Sunday, April 17, 2011

THE NATURE OF DRUG TARGET

THE NATURE OF DRUG TARGET
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 data, 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 .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 .

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 recently, 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 signals Another paper reported dopamine fluctuations after administration of cocaine, followed by a gradual increase in steady-state dopamine concentration.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 -lactam antibiotics); allosteric modulation (for example, benzodiazepine modulation of GABA ( -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 agents); 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 -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 indication
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 interest and, more importantly, to understand the systematics of molecular recognition (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 system.
Classification of drug substances according to targets. 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,
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". 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.
The number of drug 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.
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. 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.

DRUG AND DRUG TARGET

DRUGS AND DRUG TARGETS


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 .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 pharmaceuticals. 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 genome.
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 to estimate the number of known drug targets, in the following categories:
Type
Activity of drug
Drug examples
Oxidoreductases
Aldehyde dehydrogenase
Inhibitor
Disulfiram
Monoamine oxidases (MAOs)
MAO-A inhibitor
Tranylcypromine, moclobemide

MAO-B inhibitor
Tranylcypromine
Cyclooxygenases (COXs)
COX1 inhibitor
Acetylsalicylic acid, profens, acetaminophen and dipyrone (as arachidonylamides)

COX2 inhibitor
Acetylsalicylic acid, profens, acetaminophen and dipyrone (as arachidonylamides)
Vitamin K epoxide reductase
Inhibitor
Warfarin, phenprocoumon
Aromatase
Inhibitor
Exemestane
Lanosterol demethylase (fungal)
Inhibitor
Azole antifungals
Lipoxygenases
Inhibitor
Mesalazine

5-lipoxygenase inhibitor
Zileuton
Thyroidal peroxidase
Inhibitor
Thiouracils
Iodothyronine-5' deiodinase
Inhibitor
Propylthiouracil
Inosine monophosphate dehydrogenase
Inhibitor
Mycophenolate mofetil
HMG-CoA reductase
Inhibitor
Statins
5 -Testosterone reductase
Inhibitor
Finasteride, dutasteride
Dihydrofolate reductase (bacterial)
Inhibitor
Trimethoprim
Dihydrofolate reductase (human)
Inhibitor
Methotrexate, pemetrexed
Dihydrofolate reductase (parasitic)
Inhibitor
Proguanil
Dihydroorotate reductase
Inhibitor
Leflunomide
Enoyl reductase (mycobacterial)
Inhibitor
Isoniazid
Squalene epoxidase (fungal)
Inhibitor
Terbinafin
14 reductase (fungal)
Inhibitor
Amorolfin
Xanthine oxidase
Inhibitor
Allopurinol
4-Hydroxyphenylpyruvate dioxygenase
Inhibitor
Nitisinone
Ribonucleoside diphosphate reductase
Inhibitor
Hydroxycarbamide
Transferases
Protein kinase C
Inhibitor
Miltefosine
Bacterial peptidyl transferase
Inhibitor
Chloramphenicol
Catecholamine-O-methyltransferase
Inhibitor
Entacapone
RNA polymerase (bacterial)
Inhibitor
Ansamycins
Reverse transcriptases (viral)
Competitive inhibitors
Zidovudine

Allosteric inhibitors
Efavirenz
DNA polymerases
Inhibitor
Acyclovir, suramin
GABA transaminase
Inhibitor
Valproic acid vigabatrin
Tyrosine kinases
PDGFR/ABL/KIT inhibitor
Imatinib

EGFR inhibitor
Erlotinib

VEGFR2/PDGFR /KIT/FLT3
Sunitinib

VEGFR2/PDGFR /RAF
Sorafenib
Glycinamide ribonucleotide formyl transferase
Inhibitor
Pemetrexed
Phosphoenolpyruvate transferase (MurA, bacterial)
Inhibitor
Fosfomycin
Human cytosolic branched-chain aminotransferase (hBCATc)
Inhibitor
Gabapentin
Hydrolases (proteases)
Aspartyl proteases (viral)
HIV protease inhibitor
Saquinavir, indinavir
Hydrolases (serine proteases)
Unspecific
Unspecific inhibitors
Aprotinine
Bacterial serine protease
Direct inhibitor
-lactams
Bacterial serine protease
Indirect inhibitor
Glycopeptides
Bacterial lactamases
Direct inhibitor
Sulbactam
Human antithrombin
Activator
Heparins
Human plasminogen
Activator
Streptokinase
Human coagulation factor
Activator
Factor IX complex, Factor VIII
Human factor Xa
Inhibitor
Fondaparinux
Hydrolases (metalloproteases)
Human ACE
Inhibitor
Captopril
Human HRD
Inhibitor
Cilastatin
Human carboxypeptidase A (Zn)
Inhibitor
Penicillamine
Human enkephalinase
Inhibitor
Racecadotril
Hydrolases (other)
26S proteasome
Inhibitor
Bortezomib
Esterases
AChE inhibitor
Physostigmine

AChE reactivators
Obidoxime

PDE inhibitor
Caffeine

PDE3 inhibitor
Amrinon, milrinone

PDE4 inhibitor
Papaverine

PDE5 inhibitor
Sildenafil

HDAC inhibitor
Valproic acid

HDAC3/HDAC7 inhibitor
Carbamezepine
Glycosidases (viral)
-glycosidase inhibitor
Zanamivir, oseltamivir
Glycosidases (human)
-glycosidase inhibitor
Acarbose
Lipases
Gastrointestinal lipases inhibitor
Orlistat
Phosphatases
Calcineurin inhibitor
Cyclosporin

Inositol polyphosphate phosphatase inhibitor
Lithium ions
GTPases
Rac1 inhibitor
6-Thio-GTP (azathioprine metabolite)
Phosphorylases
Bacterial C55-lipid phosphate dephosphorylase inhibitor
Bacitracin
Lyases
DOPA decarboxylase
Inhibitor
Carbidopa
Carbonic anhydrase
Inhibitor
Acetazolamide
Histidine decarboxylase
Inhibitor
Tritoqualine
Ornithine decarboxylase
Inhibitor
Eflornithine
Soluble guanylyl cyclase
Activator
Nitric acid esters, molsidomine
Isomerases
Alanine racemase
Inhibitor
D-Cycloserine
DNA gyrases (bacterial)
Inhibitor
Fluoroquinolones
Topoisomerases
Topoisomerase I inhibitor
Irinotecan

Topoisomerase II inhibitor
Etoposide
8,7 isomerase (fungal)
Inhibitor
Amorolfin
Ligases (also known as synthases)
Dihydropteroate synthase
Inhibitor
Sulphonamides
Thymidylate synthase (fungal and human)
Inhibitor
Fluorouracil
Thymidylate synthase (human)
Inhibitor
Methotrexate, pemetrexed
Phosphofructokinase
Inhibitor
Antimony compounds
mTOR
Inhibitor
Rapamycin
Haem polymerase (Plasmodium)
Inhibitor
Quinoline antimalarials
1,3- -D-glucansynthase (fungi)
Inhibitor
Caspofungin
Glucosylceramide synthase
Inhibitor
Miglustat
TABLE 2 | Receptors
Type
Activity of drug
Drug examples
Direct ligand-gated ion channel receptors
GABAA receptors
Barbiturate binding site agonists
Barbiturate

Benzodiazepine binding site agonists
Benzodiazepines

Benzodiazepine binding site antagonists
Flumazenil
Acetylcholine receptors
Nicotinic receptor agonists
Pyrantel (of Angiostrongylus), levamisole

Nicotinic receptor stabilizing antagonists
Alcuronium

Nicotinic receptor depolarizing antagonists
Suxamethonium

Nicotinic receptor allosteric modulators
Galantamine
Glutamate receptors (ionotropic)
NMDA subtype antagonists
Memantine

NMDA subtype expression modulators
Acamprosate

NMDA subtype phencyclidine binding site antagonists
Ketamine
G-protein-coupled receptors
Acetylcholine receptors
Muscarinic receptor agonists
Pilocarpine

Muscarinic receptor antagonists
Tropane derivatives

Muscarinic receptor M3 antagonists
Darifenacine
Adenosine receptors
Agonists
Adenosine

Adenosine A1 receptor agonists
Lignans from valerian

Adenosine A1receptor antagonists
Caffeine, theophylline

Adenosine A2A receptor antagonists
Caffeine, theophylline
Adrenoceptors
Agonists
Adrenaline, noradrenaline, ephedrine

1- and 2-receptors agonists
Xylometazoline

1-receptor antagonists
Ergotamine

2-receptor, central agonists
Methyldopa (as methylnoradrenaline)

-adrenoceptor antagonists
Isoprenaline

1-receptor antagonists
Propranolol, atenolol

2-receptor agonists
Salbutamol

2-receptor antagonists
Propranolol
Angiotensin receptors
AT1-receptors antagonists
Sartans
Calcium-sensing receptor
Agonists
Strontium ions

Allosteric activators
Cinacalcet
Cannabinoid receptors
CB1 - and CB2-receptors agonists
Dronabinol
Cysteinyl-leukotriene receptors
Antagonists
Montelukast
Dopamine receptors166
Dopamine receptor subtype direct agonists
Dopamine, levodopa

D2, D3 and D4 agonists
Apomorphine

D2, D3 and D4 antagonists
Chlorpromazine, fluphenazine, haloperidol, metoclopramide, ziprasidone
Endothelin receptors (ETA, ETB)
Antagonists
Bosentan
GABAB receptors
Agonists
Baclofen
Glucagon receptors
Agonists
Glucagon
Glucagon-like peptide-1 receptor
Agonists
Exenatide
Histamine receptors
H1-antagonists
Diphenhydramine

H2-antagonists
Cimetidine
Opioid receptors173, 174
-opioid agonists
Morphine, buprenorphine

-, - and -opioid antagonists
Naltrexone

-opioid antagonists
Buprenorphine
Neurokinin receptors
NK1 receptor antagonists
Aprepitant
Prostanoid receptors
Agonists
Misoprostol, sulprostone, iloprost
Prostamide receptors
Agonists
Bimatoprost
Purinergic receptors
P2Y12 antagonists
Clopidogrel
Serotonin receptors
Subtype-specific (partial) agonists
Ergometrine, ergotamine

5-HT1A partial agonists
Buspirone

5-HT1B/1D agonists
Triptans

5-HT2A antagonists
Quetiapine, ziprasidone

5-HT3 antagonists
Granisetron

5-HT4 partial agonists
Tegaserode
Vasopressin receptors184
Agonists
Vasopressin

V1 agonists
Terlipressin

V2 agonists
Desmopressin

OT agonists
Oxytocin

OT antagonists
Atosiban
Cytokine receptors
Class I cytokine receptors
Growth hormone receptor antagonists
Pegvisomant

Erythropoietin receptor agonists
Erythropoietin

Granulocyte colony stimulating factor agonists
Filgrastim

Granulocyte-macrophage colony stimulating factor agonists
Molgramostim

Interleukin-1 receptor antagonists
Anakinra

Interleukin-2 receptor agonists
Aldesleukin
TNF receptors
Mimetics (soluble)
Etanercept
Integrin receptors
Glycoprotein IIb/IIIa receptor
Antagonists
Tirofiban
Receptors associated with a tyrosine kinase
Insulin receptor
Direct agonists
Insulin
Insulin receptor
Sensitizers
Biguanides
Nuclear receptors (steroid hormone receptors)
Mineralocorticoid receptor196
Agonists
Aldosterone

Antagonists
Spironolactone
Glucocorticoid receptor
Agonists
Glucocorticoids
Progesterone receptor
Agonists
Gestagens
Oestrogen receptor199
Agonists
Oestrogens

(Partial) antagonists
Clomifene

Antagonists
Fulvestrant

Modulators
Tamoxifen, raloxifene

Androgen receptor201, 202 Agonists
Testosterone

Antagonists
Cyproterone acetate
Vitamin D receptor205, 206
Agonists
Retinoids
ACTH receptor agonists
Agonists
Tetracosactide (also known as cosyntropin)
Nuclear receptors (other)

Retinoic acid receptors RAR agonists
Isotretinoin

RAR agonists
Adapalene, isotretinoin

RAR agonists
Adapalene, isotretinoin
Peroxisome proliferator-activated receptor (PPAR)
PPAR agonists
Fibrates

PPAR agonists
Glitazones
Thyroid hormone receptors
Agonists
L-Thyroxine
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TABLE 3 | Ion channels
|
Type
Activity of drug
Drug examples
Voltage-gated Ca2+ channels
General
Inhibitor
Oxcarbazepine
In Schistosoma sp.
Inhibitor
Praziquantel
L-type channels
Inhibitor
Dihydropyridines, diltiazem, lercanidipine, pregabalin, verapamil
T-type channels
Inhibitor
Succinimides
K+ channels225
Epithelial K+ channels
Opener Inhibitor
Diazoxide, minoxidilNateglinide, sulphonylureas
Voltage-gated K+ channels
Inhibitor
Amiodarone
Na+ channels
Epithelial Na+ channels (ENaC)231
Inhibitor
Amiloride, bupivacaine, lidocaine, procainamide, quinidine
Voltage-gated Na+ channels
Inhibitor
Carbamazepine, flecainide, lamotrigine, phenytoin, propafenone, topiramate, valproic acid,  
Ryanodine-inositol 1,4,5-triphosphate receptor Ca2+ channel (RIR-CaC) family
Ryanodine receptors
Inhibitor
Dantrolene
Transient receptor potential Ca2+ channel (TRP-CC) family
TRPV1 receptors
Inhibitor
Acetaminophen (as arachidonylamide)
Cl- channels243
Cl-channel
Inhibitor (mast cells) Opener (parasites)
Cromolyn sodium Ivermectin
·        
TABLE 4 | Transport proteins (uniporters, symporters and antiporters)
Type
Activity of drug
Drug examples
Cation-chloride cotransporter (CCC) family247
Thiazide-sensitive NaCl symporter, human inhibitor
Thiazide diuretics

Bumetanide-sensitive NaCl/KCl symporters, human inhibitor
Furosemide
Na+/H+ antiporters
Inhibitor
Amiloride, triamterene
Proton pumps
Ca2+-dependent ATPase (PfATP6; Plasmodia) inhibitor
Artemisinin and derivatives
H+/K+-ATPase
Inhibitor
Omeprazole
Na+/K+ ATPase
Inhibitor
Cardiac glycosides
Eukaryotic (putative) sterol transporter (EST) family
Niemann-Pick C1 like 1 (NPC1L1) protein inhibitor
Ezetimibe
Neurotransmitter/Na+ symporter (NSS) family257, 258
Serotonin/Na+ symporter inhibitor
Cocaine, tricyclic antidepressants, paroxetine

Noradrenaline/Na+ symporter inhibitor
Bupropion, venlafaxine

Dopamine/Na+ symporter inhibitor
Tricyclic antidepressants, cocaine, amphetamines

Vesicular monoamine transporter inhibitor
Reserpine

|
TABLE 5 | DNA/RNA and the ribosome

Target
Activity of drug
Example drugs
Nucleic acids
DNA and RNA265
Alkylation
Chlorambucil, cyclophosphamide, dacarbazine

Complexation
Cisplatin

Intercalation
Doxorubicin

Oxidative degradation
Bleomycin

Strand breaks
Nitroimidazoles
RNA
Interaction with 16S-rRNA
Aminoglycoside antiinfectives

Interaction with 23S-rRNA
Macrolide antiinfectives

23S-rRNA/tRNA/2-polypeptide complex
Oxazolidinone antiinfectives
Spindle
Inhibition of development
Vinca alkaloids

Inhibition of desaggregation
Taxanes
Inhibition of mitosis
Colchicine
Ribosome
30S subunit (bacterial)
Inhibitors
Tetracyclines
50S subunit (bacterial)
Inhibitors
Lincosamides, quinupristin– dalfopristin282, 283
TABLE 6 | Targets of monoclonal antibodies
|
Target
Agent
Vascular endothelial growth factor
Bevacizumab
Lymphocyte function-associated antigen 1
Efalizumab
Epidermal growth factor receptor
Cetuximab
Human epidermal growth factor receptor 2
Trastuzumab
Immunoglobulin E (IgE)
Omalizumab
CD-3
Muromonab-CD3
CD-20
Rituximab, ibritumomab tiuxetan, 131I-tositumomab
CD-33
Gemtuzumab
CD-52
Alemtuzumab
F protein of RSV subtypes A and B
Palivizumab
CD-25
Basiliximab, daclizumab
Tumour-necrosis factor-
Adalimumab, infliximab
Glycoprotein IIb/IIIa receptor
Abciximab
4-Integrin subunit
Natalizumab
·        
TABLE 7 | Various physicochemical mechanisms
|
Mechanism
Agent
Ion exchange
Fluoride
Acid binding
Magnesium hydroxide, aluminium hydroxide
Adsorptive
Charcoal, colestyramine
Adstringent
Bismuth compounds
Surface-active
Simeticone, chlorhexidine, chloroxylene
Surface-active on cell membranes
Coal tar
Surface-active from fungi
Nystatin, amphotericin B
Mucosal irritation
Anthrones, anthraquinones
Osmotically active
Lactulose, dextran 70, polygeline, glucose, electrolyte solutions, mannitol
Water binding
Urea, ethanol
UV absorbant
4-Aminobenzoic acid derivatives
Reflective
Zinc oxide, titanium dioxide
Oxidative
Tannines, polyphenoles, dithranol, polyvidon iodide, silver nitrate, hypochlorite, permanganate, benzoylperoxide, nitroimidazoles, nitrofuranes, temoporfin (mainly via singlet oxygen, cytostatic drug), verteporfin (mainly via singlet oxygen, ophthalmic drug)
Reduce disulphide bridges
D-Penicillamine, N-acetyl-cysteine
Complexing agents
Al3+, arsenic compounds
Salt formation
Sevelamer
Modification of tertiary structure
Enfuvirtide (from HIV glycoprotein 41)