Perspective

Nature Reviews Drug Discovery 5, 821-834 (October 2006) | doi:10.1038/nrd2132

There is a Corrigendum (1 February 2007) associated with this article.

OpinionDrugs, their targets and the nature and number of drug targets

Peter Imming1, Christian Sinning1 & Achim Meyer1  About the authors

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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 approx8,000 targets of pharmacological interest, of which nearly 5,000 could be potentially hit by traditional drug substances, nearly 2,400 by antibodies and approx800 by protein pharmaceuticals2. And on the basis of ligand-binding studies, 399 molecular targets were identified belonging to 130 protein families, and approx3,000 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 1,2,3,4,5,6,7,8, Box 1), to estimate the number of known drug targets, in the following categories:









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 constraints. First, the medicinal goal excludes pharmacological and biochemical tools from the present approach. Second, a major constraint is a lack of technique. Life, including disease, is dynamic, but as we do not yet directly observe the interactions of drugs and targets, and only partly notice the subsequent 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 literature 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 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 disturbed. 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 simulation of pharmacodynamic drug–drug interactions was published recently6, highlighting the complexity of interaction analyses for biological systems. Awareness is also increasing of the nonlinear correlation 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 modifications of the active centre (for example, acetylation of bacterial transpeptidases by beta-lactam antibiotics); allosteric modulation (for example, benzodiazepine modulation of GABA (gamma-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 indirectly 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 beta-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). 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 secretion. 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 molecular reaction partners of drug substances, we will have to be content with losing sight of some of the net biochemical and especially 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 significantly 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 splicing 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 blockers. 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 something in between — admittedly a somewhat arbitrary distinction.

Classification of current drugs

There are a number of possible ways to classify drug substances (active pharmaceutical 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.

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 properties. We recently proposed an alternative classification system17, although we did not follow it fully in the arrangement of entries in Tables 1,2,3,4,5,6,7,8, Box 1, as explained below.

Classification of drug substances according to targets. In Tables 1,2,3,4,5,6,7,8, 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 substance 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, antibacterial 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 proteins, 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 biochemical event to create a transition away from mass-action equilibrium" and "drug mechanisms that create transitions to a non-equilibrium state will be more efficient"18. This consideration again stresses that dynamics 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.

A further criterion needed for the full categorization of drug substances according to their target is the anatomical localization of the target. This is essential for a differentiation between substances with the same biochemical target, but a different organ specificity (for example, nifedipine and verapamil are both L-type calcium channel inhibitors; the former interacts primarily with vascular calcium channels and the latter with cardiac calcium channels). However, in the tables, we chose not to include this criterion as it would have made the list more cumbersome.

Categorization of current drugs. We began by sorting substances according to their target, considering the following biochemical structures to be target families: 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); and unknown mechanism of action (Box 1).

Within the families, individual enzymes, receptors and so on were included if they were identified in the literature as the main target(s) of an approved drug substance. We filled the list shown in Tables 1,2,3,4,5,6,7,8, Box 1 by including the following drugs and their corresponding main targets: all substances included in the thirteenth Model List of Essential Medicines published by the World Health Organization19 (excluding the categories: vitamins, minerals, oxygen as a narcotic gas, and diagnostics); drug substances included in the FDA's Approved Drug Products list (25th edition, 2005)20; all newly developed drugs from the past 5 years introduced on the German market21; and drugs approved by the FDA in 2004 with a new mechanism of action, again excluding substitution therapeuticals22. We checked the resulting list against the lists of targets in Drews and Ryser's paper1, a list of enzyme targets in the supplemental material to Robertson's paper23, and a compilation of receptors produced for nomenclature purposes24, and we further supplemented our list using the current edition of Mutschler's German textbook Drug Actions25.

In this way, Tables 1,2,3,4,5,6,7,8, Box 1 include only those targets relevant for the effect of drugs currently on the market. For drug substances or classes in the lists, selected references are given that are concerned with the mechanism of action; the references are arranged by target family and subfamily, and within the subfamilies, alphabetically. New targets and mechanisms of action were not listed if a corresponding drug that interacts with the target has not yet been marketed. Drugs currently undergoing clinical trials have been excluded for the sake of briefness and also because of the numerous status fluctuations of such drugs.

It should be noted that for a certain target, we did not include all drug substances that address it, but just a representative example of the structural classes in use. In some cases, such as the beta-lactams, we cited the structural class instead of individual representatives. We tried to name the first substance of a class, if it is still marketed.

A subdivision of the major groups according to the 'anatomy' (cell type or physiological functional unit within which the target is located and acted on by the drug) and the substance class has been carried out in just a few cases for which the literature seemed to be unanimous about the identification and relevance of such a subdivision. In order to keep Tables 1,2,3,4,5,6,7,8, Box 1 readable, the main focus has been given to the classification of the substance according to its biochemical target.

A categorization going into further detail is outside the scope of this article, although of course obtaining further molecular and cellular detail is possible in some cases. For example, transport proteins have been subclassified in great detail26, 27, and target lists have been produced for cancer drugs28. An extensive list of affinities of CNS drugs for vast numbers of targets is also available online at the PDSP Database (see Further information). The latter list illustrates well the point discussed previously: that in many cases it will not help to know a single target, because the clinical effect is caused by patterns of target interactions.

Of course, our list is an approximation. And a categorization of compounds according to their mechanism of action will inevitably lead to a group of remaining drugs with proven clinical effectiveness, but an unknown molecular target. Such compounds can, if at all, only hypothetically be classified within the selected major groups. The ATC classification system, with its systematic categorization according to therapeutic aspects (for example, 'analgesics') does not have this problem, as every substance in the list shows — or is claimed to show — a therapeutic effect. It will also be the case that, as with the ATC system, certain drug substances appear more than once in the list. Indeed, it will happen more often than in the ATC system, owing to the fact that some drug effects are based on the synergistic effects of more than one mechanism of action.

The number of drug targets

At the level of target definition we chose, which is illustrated by the table rows, we counted 218 targets. The most prominent target families included hydrolases in the enzyme family, GPCRs in the receptor family and voltage-gated Ca2+ channels in the ion-channel family. The usefulness of a target family in this count is probably a consequence of its commonness, the format of assays (with recent binding-affinity based assays having contributed little as yet), and the nature of the diseases that affect the developed world.

A large part of this paper is concerned with the nature of drug targets and the need to consider the dynamics of the drug–targets (plural intended) interactions, as these considerations were used to define what we would eventually count. Many successful drugs have emerged from the simplistic 'one drug, one target, one disease' approach that continues to dominate pharmaceutical thinking, and we have generally used this approach when counting targets here. However, there is an increasing readiness to challenge this paradigm29, 30, 31, 32. We have discussed its constraints and limitations in light of the emerging network view of targets. The recent progress made in our understanding of biochemical pathways and their interaction with drugs is impressive. However, it may be that 'the more you know, the harder it gets'. It is not the final number of targets we counted that is the most important aspect of this Perspective; rather, we stress how considerations about what to count can help us gauge the scope and limitations of our understanding of the molecular reaction partners of active pharmaceutical ingredients. Targets are highly sophisticated, delicate regulatory pathways and feedback loops but, at present, we are still mainly designing drugs that can single out and, as we tellingly say, 'hit' certain biochemical units — the simple definable, identifiable targets as described here. This is not as much as we might have hoped for, but in keeping with the saying of one of the earliest medical practitioners, Hippocrates: "Life is short, and art long; the crisis fleeting; experience perilous, and decision difficult." Humility remains important in medical and pharmaceutical sciences and practice.

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Acknowledgements

We thank the following colleagues for help with compiling the first draft: T. Bubeta, L. Ann Bailey, H. Morck, M. Ramadan and T. Rogosch (Fachbereich Pharmazie, Universität Marburg, Germany), and C. Oehler and R. Schneider (Institut für Pharmazie, Universität Halle, Germany).

Competing interests statement

The authors declare no competing financial interests.

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Author affiliations

  1. Peter Imming, Christian Sinning and Achim Meyer are at Institut für Pharmazie, Martin-Luther-Universität Halle-Wittenberg, 06120 Halle, Germany.

Correspondence to: Peter Imming1 Email: peter.imming@pharmazie.uni-halle.de