aims to provide a balanced view on polypharmacology, which can compromise the safety of drugs, but can also confer superior efficacy.

1. INTRODUCTION

correct a pathological imbalance. Indeed, some multikinase inhibitors and antipsychotics bind to more than 20 targets. Also, multitarget drugs can be safer than single-target drugs. For reasons explained below, multitarget drugs can be less liable to adverse reactions, which originate from a therapeutic target. For instance, tapentadol is a powerful analgesic combining μopioid receptor agonism with norepinephrine reuptake inhibition; this dual-acting compound is safer and has fewer side-effects than classical opioids at equianalgesic doses. Thus, while activity at nontherapeutic targets can lead to toxicity, activity at multiple therapeutic targets can result in superior efficacy or safety. Unintended polypharmacology must therefore be avoided, whereas targeted polypharmacology holds opportunities for the discovery of better drugs. This perspective discusses both of these aspects.

The pharmaceutical industry withdrew a large number of drugs during the years 1996−2001. Some of these drugs interacted with nontherapeutic targets and thereby caused severe sideeffects. For instance, the widely used anorexigen, fenfluramine, led to pulmonary hypertension and heart valve damage, because its metabolite activated the serotonin 5-HT2B receptor.1−3 When fenfluramine was withdrawn in 1997, many patients were already permanently injured, and the case sparked a public debate on drug safety and vigilance. At about the same time, advances in molecular biology allowed the set up of “safety panels”. New drug candidates were now screened against dozens of safety-relevant targets,4 such as the 5-HT2B receptor. Today, most researchers pursue high affinity for a single therapeutic target combined with high selectivity, believing that this will maximize efficacy, will minimize side-effects, and will give their drug a therapeutic window. However, this view has been challenged in recent years.5−14 Polypharmacological drugs can be unprecedentedly efficacious, and they can be developed in a modern drug discovery setting. Prominent examples are the multikinase inhibitors, which have been entering the clinic since 2005, and have been providing new hope for the treatment of previously refractory cancers. The efficacy of these drugs results from their disruption of multiple processes which sustain cancer growth, such as proliferation, angiogenesis, and recruitment of surrounding tissues.15 Polypharmacology also benefits other complex diseases, such as psychiatric diseases.16,17 For example, all marketed antipsychotics are polypharmacological, including recently approved drugs. Modern concepts explain the efficacy of these drugs by their modulation of a network of diseaserelevant targets.5,18 If individual targets are redundant in such a network, then drugs must interact with multiple targets to © XXXX American Chemical Society

2. NEW TRENDS IN SAFETY PANEL SCREENING AND PROMISCUITY PREDICTION 2.1. Why Safety Panel Screening? Many adverse drug reactions (ADRs) stem from a drug’s unintended activity at an “antitarget”;19 some antitargets are frequently encountered and well-known (Table 1).20 Animal toxicity studies21,22 do not reliably predict antitarget-related ADRs in humans due to species differences. For example, rodent models poorly predict cardiovascular ADRs in humans, because of different contributions of ion channels in the cardiovascular system of humans and rodents.23 The ICH S7A guidelines for safety studies therefore recommend antitarget screening  “ligand binding or enzyme assay data suggesting a potential for adverse effects”.24,25 In addition to protecting volunteers in clinical trials, antitarget screening also reduces preclinical and clinical Received: June 11, 2013

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dx.doi.org/10.1021/jm400856t | J. Med. Chem. XXXX, XXX, XXX−XXX

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which were part of the screening panels in at least three of the four companies, and proposed these 44 targets as a “minimal panel” for early safety screening.34 These 44 targets have a high relevance for safety and attract high hit rates. Early panels should combine predictivity for ADRs with sufficient throughput and should therefore only include targets of high importance, that is, frequently hit targets with a clear relevance for safety. Targets with no clear links to ADRs should be omitted. For example, the melatonin MT3 receptor and some serotonergic receptors (5-HT4−7) attract high hit rates but are not known to be involved in ADRs.20 The serotonergic 5-HT5A receptor may be a case in point: ligands of this receptor do not produce any adverse behavioral or physiological responses,35 and knockout animals show a very mild phenotype.36 Also, targets with low hit rates can be omitted: proteases and kinases are often safety-relevant but attract hit rates of 2.5 hit between 7 and 20 off-targets.50 However, the degree of promiscuity varies greatly between compounds of similar lipophilicity (Figure 1).37 Thus, lipophilicity alone is generally not a useful parameter to predict or to optimize the promiscuity of individual compounds, even though this has been successful in some instances.51 Rather, these studies affirm the importance of low lipophilicity as a key goal for lead optimization and as a criterion for the selection of hit and lead series.52−55 Basic compounds with a pKa[B] > 6 are (partly) protonated at assay and physiological pH. Such compounds are frequently promiscuous in safety screens (Figure 1),37,40 especially if they contain two or more aromatic rings in the vicinity of the basic center. The promiscuity of these compounds stems from their interaction with a limited set of targets, such as aminergic GPCRs, cationic ion channels, opioid receptors, and biogenic amine transporters.37 Safety panels contain usually a high percentage of such targets (∼15−25%). Thus, the connection of basicity with promiscuity could be interpreted as an artifact, due to a bias of safety panels toward “aminergic” targets. However, “aminergic” activity is also the dominant source of polypharmacology of clinically used drugs, as suggested by publications on drug-target network analyses, in-silico profiling, and database mining.56−59 On average, drugs with activity for an aminergic target bind to six other GPCRs.60,61 In safety panels, some aminergic targets attract a surprisingly high hit rate from compounds with a basic center. For example, the serotonergic 5-HT2B receptor binds more than one-third of the basic compounds in the BioPrint data set with sub-micromolar affinity, and even more than half of all basic compounds with

Figure 1. Dependence of pharmacological promiscuity (hit rate) on ionization state and lipophilicity in the BioPrint data set. The majority of promiscuous compounds are bases, which carry a positive charge under assay conditions. Compounds with a ClogP > 2 tend to be more promiscuous. The “hit rate” of a compound is the percentage of targets, to which this compound binds with sub-micromolar affinity (cytochrome P450 [CYP] enzymes are excluded). For instance, the topmost blue data point represents a compound, which “hits” 19% of the BioPrint targets (25 out of 132). Reproduced with permission from Drug Discovery Today 2012, 17(7−8), 325−335. Copyright 2012 Elsevier. C



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Chart 1. The “Heteroaryl-NH-aryl” Motif Is Predictive of Kinase Activity75

two or more aromatic rings. Numerous other aminergic targets bind more than every fifth basic compound. Consequently, “aminergic” interactions dominate safety-screening data sets. For instance, even though only 12% of the data points in the BioPrint data set represent basic compounds tested at aminergic and similar targets, these data points account for 70% of the sub-micromolar “hits”. (“Basic” means here the presence of a basic center, which is protonated at pH 7.)37 Many studies investigated the dependence of promiscuity on MW. The results are contradictory: binned MW correlates inversely with promiscuity in a large set of Pfizer highthroughput screening (HTS) data,48 whereas Novartis safety panel data62 and Roche HTS data47 show the opposite trend. The BioPrint data set shows a more complex relationship,37,52 and ligands of proteins in the Protein Data Bank (PDB) show no correlation.63 High potency promiscuity increases with MW among ChEMBL database compounds,6 but not within a small set of Roche project compounds.40 Altogether, MW does not seem to be a useful predictor of promiscuity, at least not in the druglike MW range (200−600). The influence of other parameters on promiscuity is often predictable from their relationship with lipophilicity. For example, compounds with a low polar surface area tend to be more lipophilic and also tend to be more promiscuous.64 The same is true for compounds with few hydrogen bond donors and acceptors or for compounds with multiple aromatic rings.37,52,65 Finally, compounds tend to be less promiscuous if they are of high complexity, of little flexibility, or decorated with many side chains,63,66−68 probably because such compounds require a high shape complementarity from a protein’s binding site.69,70 An important cause of promiscuity is the binding site similarity within some target families and also between unrelated proteins.63 Aminergic GPCRs and kinases are the two largest target families associated with frequent promiscuity; they are also highly safety-relevant. Certain structural features are an alert for promiscuity within these target families. The prototypical pharmacophore of aminergic GPCRs is a secondary or tertiary amine with a pKa[B] > 6, which is connected by a 2−5-atom linker to an aromatic ring.71,72 Compounds with such a pharmacophore are often promiscuous. Some more defined structural motifs lead almost invariably to high promiscuity across aminergic and related targets, for instance, the tricyclic motif in older antidepressants and many antipsychotic drugs. Similarly, the trained eye recognizes certain patterns of hydrogen bond donors, acceptors, and aromaticity as potential kinase hinge-binding motifs.73 Hinge-binders inhibit often several kinases, and some show high promiscuity across the kinome.74 The “2−0” rule helps to identify compounds with an increased likelihood of kinase activity by counting typical structural fragments: more than two heteroaromatic nitrogens (N or NH), or any (more than 0) aromatic NH substituents and nitriles. Much more predictive is the presence of a bisarylaniline motif, in particular, of a “heteroaryl-NH-aryl” motif as defined in Chart 1; such compounds often inhibit a wide variety of kinases.75 The promiscuity potential of lead series with aminergic or hinge-binding motifs should be assessed early in the drug discovery process by screening against six diverse aminergic targets,37 or six kinases,76 respectively. Several functionalities are associated with promiscuity across smaller target families. For instance, a large structural variety of drugs with a primary sulfonamide bind to carbonic

anhydrases77 and many hydroxamic acids are inhibitors of matrix metalloproteases.78 Very recently, a computational method for predicting offtarget activities has been receiving much attention: the similarity ensemble approach (SEA). This method predicts the binding of a compound to a target by the compound’s noncoincidental similarity to known ligands of this target. A comparison with ligands of many targets generates a pharmacological profile. In a profiling study of 656 marketed drugs at 73 “side-effect” targets, this method predicted numerous nonobvious interactions, half of which were confirmed either by database mining, or by in vitro pharmacological measurements. For example, it was predicted and confirmed that the synthetic estrogen chlorotriasine inhibits cyclooxygenase-1 (COX-1). This provided an explanation for a side effect of chlorotriasine, abdominal pain.79−81 Other in silico tools flag compounds either for general propensity toward promiscuity,62,82−84 or for potential activity at specific antitargets.85−87 These tools have not (yet) found widespread use. 2.4. Pharmacological Promiscuity − Prevalence, and Significance for Toxicity and Attrition. Many established drugs are not selective,88 and a significant percentage of compounds in large databases bind to more than one target:89 33% of the compounds in the BioPrint database,50 35% in a large proprietary database,90 38% in the ChEMBL database,91 50% in the PubChem database,92 and 52% of oral drugs in the ChEMBL database6 (target binding is defined differently in the cited publications). The Psychoactive Drug Screening Program (PDSP) database contains an even larger number of promiscuous compounds.16 These databases cover only a fraction of the estimated 3000 druggable targets of the human genome,93 so the actual prevalence of promiscuity is likely higher than the indicated 33−52%.61,88,94 Beta-blockers and selective serotonin reuptake inhibitors (SSRIs) illustrate the promiscuity of established drugs: betablockers are rarely selective for their principal target, the adrenergic β1-receptor, but bind to up to 20 out of 129 BioPrint targets with submicromolar activity (Figure 2).50 Carvedilol has a particularly rich pharmacology, which is responsible for its unique therapeutic profile: in contrast to other beta-blockers, carvedilol treats congestive heart failure,95 and has been described as a “powerful cardioprotector”.96 Similarly, SSRI antidepressants target the serotonin reuptake transporter as their main mechanism of action, but weak off-target activities are common. For instance, fluoxetine binds to 7 out of 129 BioPrint targets with submicromolar activity.50 Some of these off-target activities may contribute to the efficacy of fluoxetine and other SSRIs. For instance, the sigma receptor is a depression target in its own right,97,98 and paroxetine, fluoxetine, citalopram, escitalopram, fluvoxamine and sertraline bind to the sigma receptor with low micromolar or submicromolar activity.50 D



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candidates if they have safety-relevant off-target activities; such compounds may not be included in the Astra Zeneca set. Also, severe side-effects of marketed drugs have been traced back to off-target activities. For example, antipsychotics cause severe metabolic adverse effects, such as weight gain, hyperprolactinaemia, and diabetes, by antagonism of the histamine H1, the serotonin 5-HT2C, and the muscarinic receptors.17,105 Antagonism at further antitargets is responsible for the CNS-related and cardiovascular side-effects of antipsychotics, such as movement disturbances (extrapyramidal symptoms), sedation, heart rhythm changes (QT prolongation), and orthostatic hypotension (“dizzy spells”, fainting when standing up).106 Thus, promiscuity is not uncommon among druglike compounds and does not necessarily translate into toxicity. However, numerous targets are linked to adverse effects. A compound’s safety potential should therefore be assessed by a careful interpretation of its secondary pharmacology.

Despite this prevalence of promiscuity, only a quarter of drug withdrawals99−101 since 1980 can be traced back to unintended pharmacological activities (mainly hERG and 5-HT2B activities, Figure 3). Other mechanistic reasons seem equally or more

3. IS THERE A CASE FOR POLYPHARMACOLOGICAL DRUG DISCOVERY? 3.1. Multigenic and Infectious Diseases Benefit from Polypharmacological Treatment. Over the last 20 years, most drug discovery efforts were aimed at single-target compounds. However, not all diseases succumb to this “one disease−one target” approach. For instance, no selective antipsychotic has reached the market in a 60-year quest for better drugs.107 Rather, all established antipsychotics bind to multiple GPCRs and ion channels, and their polypharmacological profile underlies their antipsychotic efficacy, even though the dopamine D2 and serotonin 5-HT2A receptors are recognized as principal targets.16,108−110 The antipsychotic gold-standard, clozapine, is a weak D2 receptor antagonist (Ki > 100 nM) but has an exceptionally rich polypharmacology.111 Systems biology explains the efficacy of polypharmacological drugs by their modulation of networks of targets.112 Such networks have evolved to be robust to perturbation,113 and blockade of a single target in such a network has little effect  it is compensated for by redundant pathways.114,115 In yeast, the individual blockade of 85−90% of targets does not produce any observable effects, and knockout studies in mice suggest that only 10% of all druggable genes may be of value as single therapeutic targets.5 Thus, a drug should often modulate a pharmacological network, rather than block or activate a single target. Multikinase inhibitors for the therapy of tumors illustrate this concept.15,116 Tumors and their surrounding tissue exchange several growth factors and thereby mutually stimulate angiogenesis and tumor growth (Figure 4). Tumors secrete vascular endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF), which trigger angiogenesis from endothelial cells and pericytes. PDGF also activates fibroblasts. Activated fibroblasts, in turn, secrete other growth factors and thereby stimulate the tumor to proliferate; the growing tumor is sustained by angiogenesis. Activated fibroblasts also secrete enzymes, which degrade the extracellular matrix and thereby open room for the growing tumor, and contribute to the escape of metastatic cells. Tumors may additionally release cytokines, which attract leukocytes; leukocytes also secrete growth factors and matrix-degrading enzymes. Multikinase anticancer drugs disrupt several of these signaling processes, either by inhibiting receptor kinases or by inhibiting downstream intracellular signaling.15,117 For instance, the multikinase inhibitor suniti-

Figure 3. Mechanistic reasons for drug withdrawals since 1980. Withdrawn drugs were classified by the presumed mechanism of their main adverse effects: (a) hERG blockade: astemizole, cisapride, grepafloxacin, levomethadyl, terfenadine, terodiline, thioridazine; (b) serotonin 5-HT2B receptor agonism: benfluorex, dexfenfluramine, fenfluramine, pergolide; (c) muscarinic M2 receptor antagonism: rapacuronium; (d) CYP interaction: mibefradil; (e) therapeutic-target related: alosetron, cerivastatin, encainide, etretinate, flosequinan, hydromorphone extended-release (Palladone), methaqualone, phenylpropanolamine, rimonabant, rofecoxib, rosiglitazone, valdecoxib; (f) reactive metabolite formation, bile salt export pump (BSEP) inhibition, or mitochondrial toxicity: alpidem, amineptine, benoxaprofen, benzbromarone, bromfenac, chlormezanone, levamisole, lumiracoxib, nefazodone, nomifensine, pemoline, phenacetin, remoxipiride, sitaxentan, suprofen, temafloxacin, ticrynafen, tolcapone, tolrestat, troglitazone, trovafloxacin, ximelagatran, zimelidine, zomepirac; (g) unknown: gatifloxacin, sibutramine (likely therapeutic target related), tegaserod.

important: a second quarter of withdrawals is linked to adverse effects mediated through the drug’s therapeutic target. Almost half of all withdrawals are likely due to reactive metabolite induced toxicity, bile salt export pump (BSEP) inhibition, and mitochondrial toxicity, which occur in combination for some withdrawn drugs (for instance, the hepatotoxicity of troglitazone has been attributed to all three mechanisms).102,103 Also, promiscuity did not increase the likelihood for adverse effects in a set of 87 development candidates from Astra Zeneca: compounds terminated for safety findings in preclinical or phase I studies had a similar prevalence of promiscuity, as compounds terminated for other reasons, such as portfolio decisions.104 However, off-target activities must not be disregarded as an important cause of toxicity and attrition, and the above discussion should be seen in perspective: drugs will never reach the market, and will thus not contribute to withdrawals, if their off-target activities cause acute, nonidiosyncratic toxicity. Similarly, compounds will not be selected as development E



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Figure 4. Tumors and their surrounding tissue exchange growth factors and cytokines and thereby stimulate angiogenesis and tumor growth. The receptor kinases of these growth factors are targets of multikinase inhibiting anticancer drugs. (Reproduced with permission from Polypharmacology in Drug Discovery; Peters, J.-U., Ed.; Wiley, New York, 2012; the picture is courtesy of Annalisa Petrelli, University of Turin).

Table 2. Recently Approved Multi-Kinase Inhibitors as Anticancer Drugs drug

first approval

targets

FDA approval for (status April 2013)

sorafenib

2005

B-Raf, vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR), c-Kit, Fms-like tyrosine kinase 3 (Flt-3), RET VEGFR, PDFGR, c-Kit, Flt-3, RET, colony stimulating factor 1 receptor (CSF1R)

sunitinib

2006

dasatinib

2006

BCR/ABL, Src, c-Kit, ephrin receptors

lapatinib

2007

ErbB1, ErbB2, epidermal growth factor receptor (EGFR)

pazopanib

2009

VEGFR, PDGFR, c-Kit

vandetanib

2011

EGFR, VEGFR, RET, BRK, TIE2, Src, ephrin receptors

crizotinib

2011

ALK, Ros-1, hepatocyte growth factor receptor (HGFR)

axitinib

2012

VEGFR, PDGFR, c-Kit

bosutinib

2012

BCR/ABL, Src

regorafenib

2012

VEGFR, PDGFR, fibroblast growth factor receptor (FGFR), TIE-2, B-Raf, c-Kit, RET

cabozantinib ponatinib

2012 2012

RET, MET, VEGFR, c-Kit, Flt-3 BCR/ABL, c-Kit, RET, Flt-3

nib118 blocks the receptor kinases of many of the abovementioned growth factors and thereby prevents angiogenesis, tumor proliferation, and malignancy (compare targets in Figure 4 and Table 2). Polypharmacological anticancer drugs are also believed to prevent drug resistance.117,119 Drug resistance to a single-target kinase inhibitor can emerge from several mechanisms, such as mutations or up-regulation of the targeted kinase, or other kinases in parallel or downstream pathways. Multikinase inhibitors can block multiple targets in parallel signaling pathways and thereby prevent drug resistance due to mutations or expression changes.

liver cancer kidney cancer kidney cancer gastrointestinal stromal tumors (GIST) pancreatic neuroendocrine tumors chronic cyelogenous leukemia (Philadelphia chromosome positive) hormone-positive and human epidermal growth factor receptor 2 (HER2) positive advanced breast cancer advanced renal cell carcinoma advanced soft tissue sarcoma unresectable, locally advanced, or metastatic medullary thyroid cancer. locally advanced or metastatic nonsmall cell lung cancer (anaplastic lymphoma kinase-positive) advanced renal cell carcinoma after failure of prior systemic therapy chronic myelogenous leukemia (Philadelphia chromosome positive) advanced gastrointestinal stromal tumors (GIST) previously treated metastatic colorectal cancer progressive, metastatic medullary thyroid cancer chronic, accelerated or blast-phase chronic myeloid leukemia

Multitarget treatments also prevent rapid drug resistance in infectious diseases.120−122 Nearly all systemically efficacious antibiotics bind to multiple targets, or to targets encoded by multiple genes, so that single mutations do not lead to drug resistance. For example, β-lactam antibiotics bind to the target family of penicillin-binding proteins; several of such proteins are present in every bacterium. Physicians apply fluoroquinolone antibiotics at “mutation prevention concentrations”, at which bacterial gyrase and topoisomerase IV are dually inhibited, even though the inhibition of only one enzyme would be sufficient to stop bacterial growth. On the other hand, single-target antibiotics rapidly select resistance mutations and are only used in combination, or as topical agents. Interestingly, F



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target-related side-effects (Figure 3). Polypharmacological drugs may be less liable for such side-effects, because the therapeutic effects of multiple modes of action are often synergistic, whereas the adverse effects are not. For instance, a combination of antihypertensives with different modes of action leads to an improved therapeutic effect, without an equal exacerbation of side-effects.138 This concept of “selective synergy” 145,146 may be particularly obvious when the therapeutic targets are expressed together only in the diseased tissue or targeted cell but not in the tissue that may be affected by side-effects related to the therapeutic targets. For instance, glucocorticoids are efficacious anti-inflammatory drugs, because they activate the glucocorticoid receptor in lymphocytes and thereby suppress inflammatory signaling. Inflammatory signaling is also suppressed by an activation of the lymphocyte’s βadrenergic receptors by norepinephrine (NE). NE reuptake inhibitors target this second, complementary pathway by increasing extracellular levels of NE. The anti-inflammatory effects of glucocorticoid receptor activation and NE reuptake inhibition are synergistic. On the other hand, chronic glucocorticoid treatment causes severe side-effects, for example, hyperglycemia, via glucocorticoid receptors in the liver and the pituitary gland. NE reuptake inhibitors do not increase these side-effects because those tissues express fewer β-adrenergic receptors. Thus, NE reuptake inhibitors, such as nortriptyline, improve the therapeutic effect of glucocorticoids, such as prednisolone, but do not exacerbate the side-effects.145 A notable example of side-effect reduction by multitargeting is the analgesic, tapentadol, which was designed as a safer alternative to the classical opioids.147 Opioids such as morphine exert a strong analgesic effect through μ-opioid receptor agonism but are used only for the treatment of the most severe pain. This limited use is due to therapeutic-target-related sideeffects: dependence, nausea, constipation, and respiratory depression. Also, because of these side-effects, failure to reach full efficacy cannot be overcome by dose escalation. Physicians found that NE reuptake inhibitors increase the efficacy of opioids in such cases. On the basis of this observation, Grünenthal researchers designed tapentadol as a relatively weak, dual-acting μ-receptor agonist/NE reuptake inhibitor. Tapentadol turned out to have a much more benign side-effect profile than morphine at equianalgesic doses, especially with respect to emetic potential and respiratory depression, and the development of tolerance is delayed. Many current research programs aim for multitarget antidepressants with reduced side-effects.127,128 While especially the SSRI antidepressants are exceptionally safe drugs, they have unpleasant effects, which limit patient compliance and contribute to a high discontinuation rate: sexual dysfunction, disrupted sleep, and acute anxiety at the beginning of the treatment. These side-effects are likely due to the stimulation of serotonin 5-HT2A, 5-HT2C, and 5-HT3 receptors by increased serotonin levels; combined serotonin reuptake inhibition and antagonism at these receptors is thus a desirable profile for novel antidepressants. Target-related adverse effects are sometimes “outbalanced” by additional pharmacological activities. Selective cyclooxygenase-2 (COX-2) inhibitors (“coxibs”) were withdrawn due to an increased risk of cardiovascular events,148 whereas dual COX-1/COX-2 inhibitors (nonsteroidal anti-inflammatory drugs) remain widely used. Rapacuronium was withdrawn because of bronchospasms during treatment, likely due to selective muscarinic M2 receptor antagonism in absence of M3

practically all clinically efficacious antibiotics were discovered by whole-cell screening, which allows for the discovery of multitarget drugs. Since the mid-1990s, antibiotic research focused increasingly on single targets derived from bacterial genomes; these endeavors seem to have been generally fruitless. Similarly, polypharmacological treatment prevents drug resistance in viral and parasite infections.123 For neglected tropical diseases, polypharmacological drugs are expected to combat several strains of parasites124,125 or to treat both primary and opportunistic infections.125,126 Apart from schizophrenia, cancer, and infections, polypharmacological treatments may benefit a range of other diseases, such as depression,127−129 other psychiatric disorders,107,130,131 neurodegeneration,132−135 epilepsy,136 cardiovascular disorders,96,137,138 arrhythmia139−141 airway diseases,142 autoimmune disorders,14 inflammation,143 and pain.144 The Food and Drug Administration (FDA) approved numerous polypharmacological drugs in recent years, for example, asenapine, sunitinib, and dronedarone (Chart 2). The majority of these approved drugs are multikinase anticancer drugs, followed by antipsychotics and antidepressants. For an overview, see Tables 2−4. 3.2. Why Polypharmacological Drugs Can Be Safer. Selective drugs are often perceived as inherently safer, because they cannot cause side-effects via nontherapeutic targets. However, many side-effects stem from interaction with the therapeutic target itself. Therapeutic-target-related side-effects are similarly common reasons for drug withdrawals, as are offChart 2. Recently Approved, Polypharmacological Drugs for Different Indications and Target Classes

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Table 3. Recently Approved and Advanced Investigational Antipsychotics drug

status

low nanomolar affinity for

paliperidone iloperidone asenapine

approved (FDA), 2006 approved (FDA), 2009 approved (FDA), 2009

lurasidone cariprazine zicronapine

approved (FDA), 2010 clinical studies, phase III clinical studies, phase III

dopamine D2, serotonin 5-HT2A, 5-HT7, α1, α2 adrenergic, histamine H1 receptor dopamine D2 − D4, serotonin 5-HT2A, 5-HT6, 5-HT7, and α1 adrenergic receptors dopamine D1 − D4, serotonin 5-HT1A, 5-HT1B, 5-HT2A‑C, 5-HT5A, 5-HT6, 5-HT7, α1, α2A‑C adrenergic, histamine H1, H2 receptors dopamine D2, serotonin 5-HT1A, 5-HT2A, 5-HT7, α2C adrenergic receptors dopamine D2, D3, serotonin 5-HT1A, 5-HT2A‑C receptors dopamine D2, D3, serotonin 5-HT2, α1 adrenergic receptors

Table 4. Recently Approved and Advanced Investigational Multi-Target Antidepressants drug

status

targets

agomelatine vilazodone vortioxetine tedatioxetine

approved (Europe), 2009 approved (FDA), 2011 clinical studies, phase III clinical studies, phase II

melatonin MT1, MT2, and serotonin 5-HT2C receptors serotonin reuptake, serotonin 5-HT1A receptor serotonin reuptake, serotonin 5-HT1A, 5-HT1B, 5-HT3A, 5-HT7 receptors serotonin, norepinephrine and dopamine reuptake, serotonin 5-HT2A, 5-HT2C, 5-HT3, α1A adrenergic receptors

Figure 5. Experimentation with early, polypharmacological antihistamines led to the discovery of antipsychotics and antidepressants.

receptor antagonism.149,150 Other drugs, which antagonize both the M2 and the M3 receptor, remain in use (atracurium, pancuronium, rocuronium, doxacurium). Fluoxetine, haloperidol, verapamil, and citalopram are potent hERG blockers (IC50 = 10 nM − 1 μM) but have a low pro-arrhythmic potential, probably because their hERG activity is offset by additional activities at cardiac Ca2+ and Na+ channels.151,152 3.3. Drug Polypharmacology: Opportunities for Repurposing and for the Discovery of New Drugs. “Drug repurposing” or “repositioning” refers to the use of an old drug for a new indication and has received much interest in recent years.153,154 The development of an already established drug for a new indication is usually faster and less risky than the development of a novel drug, because an established drug’s second development is facilitated by previous studies, such as formulation, human pharmacokinetic, and toxicity studies. Polypharmacological drugs can be repurposed based on their “off-target” activities.155 An astonishing case is the revival of thalidomide, which was first introduced in 1957 as a hypnotic. As is known today, thalidomide nearly always causes malformations in babies when taken during the first 3−6 weeks of pregnancy, likely due to induction of oxidative stress156 or due to interference with transcription.157 Tragically, the drug was recommended particularly for pregnant women for the alleviation of morning sickness and caused birth defects in thousands of cases. Thalidomide was withdrawn in 1961 after

these disastrous effects were recognized. In 1964, a serendipitous discovery led to the repurposing of thalidomide for the treatment of erythema nodosum leprosum (ENL), a painful inflammatory complication of leprosy. An ENL patient had been in so much pain that he had not slept in weeks, and his physician turned to thalidomide as a last resort  the banned hypnotic was still available in his infirmary. Thalidomide not only allowed this patient to sleep, it also eliminated the pain and the other symptoms of ENL. Clinical trials followed and demonstrated that thalidomide effected complete remission of ENL in nearly all treated patients. This efficacy is due to thalidomide’s off-target activity on tumor necrosis factor α (TNF-α), which is inappropriately produced in inflamed tissue. Today, thalidomide is used primarily for the treatment of multiple myeloma; its efficacy in this disease is due to still other, multiple off-target activities.158 More typical is the repurposing of contemporary kinase inhibitors for the treatment of different cancers. The first marketed kinase inhibitor, imatinib,159,160 was originally approved in 2001 for the treatment of chronic myelogenous leukemia (CML). Imatinib was initially intended to be a selective inhibitor of a kinase expressed from the fusion gene Bcr/Abl, which is the oncogene responsible for CML. Later, it was discovered that imatinib also inhibits the kinase c-Kit, whose gain-of-function mutations are responsible for many gastrointestinal tumors (GISTs).161 Imatinib showed high H



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Figure 6. Sulfonylurea antidiabetics were derived from antibiotics with hypoglycemic side-effects.

several “tricyclic” antidepressants. Only after the advent of radioligand binding assays, was it confirmed in 1976 that the efficacy of the phenothiazine antipsychotics correlated with their dopamine D2 receptor affinity167,168 and not with their antihistaminic activity. Similarly, it was shown that the tricyclic antidepressants inhibit serotonin and noradrenaline reuptake as their principal mode of action.169 In other cases, established drugs had therapeutically useful side-effects and were derivatized to maximize these side-effects into a main activity. Such derivatization shifted the affinity profile of an unselective compound class from one molecular therapeutic target to another, even though these targets were often not known at the time. For instance, sulfacarbamide (Figure 6) became an important sulfonamide antibacterial after World War II in Germany’s Soviet Occupation Zone, because it could be prepared from the limited stocks of then available chemicals. However, sulfacarbamide suffered from a short halflife. Loranil (1)170 was a follow-up compound with a longer half-life, but produced side-effects, which were reminiscent of hypoglycemia. The director of the sulfacarbamide-producing company Heyden AG took a massive dose of 1, reversed the adverse effects by ingestion of sugar, and thus proved the hypoglycemic activity of 1. The drug was banned thereafter and replaced by carbutamide, which was not only investigated as an antibiotic but also as a hypoglycemic drug for the treatment of noninsulin-dependent diabetes. Even though carbutamide was later marketed in Europe as an oral antidiabetic, it raised concerns because of its residual antibiotic activity and the possibility of the development of treatment-resistant bacteria. Also, carbutamide was not approved in the U.S. due to unacceptable side-effects. It was therefore followed up by tolbutamide, which had no antibiotic activity, and became an important treatment of noninsulin-dependent diabetes.171,172 This strategy to obtain a new drug by maximizing the sideeffects of an existing drug, and by minimizing its main activity, has been termed “selective optimization of side activities” (SOSA).173−175 SOSA was recently recommended as an alternative to the optimization of high-throughput screening hits. The main advantage of SOSA is the use of an established drug as a starting point for drug discovery, which should increase the chances of identifying clinical candidates with druglike properties. 3.4. How Could Polypharmacological Drug Discovery Be Put into Practice? Multitarget or polypharmacological

efficacy in the treatment of GISTs, a cancer type that had previously been resistant to chemotherapy, and the FDA approved imatinib for this indication in 2002. A similarly repurposed drug is sunitinib,162 which was originally intended for renal cell carcinoma therapy. Like imatinib, sunitinib inhibits c-Kit and was therefore also developed for the treatment of GISTs. In 2006, the FDA approved sunitinib simultaneously for both indications. Additionally, sunitinib inhibits FLT3, RET, and CSF1R, which are drug targets for acute myeloid leukemia, neuroendocrine tumors, and metastatic breast cancer, respectively. Sunitinib is currently being developed for these and other indications. Also, sorafenib was originally intended to be a Raf kinase inhibitor for the treatment of Raf-dependent melanoma, but failed in clinical trials. However, early clinical safety studies indicated unexpected efficacy in kidney and liver cancer, which led to a successful development of sorafenib for these cancer types. This unexpected efficacy is attributed to sorefenib’s (originally unintended) activity at VEGFR and PDGFR.15,117,163 Polypharmacology-based repurposing also led to the discovery of several important drug classes in the early years of drug discovery. For example, antihistamines were a popular research topic in the 1940s, because these compounds were easy to synthesize and easy to test in animals. Antihistamines entered the market in large numbers, and physicians experimented with them in a variety of diseases.164 For instance, promethazine (Figure 5) was used experimentally to sedate patients before surgery. The promising results led to experimentation with similar, investigational antihistamines. Chlorpromazine165 was particularly efficacious and was thus recommended to be used as a sedative also in psychiatry. When chlorpromazine was tested in schizophrenic patients, it showed an astonishing efficacy, which went far beyond its sedative effects. This discovery revolutionized the treatment of schizophrenia: for the first time, a pharmacological management of schizophrenia was available and allowed patients to live a relatively normal life outside locked wards. This success prompted many research companies to discover and develop their own antipsychotics. One of these investigational compounds, imipramine,166 was completely ineffective in a large number of schizophrenic patients and was therefore tested in other psychiatric indications. Antidepressant efficacy was recognized after the treatment of only three patients and was later confirmed in larger trials. Imipramine became the first of I



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Figure 7. The connection of two dissimilar pharmacophores led to the dual-target antihypertensive 2 with a high molecular weight.

Compound 2 was antihypertensive in vivo, but was never developed, possibly due to extreme molecular properties. Thus, multitargeting across different target classes is challenging; only 2% of the drugs in the ChEMBL database are annotated to targets of different classes.91 However, if pharmacophores are similar, they may overlap in a single molecule. Such “fused” or “merged” pharmacophores180,181 have often acceptable molecular properties, especially if the individual pharmacophores have a low MW to start with. For instance, Pfizer researchers merged naphtylpiperazine and dopamine into 3 (Figure 8) in a

drugs have been advocated mainly by academic groups in recent years. Industrial drug hunters have not yet widely embraced polypharmacological drug research (except for anticancer and psychiatry drugs), in part because lead-to-drug optimization is much more complex for multitarget compounds: druglike molecular properties must be balanced with multiple pharmacological activities, rather than single activities. Unintended interactions with additional targets can often not be avoided, which raises safety concerns. The translatability of animal disease models to human patients may be even less reliable. Finally, the optimal ratio of pharmacological activities for different targets may not be 1:1 and can be a matter of debate. For instance, antipsychotics are believed to have an optimal ratio of serotonin 5-HT2A/dopamine D2 receptor antagonism of 10:1 to reduce extrapyramidal side-effects; triple reuptake inhibitors as antidepressants may need a higher inhibitory activity for the serotonin and norepinephrine transporters than for the dopamine transporter to avoid abuse liabilities.176 The combination of individual single-target drugs may appear as a viable alternative to polypharmacological drug discovery and is common practice in the therapy of hypertension,138 metabolic disorders, cancer, and infections (in particular, human immunodeficiency virus [HIV], and tuberculosis infections). However, an increasing number of individual drugs put patients at an exponentially increasing risk of drug−drug interactions or of poor compliance due to complex dosing regimens. To avoid these risks, two or three single-target drugs can be combined in a single pill. Such “fixeddose combinations” are for instance common in anti-HIV drugs.177 But combination pills are often not feasible for more than three active ingredients, because of pharmacokinetic differences between the individual drugs. Perhaps more importantly, drugs are rarely developed to be used solely in combination: for the regulatory approval of a drug combination, safety must be demonstrated for the combination, as well as for the individual drugs, which is often prohibitively costly for novel drugs. Additional difficulties arise when investigational drugs originate from different companies.178 Consequently, there is a need for single drugs with multiple targets.179 But how can starting points for multitarget drug discovery projects be obtained and optimized? In the recent past, three main strategies have been pursued: design, multitarget screening, and phenotypical screening. Polypharmacological leads can be designed by a combination of known pharmacophores into a single compound.180 Dissimilar pharmacophores (for different target classes) have been connected by linkers. This strategy leads often to a high MW and extreme lipophilicity,181 and the development of such hybrid drugs has met little success.182 For example, the betablocker pindolol was connected to the angiotensin-converting enzyme (ACE) inhibitor enalaprilat to give the dual-target 2 (Figure 7),182 with a high MW well outside the Lipinski rules.

Figure 8. The antipsychotic ziprasidone was discovered by merging serotonin and dopamine receptor pharmacophores.

search for multitarget serotonin/dopamine receptor antagonists as novel antipsychotics. Naphtylpiperazine binds to practically all serotonin receptors, and dopamine is an endogenous ligand of all dopamine receptors. Compound 3 combines much of the serotonin and dopamine receptor affinities of the individual compounds and has a drug-like MW. Further optimization resulted in ziprasidone, which was successfully developed. J



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screened unselective RET kinase inhibitors in a fruit fly (Drosophila) model of RET-driven cancer and identified a compound which rescued fruit fly larvae to adulthood. In a next step, they performed a kinome scan in the presence of this compound. Raf and Src inhibition (in addition to RET inhibition) increased survival rates, whereas inhibition of the mammalian target of rapamycin (mTOR) was toxic. On the basis of these findings, they designed an improved compound, which was highly efficacious and well tolerated in the fruit fly model, and which performed 500 times better on human cell lines than the thyroid cancer drug vandetanib. In a mouse model, this improved compound was far more effective than vandetanib and again very well tolerated.197 Phenotypic screening with polypharmacological compounds exploits an extended target space. Often, an individual blockade or knockout of single targets does not result in an observable effect, whereas a combined multiple blockade of the same targets leads to a phenotype (“synthetic behavior”).9 For example, glycine transporter 2 (GlyT2) antagonists with additional purinergic P2X3 and serotonergic 5-HT2A receptor antagonism were efficacious in electrophysiological and in animal pain models, whereas selective antagonists of the same targets were not (but were again effective when dosed together).198 Thus, polypharmacological compounds can recruit a target space which is unavailable for single-target compounds. This is not only an opportunity for drug discovery but also increases the chances of finding polypharmacological lead compounds in phenotypic approaches.

Many more examples for the design of multitarget compounds can be found in reviews.180−184 Automated denovo design of compounds with a desired pharmacological profile is also possible.185 A special case is multitarget peptides, which combine the pharmacophores of two or more related peptide hormones.186,187 Multitarget leads can also be identified in high-throughput screens against several targets. Screens are usually performed subsequently, rather than in parallel.180 For instance, serotonin reuptake transporter inhibitors with additional serotonin 5HT1A receptor antagonism are believed to have a faster onset of antidepressant action. To identify starting points for a dual SERT/5-HT1A receptor blocker, GlaxoSmithKline scientists first screened their compound library in a functional serotonin 5-HT1A receptor assay and then screened identified antagonists for blockade of the serotonin reuptake mechanism.188 In similar approaches, compounds with an already known pharmacology are screened against other targets of interest. Sometimes, “screening” for multitarget compounds can even be reduced to a data-mining effort: multitarget discovery projects usually pursue established targets, rather than novel targets. Consequently, multitarget “hits” may be found by mining public or proprietary databases of established targets and ligands.12,189 For example, dual antagonism at the serotonin reuptake transporter (SERT) and the 5-HT2A receptor is regarded as a desirable profile for novel antidepressants with a reduced liability for disrupted sleep and sexual dysfunction.107,127 Mining of Roche legacy HTS data yielded 50 compounds with potent SERT and 5-HT2A receptor antagonism as hits for a proposed antidepressant discovery project. Multitarget fragment screening is another option and was successful in the discovery of the pan-peroxisome-proliferator-activatedreceptor (pan-PPAR) agonist, indeglitazar.190 Virtual screening (pharmacophore-based) and computational docking (biostructure-based) have also been used to discover multitarget compounds.191−193 Researchers from the Peking University and the Beijing National Laboratory for Molecular Sciences combined both methods in a search for multitarget anti-inflammatory compounds: in a first step, they sought inflammation targets, which accommodated similar pharmacophores, and could thus be inhibited by a single drug. In a second step, they docked commercially available compounds into these targets and screened them against the common pharmacophore. This approach led to the identification of a dual leukotriene A4 hydrolase/phospholipase A2 inhibitor.194 However, future polypharmacological drugs may not necessarily be discovered by deliberate design or screening. More likely, they will emerge from new approaches to drug discovery. Our current single-target-based paradigm results in single-target drugs by implication. The dominance of this paradigm has been challenged and has been associated with the productivity decline of the pharmaceutical industry.13 Many research organizations are therefore considering alternatives.195 Particularly, they revisit phenotypic screening, which is generally more successful for the discovery of first-in-class medicines. 196 In the “golden era” of drug discovery, phenotypical approaches often led to polypharmacological drugs. As we “rediscover” such approaches, we may again encounter polypharmacology by serendipity. Alternatively, we can apply phenotypic screening to the rational discovery of polypharmacological drugs with maximal efficacy and minimal toxicity. Researchers from the Mount Sinai School of Medicine and University of California, San Francisco,

4. SUMMARY Since the 1990s, industrial drug discovery has been aiming for highly selective drugs to avoid adverse effects mediated through “antitargets”. Lack of selectivity has usually been discovered late in a drug discovery project and has typically led to substantial delays or late-stage attrition. Major research organizations have therefore begun to screen early compounds against small panels of frequently hit antitargets and made selectivity a matter of early optimization. On the other hand, the opportunities of polypharmacological drug discovery are increasingly being appreciated. The FDA has approved numerous polypharmacological drugs for different target classes and indications in recent years. Many multigenic diseases do not succumb to single-target therapies but rather require a polypharmacological modulation of a network of targets. Some authors have even associated the “one disease − one target” philosophy with the productivity decline of the pharmaceutical industry13 and have advocated network pharmacology as the “next paradigm in drug discovery”.5 However, many researchers perceive a gap between theoretical network concepts and the practical discovery of polypharmacological drugs: how can they achieve a desired polypharmacological profile, especially across different target classes? Will polypharmacology increase the incidences of adverse effects? Will the optimization of polypharmacological compounds be prohibitively complex? The pharmaceutical industry currently revisits phenotypical screening as an alternative to the ubiquitous target-based drug discovery. In the “golden era” of drug discovery, phenotypical approaches delivered many polypharmacological drugs. It is quite possible that we will encounter polypharmacology again in such approaches without explicitly looking for it. K



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(2) Connolly, H. M.; Crary, J. L.; Mcgoon, M. D.; Hensrud, D. D.; Edwards, B. S.; Edwards, W. D.; Schaff, H. V. Valvular heart disease associated with fenfluramine-phentermine. N. Engl. J. Med. 1997, 337 (9), 581−588. (3) Hutcheson, J. D.; Setola, V.; Roth, B. L.; Merryman, W. D. Serotonin receptors and heart valve disease-It was meant 2B. Pharmacol. Ther. 2011, 132 (2), 146−157. (4) Whitebread, S.; Hamon, J.; Bojanic, D.; Urban, L. In vitro safety pharmacology profiling: an essential tool for successful drug development. Drug Discovery Today 2005, 10 (21), 1421−1433. (5) Hopkins, A. L. Network pharmacology: the next paradigm in drug discovery. Nat. Chem. Biol. 2008, 4 (11), 682−690. (6) Gleeson, M. P.; Hersey, A.; Montanari, D.; Overington, J. Probing the links between in vitro potency, ADMET and physicochemical parameters. Nat. Rev. Drug Discovery 2011, 10 (3), 197−208. (7) Ainsworth, C. Networking for new drugs. Nat. Med. 2011, 17 (10), 1166−1168. (8) Mencher, Simon, K.; Wang, Long, G. Promiscuous drugs compared to selective drugs (promiscuity can be a virtue). BMC Clin. Pharmacol. 2005, 5 (1), 3. (9) Hopkins, A. L. The Case for Polypharmacology. In Polypharmacology in Drug Discovery; Peters, J.-U., Ed.; Wiley: Hoboken, 2012; pp 1−6. (10) Abbenante, G.; Reid, R. C.; Fairlie, D. P. ‘Clean’ or ‘Dirty’ - Just How Selective Do Drugs Need To Be? Aust. J. Chem. 2008, 61 (9), 654−660. (11) Korcsmaros, T.; Szalay, M. S.; Bode, C.; Kovacs, I. A.; Csermely, P. How to design multi-target drugs: target search options in cellular networks. Expert Opin. Drug Discovery 2007, 2 (6), 799−808. (12) Reddy, A. S.; Zhang, S. Polypharmacology: drug discovery for the future. Expert Rev. Clin. Pharmacol. 2013, 6 (1), 41−47. (13) Sams-Dodd, F. Target-based drug discovery: is something wrong? Drug Discovery Today 2005, 10 (2), 139−147. (14) Hornberg, J. J. Simple Drugs Do Not Cure Complex Diseases: The Need for Multi-Targeted Drugs. In Designing Multi-Target Drugs; Morphy, J. R.; Harris, C. J., Eds.; RSC Publishing: Cambridge, 2012; pp 1−13. (15) Petrelli, A. Polypharmacological Kinase Inhibitors: New Hopes for Cancer Therapy. In Polypharmacology in Drug Discovery; Peters, J.U., Ed., Wiley: Hoboken, 2012; pp 149−165. (16) Kroeze, W. K.; Roth, B. L. Polypharmacological Drugs: Magic Shotguns for Psychiatric Diseases. In Polypharmacology in Drug Discovery; Peters, J.-U., Ed., Wiley: Hoboken, 2012; pp 135−148. (17) Roth, B. L.; Sheffler, D. J.; Kroeze, W. K. Magic shotguns versus magic bullets: selectively non-selective drugs for mood disorders and schizophrenia. Nat. Rev. Drug Discovery 2004, 3 (4), 353−359. (18) Hopkins, A. L. Network pharmacology. Nat. Biotechnol. 2007, 25 (10), 1110−1111. (19) Vaz, R. J.; Klabunde, T., Eds. Antitargets; Wiley-VCH: Weinheim, 2008. (20) Urban, L.; Whitebread, S.; Hamon, J.; Mikhailov, D.; Azzaoui, K. Screening for Safety-Relevant Off-Target Activities. In Polypharmacology in Drug Discovery; Peters, J.-U., Ed., Wiley: Hoboken, 2012; pp 15−46. (21) Olson, H.; Betton, G.; Robinson, D.; Thomas, K.; Monro, A.; Kolaja, G.; Lilly, P.; Sanders, J.; Sipes, G.; Bracken, W.; Dorato, M.; Van Deun, K.; Smith, P.; Berger, B.; Heller, A. Concordance of the Toxicity of Pharmaceuticals in Humans and in Animals. Regul. Toxicol. Pharmacol. 2000, 32 (1), 56−67. (22) Zbinden, G. Predictive value of animal studies in toxicology. Regul. Toxicol. Pharmacol. 1991, 14 (2), 167−77. (23) Kaczorowski, G. J.; Garcia, M. L.; Bode, J.; Hess, S. D.; Patel, U. A. The importance of being profiled: improving drug candidate safety and efficacy using ion channel profiling. Front. Pharmacol. 2011, 2, 78. (24) http://www.ich.org/fileadmin/Public_Web_Site/ICH_ Products/Guidelines/Safety/S7A/Step4/S7A_Guideline.pdf (25) Pugsley, M. K.; Authier, S.; Curtis, M. J. Principles of Safety Pharmacology. Br. J. Pharmacol. 2008, 154 (7), 1382−1399.

AUTHOR INFORMATION

Corresponding Author

*Phone: +49 61 68 82636. E-mail: [email protected]. Notes

The authors declare no competing financial interest. Biography Jens-Uwe Peters studied chemistry at the University of Göttingen and the University of California, San Diego. After receiving his diploma, he worked in Siegfried Blechert’s laboratories at the TU Berlin, obtained his Ph.D., and then did a postdoc with Julius Rebek at the Scripps Institute in La Jolla. In 1999, he joined the Discovery Chemistry department of F. Hoffmann-La Roche Ltd. in Basel and has since contributed to numerous drug discovery projects. In parallel to his project work, he has been active in several work groups concerned with the assessment, interpretation, and optimization of molecular properties, especially properties related to early safety pharmacology.

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ACKNOWLEDGMENTS I would like to thank the following for their advice: Annalisa Petrelli from the University of Turin, the anonymous reviewers, and my Roche colleagues Luke Green, Wolfgang Guba, Jérôme Hert, Susanne Mohr, Liudmila Polonchuk, and Hervé Schaffhauser.

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ABBREVIATIONS USED ACE, angiotensin-converting enzyme; ADR, adverse drug reaction; BSEP, bile salt export pump; CML, chronic myelogenous leukemia; COX, cyclooxygenase; CSF-1, colony stimulating factor 1; CSF-1R, colony stimulating factor 1 receptor; CYP, cytochrome P450; EGF, epidermal growth factor; EGFR, epidermal growth factor receptor; ENL, erythema nodosum leprosum; FDA, Food and Drug Administration; FGFR, fibroblast growth factor receptor; Flt-3, Fmslike tyrosine kinase 3; GIST, gastrointestinal stromal tumor; GlyT2, glycine transporter 2; GPCR, G protein-coupled receptor; HER-2, human epidermal growth factor receptor 2; hERG, human ether-à-go-go-related gene; HGF, hepatocyte growth factor receptor; HGFR, hepatocyte growth factor receptor; HIV, human immunodeficiency virus; 5-HT, 5hydroxytryptamine (serotonin); HTS, high-throughput screen; MW, molecular weight; NE, norepinephrine; NSAID, nonsteroidal anti-inflammatory drug; PDB, Protein Data Bank; PDGF, platelet-derived growth factor; PDGFR, platelet-derived growth factor receptor; PDSP, Psychoactive Drug Screening Program; PPAR, peroxisome proliferator-activated receptor; RET, (“rearranged during transfection”) a proto-oncogene; SEA, similarity ensemble approach; SERT, serotonin reuptake transporter; SOSA, selective optimization of side activities; SDF-1, stromal cell-derived factor-1; Src, (short for sarcoma) a proto-oncogene; SSRI, selective serotonin reuptake inhibitor; TIE2, tyrosine kinase with immunoglobulin-like and EGF-like domains 2; TNF-α, tumor necrosis factor α; mTOR, mammalian target of rapamycin; VEGF, vascular endothelial growth factor; VEGFR, vascular endothelial growth factor receptor

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