PERSPECTIVES
`
`O P I N I O N
`
`Drugs, their targets and the nature
`and number of drug targets
`
`Peter Imming, Christian Sinning and Achim Meyer
`
`Abstract | What is a drug target? And how many such targets are there? Here, we
`consider the nature of drug targets, and by classifying known drug substances on
`the basis of the discussed principles we provide an estimation of the total number
`of current drug targets.
`
`Estimations of the total number of drug
`targets are presently dominated by analyses
`of the human genome, which are limited
`for various reasons, including the inability
`to infer the existence of splice variants or
`interactions between the encoded proteins
`from gene sequences alone, and the fact
`that the function of most of the DNA in
`the genome remains unclear. In 1997,
`when 100,000 protein-coding sequences
`were hypothesized to exist in the human
`genome, Drews and Ryser estimated the
`number of molecular targets ‘hit’ by all
`marketed drug substances to be only 482
`(REF. 1). In 2002, after the sequencing of the
`human genome, others arrived at ~8,000
`targets of pharmacological interest, of
`which nearly 5,000 could be potentially
`hit by traditional drug substances, nearly
`2,400 by antibodies and ~800 by protein
`pharmaceuticals2. And on the basis of
`ligand-binding studies, 399 molecular
`targets were identified belonging to 130
`protein families, and ~3,000 targets for
`small-molecule drugs were predicted to
`exist by extrapolations from the number
`of currently identified such targets in the
`human genome3.
`In summary, current target counts are
`of the order of 102, whereas estimations of
`the number of potential drug targets are an
`order of magnitude higher. In this paper, we
`consider the nature of drug targets, and use a
`classification based on this consideration, and
`a list of approved drug substances (TABLES 1–8,
`BOX 1), to estimate the number of known drug
`targets, in the following categories:
`
`• Enzymes (TABLE 1)
`• Substrates, metabolites and proteins
`(TABLE 2)
`• Receptors (TABLE 3)
`• Ion channels (TABLE 4)
`• Transport proteins (TABLE 5)
`• DNA/RNA and the ribosome (TABLE 6)
`•
` Targets of monoclonal antibodies
`(TABLE 7)
`• Various physicochemical mechanisms
`(TABLE 8)
`• Unknown mechanism of action (BOX 1)
`
`The nature of drug targets
`A prerequisite for counting the number of
`targets is defining what a target is. Indeed,
`this is the crucial, most difficult and also
`most arbitrary part of the present approach.
`For the purpose of this paper, we consider a
`target to be a molecular structure (chemically
`definable by at least a molecular mass) that
`will undergo a specific interaction with
`chemicals that we call drugs because they are
`administered to treat or diagnose a disease.
`The interaction has a connection with the
`clinical effect(s).
`This definition implies several con-
`straints. First, the medicinal goal excludes
`pharmacological and biochemical tools
`from the present approach. Second, a major
`constraint is a lack of technique. Life, includ-
`ing disease, is dynamic, but as we do not yet
`directly observe the interactions of drugs
`and targets, and only partly notice the sub-
`sequent biochemical ‘ripples’ they produce;
`we are generally limited to ‘still life’ (for
`example, X-ray crystal structures)
`
`and to treating targets as static objects.
`In the case of G-protein-coupled receptors
`(GPCRs), the pharmaceutically most useful
`class of receptors, a re-organization of the
`protein after drug binding was derived from
`biochemical data4, but such approaches are
`still in their infancy.
`For most drugs, several if not many targets
`were identified. Consequently, we had to
`decide for every drug substance or drug
`class which target(s) to include in our list.
`For this, we relied on the existence of lit-
`erature data that showed some connection
`between the interaction of the drug with
`the biochemical structure of the target and
`the clinical effect(s) (not side effects).
`A chemical with a certain reactivity or
`binding property is used as a drug because
`of its clinical effects, but it should be
`stressed that it can be challenging to prove
`that a certain molecular interaction is
`indeed the one triggering the effect(s).
`In this respect, knockout mice are proving
`increasingly useful. For example, a lack of
`effect of a drug in mice lacking a particular
`target can provide strong support that the
`effects of the drug are mediated by that target
`(for a review on knockout mice in target
`validation, see REF. 5).
`We therefore considered the construction
`of knockout animals that lack the target,
`with pertinent observation of effects, strong
`proof or disproof for a certain mechanism
`of action. In the case of receptors, we
`regarded the availability and testing of
`both agonists and antagonists (and/or
`inverse agonists) proof for a mechanism.
`In the case of enzyme inhibitors (for example,
`cyclooxygenase inhibitors), molecular
`interactions and effects of structurally
`unrelated substances that are largely
`identical were considered proof of the
`mechanism. In cases where a drug inter-
`action on the biochemical level was found,
`but the biochemical pathway was not yet
`known to be connected with the observed
`drug effect, the target was not counted. For
`antipsychotic drugs in particular, a plethora
`of target receptors and receptor subtypes
`are known and discussed (see PDSP Ki
`Database in Further information and
`BOX 2). However, extensive discussion of
`such issues is outside the scope of an article
`
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`P E R S P E C T I V E S
`
`Table 1a | Enzymes
`Type
`Oxidoreductases
`Aldehyde dehydrogenase
`Monoamine oxidases (MAOs)
`
`Cyclooxygenases (COXs)
`
`Vitamin K epoxide reductase
`Aromatase
`Lanosterol demethylase (fungal)
`Lipoxygenases
`
`Thyroidal peroxidase
`Iodothyronine-5′ deiodinase
`Inosine monophosphate dehydrogenase
`HMG-CoA reductase
`5α-Testosterone reductase
`Dihydrofolate reductase (bacterial)
`Dihydrofolate reductase (human)
`Dihydrofolate reductase (parasitic)
`Dihydroorotate reductase
`Enoyl reductase (mycobacterial)
`Squalene epoxidase (fungal)
`Δ14 reductase (fungal)
`Xanthine oxidase
`4-Hydroxyphenylpyruvate dioxygenase
`Ribonucleoside diphosphate reductase
`Transferases
`Protein kinase C
`Bacterial peptidyl transferase
`Catecholamine-O-methyltransferase
`RNA polymerase (bacterial)
`Reverse transcriptases (viral)
`
`DNA polymerases
`GABA transaminase
`Tyrosine kinases
`
`Glycinamide ribonucleotide formyl transferase
`Phosphoenolpyruvate transferase (MurA, bacterial)
`Human cytosolic branched-chain aminotransferase
`(hBCATc)
`EGFR, epidermal growth factor receptor; GABA, γ-amino butyric acid; HMG-CoA, 3-hydroxy-3-methyl-glutaryl coenzyme A; PDGFR, platelet-derived growth factor receptor;
`VEGFR, vascular endothelial growth factor receptor.
`
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`
`Activity of drug
`
`Drug examples
`
`Inhibitor
`MAO-A inhibitor
`
`MAO-B inhibitor
`COX1 inhibitor
`
`COX2 inhibitor
`
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`5-lipoxygenase inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`
`Disulfiram39
`Tranylcypromine40, moclobemide41
`
`Tranylcypromine40
`Acetylsalicylic acid, profens, acetaminophen and
`dipyrone (as arachidonylamides)42,43
`Acetylsalicylic acid, profens, acetaminophen and
`dipyrone (as arachidonylamides)44
`Warfarin, phenprocoumon45
`Exemestane46
`Azole antifungals47
`Mesalazine48
`Zileuton49
`Thiouracils50
`Propylthiouracil50
`Mycophenolate mofetil51
`Statins52
`Finasteride, dutasteride53
`Trimethoprim54
`Methotrexate, pemetrexed55
`Proguanil56
`Leflunomide57
`Isoniazid58
`Terbinafin59
`Amorolfin60
`Allopurinol61
`Nitisinone62
`Hydroxycarbamide63
`
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Competitive inhibitors
`Allosteric inhibitors
`Inhibitor
`Inhibitor
`PDGFR/ABL/KIT inhibitor
`EGFR inhibitor
`VEGFR2/PDGFRβ/KIT/FLT3
`VEGFR2/PDGFRβ/RAF
`Inhibitor
`Inhibitor
`Inhibitor
`
`Miltefosine64,65
`Chloramphenicol67
`Entacapone68
`Ansamycins69
`Zidovudine70,71
`Efavirenz72,73
`Acyclovir, suramin74,75
`Valproic acid76, vigabatrin77
`Imatinib78
`Erlotinib79
`Sunitinib66
`Sorafenib109
`Pemetrexed55
`Fosfomycin80,81
`Gabapentin82
`
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`Activity of drug
`
`HIV protease inhibitor
`
`Unspecific inhibitors
`Direct inhibitor
`Indirect inhibitor
`Direct inhibitor
`Activator
`Activator
`Activator
`Inhibitor
`
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`
`Inhibitor
`AChE inhibitor
`AChE reactivators
`PDE inhibitor
`PDE3 inhibitor
`PDE4 inhibitor
`PDE5 inhibitor
`HDAC inhibitor
`HDAC3/HDAC7 inhibitor
`α-glycosidase inhibitor
`α-glycosidase inhibitor
`Gastrointestinal lipases inhibitor
`Calcineurin inhibitor
`Inositol polyphosphate phosphatase inhibitor
`Rac1 inhibitor
`Bacterial C55-lipid phosphate dephosphorylase inhibitor
`
`Inhibitor
`Inhibitor
`Inhibitor
`Inhibitor
`Activator
`
`P E R S P E C T I V E S
`
`Drug examples
`
`Saquinavir, indinavir94
`
`Aprotinine95
` β-lactams96
`Glycopeptides97
`Sulbactam98
`Heparins99-101
`Streptokinase102,103
`Factor IX complex, Factor VIII104
`Fondaparinux105
`
`Captopril106
`Cilastatin107
`Penicillamine108
`Racecadotril110
`
`Bortezomib83
`Physostigmine84
`Obidoxime85
`Caffeine86
`Amrinon, milrinone87
`Papaverine88
`Sildenafil89
`Valproic acid76
`Carbamezepine90
`Zanamivir, oseltamivir91
`Acarbose92
`Orlistat93
`Cyclosporin111
`Lithium ions112,113
`6-Thio-GTP (azathioprine metabolite)114
`Bacitracin115
`
`Carbidopa116
`Acetazolamide117
`Tritoqualine118
`Eflornithine119
`Nitric acid esters, molsidomine120-123
`
`Inhibitor
`Inhibitor
`Topoisomerase I inhibitor
`Topoisomerase II inhibitor
`Inhibitor
`
`d-Cycloserine124
`Fluoroquinolones125
`Irinotecan126
`Etoposide127
`Amorolfin128
`
`Table 1b | Enzymes
`Type
`Hydrolases (proteases)
`Aspartyl proteases (viral)
`Hydrolases (serine proteases)
`Unspecific
`Bacterial serine protease
`Bacterial serine protease
`Bacterial lactamases
`Human antithrombin
`Human plasminogen
`Human coagulation factor
`Human factor Xa
`Hydrolases (metalloproteases)
`Human ACE
`Human HRD
`Human carboxypeptidase A (Zn)
`Human enkephalinase
`Hydrolases (other)
`26S proteasome
`Esterases
`
`Glycosidases (viral)
`Glycosidases (human)
`Lipases
`Phosphatases
`
`GTPases
`Phosphorylases
`Lyases
`DOPA decarboxylase
`Carbonic anhydrase
`Histidine decarboxylase
`Ornithine decarboxylase
`Soluble guanylyl cyclase
`Isomerases
`Alanine racemase
`DNA gyrases (bacterial)
`Topoisomerases
`
`Δ8,7 isomerase (fungal)
`Ligases (also known as synthases)
`Sulphonamides129
`Inhibitor
`Dihydropteroate synthase
`Fluorouracil130
`Inhibitor
`Thymidylate synthase (fungal and human)
`Methotrexate, pemetrexed55,131
`Inhibitor
`Thymidylate synthase (human)
`Antimony compounds132
`Inhibitor
`Phosphofructokinase
`Rapamycin133
`Inhibitor
`mTOR
`Quinoline antimalarials134
`Inhibitor
`Haem polymerase (Plasmodium)
`1,3-β-d-glucansynthase (fungi)
`Caspofungin135
`Inhibitor
`Miglustat136
`Inhibitor
`Glucosylceramide synthase
`ACE, angiotensin-converting enzyme; AChE, acetylcholinesterase; HDAC, histone deacetylase; HRD, human renal dehydropeptidase; mTOR, mammalian target of rapamycin;
`PDE, phosphodiesterase.
`
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`P E R S P E C T I V E S
`
`Table 2 | Substrates, metabolites and proteins
`Substrate
`Drug substance
`Asparagine
`Asparaginase137
`Urate
`Rasburicase (a urate oxidase)138
`VAMP–synaptobrevin, SNAP25, Syntaxin
`Light chain of the botulinum neurotoxin
`(Zn-endopeptidase)139
`SNAP, synaptosomal-associated protein; VAMP, vesicle-associated membrane protein.
`
`that tries to cover ‘all’ drug substances.
`For the present purpose, we chose to limit
`our analysis to published consensus data
`on one to three of the main biochemical
`targets of drug substances. If there was
`no consensus or proof of target and/or
`target–effect connection, we included the
`respective substances in a part of our list
`called ‘Unknown mechanism of action’.
`
`The dynamics of drug effects. It would
`ultimately be desirable to move away from a
`static target definition, but this is hindered
`mainly by our inability to gauge the inter-
`action of the aforementioned ‘ripples’ — in
`other words, the actual pharmacodynamics
`of drugs. All drugs somehow interfere with
`signal transduction, receptor signalling and
`biochemical equilibria. For many drugs
`we know, and for most we suspect, that
`they interact with more than one target.
`So, there will be simultaneous changes in
`several biochemical signals, and there will
`be feedback reactions of the pathways dis-
`turbed. In most cases, the net result will not
`be linearly deducible from single effects.
`For drug combinations, this is even more
`complicated. A mechanism-based simula-
`tion of pharmacodynamic drug–drug
`interactions was published recently6,
`highlighting the complexity of interaction
`analyses for biological systems. Awareness
`is also increasing of the nonlinear correla-
`tion of molecular interactions and clinical
`effects. For example, the importance of
`receptor–receptor interactions (receptor
`mosaics) was recently summarized for
`GPCRs, resulting in the hypothesis that
`cooperativity is important for the decoding
`of signals, including drug signals7. Another
`paper reported dopamine fluctuations after
`
`administration of cocaine, followed by a
`gradual increase in steady-state dopamine
`concentration8. Indeed, the dynamics of the
`response are what really matters, but are
`difficult to assess experimentally. Further
`examples of dynamic (process) mechanisms
`of drug action include non-covalent modi-
`fications of the active centre (for example,
`acetylation of bacterial transpeptidases by
`β-lactam antibiotics); allosteric modulation
`(for example, benzodiazepine modulation
`of GABA (γ-amino butyric acid) receptors);
`drugs that require the receptor to be in a
`certain state for binding and inhibition
`(for example, ‘trapping’ of K+ channels by
`methanesulphoanilide anti-arrhythmic
`agents9); drugs that exert their effect indi-
`rectly and require a functional background
`(for example, the catechol-O-methyl
`transferase inhibitor entacapone, the effect
`of which is due to the accumulation of non-
`metabolized dopamine); anti-infectives
`that require the target organism to be
`in an active, growing state (for example
`β-lactams); molecules requiring activation
`(prodrugs, such as paracetamol); and cases
`of modifications of a substrate or cofactor
`(for example, asparaginase, which depletes
`tumour cells of asparagine; isoniazide,
`which is activated by mycobacteria leading
`to an inactive covalently modified NADH;
`and vancomycin, which binds to the
`building block bacteria use for constructing
`their cell wall).
`
`The macro- and micro-world of targets.
`So, for estimations of the total number of
`targets, a clinically relevant ‘target’ might
`consist not of a single biochemical entity, but
`the simultaneous interference of a number
`of receptors (pathways, enzymes and so on).
`
`Box 1 | Drugs with unknown mechanism of action
`
`4-Aminosalicylic acid | Alendronate | Ambroxol | Arsenic trioxide | Becaplermin | Bexarotene |
`Chloral hydrate | Clofazimine | Dactinomycin (RNA synthesis inhibitor) | Dapsone (folic acid
`synthesis inhibitor) | Diethyl carbamazine | Diethyl ether | Diloxanide | Dinitric oxide | Ethambutol |
`Gentian violet | Ginkgolides | Griseofulvin | Halofantrine | Halothane | Hydrazinophthalazine |
`Limefantrine (antimalarial; prevents haem polymerization) | Levetiracetam | Mebendazole |
`Methyl-(5-amino-4-oxopentanoate) | Niclosamide | Pentamidine | Podophyllotoxin | Procarbazine |
`Selenium sulphide
`
`Only this will give a net clinical effect that
`might be considered beneficial. As yet, we
`are unable to count ‘targets’ in this sense
`(‘macro-targets’), and it is only by chance
`that most of the current in vitro screening
`techniques will identify drugs that work
`through such targets.
`Greater knowledge of how drugs
`interact with the body (mechanisms of
`action, drug–target interactions) has led
`to a reduction of established drug doses
`and inspired the development of newer,
`highly specific drug substances with a
`known mechanism of action. However,
`a preoccupation with the molecular details
`has sometimes resulted in a tendency to
`focus only on this one aspect of the drug
`effects. For example, cumulative evidence
`now suggests that the proven influence of
`certain psychopharmaceuticals on neuro-
`transmitter metabolism has little to do
`with the treatment of schizophrenia or
`the effectiveness of the drug for this
`indication10. Here, we touch on a very
`basic and important point that cannot be
`expanded in the context of this paper but
`which deserves to be stressed: with all our
`efforts to understand the molecular basis of
`drug action, we must not fall into the trap
`of reductionism. As Roald Hoffmann aptly
`said in his speech at the Nobel Banquet:
`
`“Chemistry reduced to its simplest terms,
`is not physics. Medicine is not chemistry ....
`knowledge of the specific physiological and
`eventually molecular sequence of events
`does not help us understand what [a] poet
`has to say to us.”
`
`With diseases such as type 1 diabetes, for
`example, the molecule insulin is indeed all
`that is needed to produce a cure, although
`we cannot imitate its regulated secre-
`tion. With diseases such as psychoses, for
`example, antipsychotic drugs might not
`correct nor even interfere with the aspect
`of the human constitution that is actually
`deranged, and with such drugs molecular
`determinism might be counterproductive
`to the use and development of therapeutic
`approaches. It is thought that rather
`than chemically providing a ‘cure’, these
`drugs make the patient more responsive
`to a therapy that acts at a different level.
`Reflections on molecular targets are very
`important because drugs are molecules,
`but it is important not to be too simplistic.
`Returning to the key question, what do
`we count as a target? In the search for molec-
`ular reaction partners of drug substances,
`we will have to be content with losing sight
`
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`Box 2 | One drug — many targets
`
`Over the past 20 years, drug approval authorities and many pharmacologists have moved away
`from combination therapies and asked for rational, single-drug, single-target therapies. This is
`understandable, as it rapidly becomes challenging to analyse the contributions of multiple drugs
`or those that hit multiple targets to the observed effects, both desirable and undesirable.
`The principle that blocking a single pharmacological target with high potency is desirable
`because it minimizes the side effects that come with non-specific drugs has become well-
`established, almost dogma, in drug development circles. However, a few examples will suffice to
`show that it is an oversimplification. First, despite the appeal of a single-drug-target strategy for
`drug development, the most effective anti-arrhythmic compound, amiodarone, is the ‘dirtiest’ of
`all anti-arrhythmics33. Second, the problems with highly selective cyclooxygenase-2-inhibitors are
`considered to be due to their very selectivity, which seems to tip the balance of pro- and anti-
`thrombotic mediators in an unfavourable way34. Third, propranolol is the first and classic
`β-sympatholytic agent, but it has neither an absolute selectivity for an adrenoceptor subtype nor
`does it address receptors exclusively; for example, it also inhibits phosphatidic acid
`phosphorylase. It is not clear whether the latter activity contributes to the net clinical effects
`(hypotension and so on)35. Fourth, oestrogens not only have an intracellular nuclear receptor,
`but also activate a membrane-bound one as well (GPR30)36. The effects of oestrogen result from
`the interplay of the two mechanisms. Fifth, for papaverine, a smooth-muscle relaxant agent,
`the following activities were recorded, and all seem to be important for the net effect: cyclic
`nucleotide phosphodiesterase inhibition, Ca2+-channel blockade and α-adrenoreceptor
`antagonism37. And last, the anticancer drug imatinib was originally moved into clinical
`development on the basis of its capacity to inhibit a single target: the BCR–ABL kinase. It has since
`become clear that its success could be linked to interaction with at least two other targets;
`indeed, two anticancer drugs, sorafenib and sunitinib, that were developed to inhibit multiple
`kinases have recently been approved. As with antipyschotics30, such ‘dirty’ or ‘promiscuous’
`anticancer drugs might be increasingly sought in the near future38.
`
`of some of the net biochemical and espe-
`cially clinical effects of the drug’s action. A
`target definition derived from the net effect
`rather than the direct chemical interaction
`will require input from systems biology, a
`nascent research field that promises to sig-
`nificantly affect the drug discovery process11.
`At the other end of the scale of precision, we
`can define some targets very precisely on the
`molecular level: for example, we can say that
`dihydropyridines block the CaV1.2a splic-
`ing variant in heart muscle cells of L-type
`high-voltage activated calcium channels.
`This is an example of a ‘micro-target’. It does
`make sense to define it because a subtype or
`even splicing variant selectivity could alter
`the effectiveness of calcium channel block-
`ers. We could further differentiate between
`genetic, transcriptional, post-transcriptional
`or age differences between individuals, and
`again this will make sense in some cases.
`But for a target count, a line needs to be
`drawn somewhere, otherwise the number of
`individual patients that receive a drug could
`be counted and equated with the number of
`known targets. In summary, we will count
`neither macro- nor micro-targets, but some-
`thing in between — admittedly a somewhat
`arbitrary distinction.
`
`Classification of current drugs
`There are a number of possible ways to
`classify drug substances (active pharma-
`ceutical ingredients). From the end of the
`
`nine-teenth century until the 1970s,
`drug substances were classified in the
`same way as other chemical entities:
`by the nature of their primary elements,
`functional moieties or organic substance
`class. Recently, the idea of classifying
`drug substances strictly according to their
`chemical constitution or structure has
`been revived. Numerous databases now
`attempt to gather and organize information
`on existing or potential drug substances
`according to their chemical structure
`and diversity. The objective is to create
`substance ‘libraries’ that contain pertinent
`information about possible ligands for
`new targets (for example, an enzyme or
`receptor) of clinical interest12,13 and,
`more importantly, to understand the
`systematics of molecular recognition14,15
`(ligand–receptor).
`
`In situations in which
`the dynamic actions of the
`drug substance stimulate, or
`inhibit, a biological process,
`it is necessary to move away
`from the descriptions of single
`proteins, receptors and so on
`and to view the entire signal
`chain as the target.
`
`P E R S P E C T I V E S
`
`At present, the most commonly used
`classification system for drug substances is
`the ATC system16 (see WHO Collaborating
`Centre for Drug Statistics Methodology,
`Further information). It categorizes drug
`substances at different levels: anatomy,
`therapeutic properties and chemical proper-
`ties. We recently proposed an alternative
`classification system17, although we did not
`follow it fully in the arrangement of entries
`in TABLES 1–8, BOX 1, as explained below.
`
`Classification of drug substances according
`to targets. In TABLES 1–8, we arranged drug
`substances according to their mechanism
`of action. Although the term ‘mechanism of
`action’ itself implies a classification
`according to the dynamics of drug sub-
`stance effects at the molecular level, the
`dynamics of these interactions are only
`speculative models at present, and so
`mechanism of action can currently only be
`used to describe static (micro)targets, as
`discussed above.
`The actual depth of detail used to define
`the target is primarily dependent on the
`amount of knowledge available about the
`target and its interactions with a drug.
`If the target structure has already been
`determined, it could still be that the
`molecular effect of the drug cannot be fully
`described by the interactions with one
`target protein alone. For example, anti-
`bacterial oxazolidinones interact with
`23S-rRNA, tRNA and two polypeptides,
`ultimately leading to inhibition of protein
`synthesis. In this case, a description of the
`mechanism of action that only includes
`interactions with the 23S-rRNA target would
`be too narrowly defined. In particular, in
`situations in which the dynamic actions of
`the drug substance stimulate, or inhibit, a
`biological process, it is necessary to move
`away from the descriptions of single pro-
`teins, receptors and so on and to view the
`entire signal chain as the target. Indeed,
`it has been pointed out by Swinney in an
`article on this topic that “two components
`are important to the mechanism of action ...
`The first component is the initial mass-
`action-dependent interaction ... The second
`component requires a coupled biochemi-
`cal event to create a transition away from
`mass-action equilibrium” and “drug mecha-
`nisms that create transitions to a non-
`equilibrium state will be more efficient”18.
`This consideration again stresses that dynam-
`ics are essential for effective drug action and,
`as discussed above, indicates that an effective
`drug target comprises a biochemical system
`rather than a single molecule.
`
`NATURE REVIEWS | DRUG DISCOVERY
`
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`
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`

`Activity of drug
`
`Drug examples
`
`P E R S P E C T I V E S
`
`Table 3a | Receptors
`Type
`Direct ligand-gated ion channel receptors
`GABAA receptors
`
`Acetylcholine receptors
`
`Glutamate receptors (ionotropic)
`
`G-protein-coupled receptors
`Acetylcholine receptors
`
`Adenosine receptors
`
`Adrenoceptors158,159
`
`Angiotensin receptors
`Calcium-sensing receptor
`
`Cannabinoid receptors
`Cysteinyl-leukotriene receptors
`Dopamine receptors166
`
`Barbiturate binding site agonists
`Benzodiazepine binding site agonists
`Benzodiazepine binding site antagonists
`Nicotinic receptor agonists
`Nicotinic receptor stabilizing antagonists
`Nicotinic receptor depolarizing antagonists
`Nicotinic receptor allosteric modulators
`NMDA subtype antagonists
`NMDA subtype expression modulators
`NMDA subtype phencyclidine binding site
`antagonists
`
`Muscarinic receptor agonists
`Muscarinic receptor antagonists
`Muscarinic receptor M3 antagonists
`Agonists
`Adenosine A1 receptor agonists
`Adenosine A1 receptor antagonists
`Adenosine A2A receptor antagonists
`Agonists
`1- and α2-receptors agonists
`
`α
`α
`1-receptor antagonists
`α
`2-receptor, central agonists
`β-adrenoceptor antagonists
`β
`1-receptor antagonists
`β
`2-receptor agonists
`β
`2-receptor antagonists
`AT1-receptors antagonists
`Agonists
`Allosteric activators
`CB1- and CB2-receptors agonists
`Antagonists
`Dopamine receptor subtype direct agonists
`D2, D3 and D4 agonists
`D2, D3 and D4 antagonists
`
`Barbiturate140
`Benzodiazepines141
`Flumazenil142
`Pyrantel (of Angiostrongylus), levamisole143,144
`Alcuronium145
`Suxamethonium146
`Galantamine147
`Memantine148
`Acamprosate149
`Ketamine150
`
`Pilocarpine151
`Tropane derivatives152,153
`Darifenacine154
`Adenosine155
`Lignans from valerian156
`Caffeine, theophylline
`Caffeine, theophylline157
`Adrenaline, noradrenaline, ephedrine
`Xylometazoline
`Ergotamine160
`Methyldopa (as methylnoradrenaline)
`Isoprenaline
`Propranolol, atenolol
`Salbutamol
`Propranolol
`Sartans161
`Strontium ions162
`Cinacalcet163
`Dronabinol164
`Montelukast165
`Dopamine, levodopa
`Apomorphine
`Chlorpromazine, fluphenazine, haloperidol,
`metoclopramide, ziprasidone
`Bosentan167
`Baclofen168
`Glucagon169
`Exenatide170
`Diphenhydramine171
`Cimetidine172
`Morphine, buprenorphine
`Naltrexone
`Buprenorphine
`
`Aprepitant175
`
`Endothelin receptors (ETA, ETB)
`GABAB receptors
`Glucagon receptors
`Glucagon-like peptide-1 receptor
`Histamine receptors
`
`Antagonists
`Agonists
`Agonists
`Agonists
`H1-antagonists
`H2-antagonists
`μ-opioid agonists
`μ-, κ- and δ-opioid antagonists
`κ-opioid antagonists
`NK1 receptor antagonists
`Neurokinin receptors
`GABA, γ-amino butyric acid; NMDA, N-methyl-d-aspartate.
`
`Opioid receptors173,174
`
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`

`Table 3b | Receptors
`Type
`Prostanoid receptors
`Prostamide receptors
`Purinergic receptors
`Serotonin receptors
`
`Vasopressin receptors184
`
`Cytokine receptors
`Class I cytokine receptors
`
`Activity of drug
`Agonists
`Agonists
`P2Y12 antagonists
`Subtype-specific (partial) agonists
`5-HT1A partial agonists
`5-HT1B/1D agonists
`5-HT2A antagonists
`5-HT3antagonists
`5-HT4 partial agonists
`Agonists
`V1 agonists
`V2 agonists
`OT agonists
`OT antagonists
`
`Growth hormone receptor antagonists
`Erythropoietin receptor agonists
`Granulocyte colony stimulating factor agonists
`Granulocyte-macrophage colony stimulating factor
`agonists
`Interleukin-1 receptor antagonists
`Interleukin-2 receptor agonists
`Mimetics (soluble)
`
`TNFα receptors
`Integrin receptors
`Antagonists
`Glycoprotein IIb/IIIa receptor
`Receptors associated with a tyrosine kinase
`Insulin receptor
`Direct agonists
`Insulin receptor
`Sensitizers
`Nuclear receptors (steroid hormone receptors)
`Mineralocorticoid receptor196
`Agonists
`Antagonists
`Agonists
`Agonists
`Agonists
`(Partial) antagonists
`Antagonists
`Modulators
`Agonists
`Antagonists
`Agonists
`Agonists
`
`Glucocorticoid receptor
`Progesterone receptor
`Oestrogen receptor199
`
`Androgen receptor201,202
`
`Vitamin D receptor205,206
`ACTH receptor agonists
`Nuclear receptors (other)
`Retinoic acid receptors
`
`RARα agonists
`RARβ agonists
`RARγ agonists
`PPARα agonists
`PPARγ agonists
`Agonists
`
`Peroxisome proliferator-activated
`receptor (PPAR)
`
`Thyroid hormone receptors
`ACTH, adrenocorticotropic hormone.
`
`P E R S P E C T I V E S
`
`Drug examples
`Misoprostol, sulprostone, iloprost176
`Bimatoprost177
`Clopidogrel178
`Ergometrine, ergotamine160
`Buspirone179
`Triptans180
`Quetiapine, ziprasidone181
`Granisetron182
`Tegaserode183
`Vasopressin
`Terlipressin185
`Desmopressin
`Oxytocin
`Atosiban
`
`Pegvisomant186
`Erythropoietin187
`Filgrastim188
`Molgramostim189
`
`Anakinra190
`Aldesleukin191
`Etanercept192
`
`Tirofiban193
`
`Insulin194
`Biguanides195
`
`Aldosterone
`Spironolactone
`Glucocorticoids197
`Gestagens198
`Oestrogens
`Clomifene
`Fulvestrant
`Tamoxifen, raloxifene200
`Testosterone203
`Cyproterone acetate204
`Retinoids207
`Tetracosactide (also known as cosyntropin) 208
`
`Isotretinoin209
`Adapalene, isotretinoin210
`Adapalene, isotretinoin210
`Fibrates211,212
`Glitazones213
`l-Thyroxine214
`
`NATURE REVIEWS | DRUG DISCOVERY
`
` VOLUME 5 | OCTOBER 2006 | 827
`
`© 2007 Nature Publishing Group
`
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`
`YEDA EXHIBIT NO. 2055
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`IPR2015-00643
`
`

`

`P E R S P E C T I V E S
`
`Table 4 | Ion channels
`Type
`Activity of drug
`Voltage-gated Ca2+ channels
`General
`Inhibitor
`In Schistosoma sp.
`Inhibitor
`L-type channels
`Inhibitor
`
`Inhibitor
`
`Opener
`Inhibitor
`Inhibitor
`
`Inhibitor
`
`Inhibitor
`
`Drug examples
`
`Oxcarbazepine216
`Praziquantel217
`Dihydropyridines, diltiazem, lercanidipine,
`pregabalin, verapamil218–223
`Succinimides224
`
`Diazoxide, minoxidil226,227
`Nateglinide, sulphonylureas228,229
`Amiodarone230
`
`T-type channels
`K+ channels225
`Epithelial K+
`channels
`Voltage-gated K+
`channels
`Na+ channels
`Amiloride, bupivacaine, lidocaine, procainamide,
`Epithelial Na+
`quinidine
`channels (ENaC)231
`Carbamazepine, flecainide, lamotrigine, phenytoin,
`Voltage-gated Na+
`propafenone, topiramate, valproic acid232–239
`channels
`Ryanodine-inositol 1,4,5-triphosphate receptor Ca2+ channel (RIR-CaC) family
`Ryanodine
`Inhibitor
`Dantrolene240,241
`receptors
`Transient receptor potential Ca2+ channel (TRP-CC) family
`TRPV1 receptors
`Inhibitor
`Acetaminophen (as arachidonylamide)242
`Cl– channels243
`Cl– channel
`
`Inhibitor (mast cells)
`Opener (parasites)
`TRPV, transient receptor potential vanilloid.
`
`Cromolyn sodium244
`Ivermectin245
`
`substances included in the thirteenth Model
`List of Essential Medicines published by the
`World Health Organization19 (excluding
`the categories: vitamins, minerals, oxygen
`as a