Drug discovery
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In the fields of medicine, biotechnology and pharmacology, drug discovery is the process by which drugs are discovered and/or designed.
In the past most drugs have been discovered either by identifying the active ingredient from traditional remedies or by serendipitous discovery. A new approach has been to understand how disease and infection are controlled at the molecular and physiological level and to target specific entities based on this knowledge.
The process of drug discovery involves the identification of candidates, synthesis, characterization, screening, and assays for therapeutic efficacy. Once a compound has shown its value in these tests, it will begin the process of drug development prior to clinical trials.
Despite advances in technology and understanding of biological systems, drug discovery is still a lengthy, "expensive, difficult, and inefficient process" with low rate of new therapeutic discovery.[1] Currently, the research and development cost of each new molecular entity (NME) is approximately US$1.8 billion.[2]
Information on the human genome, its sequence and what it encodes has been hailed as a potential windfall for drug discovery, promising to virtually eliminate the bottleneck in therapeutic targets that has been one limiting factor on the rate of therapeutic discovery.[citation needed] However, data indicates that "new targets" as opposed to "established targets" are more prone to drug discovery project failure in general[citation needed] This data corroborates some thinking underlying a pharmaceutical industry trend beginning at the turn of the twenty-first century and continuing today which finds more risk aversion in target selection among multi-national pharmaceutical companies.[citation needed]
Contents
Drug targets
The definition of "target" itself is something argued within the pharmaceutical industry. Generally, the "target" is the naturally existing cellular or molecular structure involved in the pathology of interest that the drug-in-development is meant to act on. However, the distinction between a "new" and "established" target can be made without a full understanding of just what a "target" is. This distinction is typically made by pharmaceutical companies engaged in discovery and development of therapeutics.
"Established targets" are those for which there is a good scientific understanding, supported by a lengthy publication history, of both how the target functions in normal physiology and how it is involved in human pathology. This does not imply that the mechanism of action of drugs that are thought to act through a particular established targets is fully understood. Rather, "established" relates directly to the amount of background information available on a target, in particular functional information. The more such information is available, the less investment is (generally) required to develop a therapeutic directed against the target. The process of gathering such functional information is called "target validation" in pharmaceutical industry parlance. Established targets also include those that the pharmaceutical industry has had experience mounting drug discovery campaigns against in the past; such a history provides information on the chemical feasibility of developing a small molecular therapeutic against the target and can provide licensing opportunities and freedom-to-operate indicators with respect to small-molecule therapeutic candidates.
In general, "new targets" are all those targets that are not "established targets" but which have been or are the subject of drug discovery campaigns. These typically include newly discovered proteins, or proteins whose function has now become clear as a result of basic scientific research.
The majority of targets currently selected for drug discovery efforts are proteins. Two classes predominate: G-protein-coupled receptors (or GPCRs) and protein kinases.
Screening and design
The process of finding a new drug against a chosen target for a particular disease usually involves high-throughput screening (HTS), wherein large libraries of chemicals are tested for their ability to modify the target. For example, if the target is a novel GPCR, compounds will be screened for their ability to inhibit or stimulate that receptor (see antagonist and agonist): if the target is a protein kinase, the chemicals will be tested for their ability to inhibit that kinase.
Another important function of HTS is to show how selective the compounds are for the chosen target. The ideal is to find a molecule which will interfere with only the chosen target, but not other, related targets. To this end, other screening runs will be made to see whether the "hits" against the chosen target will interfere with other related targets - this is the process of cross-screening. Cross-screening is important, because the more unrelated targets a compound hits, the more likely that off-target toxicity will occur with that compound once it reaches the clinic.
It is very unlikely that a perfect drug candidate will emerge from these early screening runs. It is more often observed that several compounds are found to have some degree of activity, and if these compounds share common chemical features, one or more pharmacophores can then be developed. At this point, medicinal chemists will attempt to use structure-activity relationships (SAR) to improve certain features of the lead compound:
- increase activity against the chosen target
- reduce activity against unrelated targets
- improve the "drug-like" or ADME properties of the molecule.
This process will require several iterative screening runs, during which, it is hoped, the properties of the new molecular entities will improve, and allow the favoured compounds to go forward to in vitro and in vivo testing for activity in the disease model of choice.
A range of parameters can be used to assess the quality of a compound, or a series of compounds, as proposed in the Lipinski's Rule of Five. Such parameters include calculated properties such as cLogP to estimate lipophilicity, molecular weight, polar surface area and measured properties, such as potency, in-vitro measurement of enzymatic clearance etc. Some descriptors such as Ligand Efficiency[3] (LE) and Lipophilic Efficiency[4][5] (LiPE) combine such parameters to assess druglikeness.
While HTS is a commonly used method for novel drug discovery, it is not the only method. It is often possible to start from a molecule which already has some of the desired properties. Such a molecule might be extracted from a natural product or even be a drug on the market which could be improved upon (so-called "me too" drugs). Other methods, such as virtual high throughput screening, where screening is done using computer-generated models and attempting to "dock" virtual libraries to a target, are also often used.
Another important method for drug discovery is drug design, whereby the biological and physical properties of the target are studied, and a prediction is made of the sorts of chemicals that might (eg.) fit into an active site. One example is fragment-based lead discovery (FBLD). Novel pharmacophores can emerge very rapidly from these exercises.
Once a lead compound series has been established with sufficient target potency and selectivity and favourable drug-like properties, one or two compounds will then be proposed for drug development. The best of these is generally called the lead compound, while the other will be designated as the "backup".
Historical background
The idea that effect of drug in human body are mediated by specific interactions of the drug molecule with biological macromolecules, (proteins or nucleic acids in most cases) led scientists to the conclusion that individual chemicals are required for the biological activity of the drug. This made for the beginning of the modern era in pharmacology, as pure chemicals, instead of crude extracts, became the standard drugs. Examples of drug compounds isolated from crude preparations are morphine, the active agent in opium, and digoxin, a heart stimulant originating from Digitalis lanata. Organic chemistry also led to the synthesis of many of the cochemicals isolated from biological sources.
Nature as source of drugs
Despite the rise of combinatorial chemistry as an integral part of lead discovery process, natural products still play a major role as starting material for drug discovery.[6] A report was published in 2007 [7], covering years 1981-2006 details the contribution of biologically occurring chemicals in drug development. According to this report, of the 974 small molecule new chemical entities, 63% were natural derived or semisynthetic derivatives of natural products. For certain therapy areas, such as antimicrobials, antineoplastics, antihypertensive and anti-inflammatory drugs, the numbers were higher.
Natural products may be useful as a source of novel chemical structures for modern techniques of development of antibacterial therapies.[8]
Despite the implied potential, only a fraction of Earth’s living species has been tested for bioactivity.
Plant-derived
Prior to Paracelsus, the vast majority of traditionally used crude drugs in Western medicine were plant-derived extracts. This has resulted in a pool of information about the potential of plant species as an important source of starting material for drug discovery. A different set of metabolites is sometimes produced in the different anatomical parts of the plant (e.g. root, leaves and flower), and botanical knowledge is crucial also for the correct identification of bioactive plant materials.
Microbial metabolites
Microbes compete for living space and nutrients. To survive in these conditions, many microbes have developed abilities to prevent competing species from proliferating. Microbes are the main source of antimicrobial drugs. Streptomyces species have been a source of antibiotics. The classical example of an antibiotic discovered as a defense mechanism against another microbe is the discovery of penicillin in bacterial cultures contaminated by Penicillium fungi in 1928.
Marine invertebrates
Marine environments are potential sources for new bioactive agents.[9] Arabinose nucleosides discovered from marine invertebates in 1950s, demonstrating for the first time that sugar moieties other than ribose and deoxyribose can yield bioactive nucleoside structures. However, it was 2004 when the first marine-derived drug was approved. The cone snail toxin ziconotide, also known as Prialt, was approved by the Food and Drug Administration to treat severe neuropathic pain. Several other marine-derived agents are now in clinical trials for indications such as cancer, anti-inflammatory use and pain. One class of these agents are bryostatin-like compounds,under investigation as anti-cancer therapy.
Chemical diversity of natural products
As above mentioned, combinatorial chemistry was a key technology enabling the efficient generation of large screening libraries for the needs of high-throughput screening. However, now, after two decades of combinatorial chemistry, it has been pointed out that despite the increased efficiency in chemical synthesis, no increase in lead or drug candidates has been reached [7]. This has led to analysis of chemical characteristics of combinatorial chemistry products, compared to existing drugs and/or natural products. The chemoinformatics concept chemical diversity, depicted as distribution of compounds in the chemical space based on their physicochemical characteristics, is often used to describe the difference between the combinatorial chemistry libraries and natural products. The synthetic, combinatorial library compounds seem to cover only a limited and quite uniform chemical space, whereas existing drugs and particularly natural products, exhibit much greater chemical diversity, distributing more evenly to the chemical space [6] . The most prominent differences between natural products and compounds in combinatorial chemistry libraries is the number of chiral centers (much higher in natural compounds), structure rigidity (higher in natural compounds) and number of aromatic moieties (higher in combinatorial chemistry libraries). Other chemical differences between these two groups include the nature of heteroatoms (O and N enriched in natural products, and S and halogen atoms more often present in synthetic compounds), as well as level of non-aromatic unsaturation (higher in natural products). As both structure rigidity and chirality are both well-established factors in medicinal chemistry known to enhance compounds specificity and efficacy as a drug, it has been suggested that natural products compare favourable to today's combinatorial chemistry libraries as potential lead molecules.
Natural product drug discovery
Screening
Two main approaches exist for the finding of new bioactive chemical entities from natural sources: random collection and screening of material; and exploitation of ethnopharmacological knowledge in the selection. The former approach is based on the fact that only a small part of Earth’s biodiversity has ever been tested for pharmaceutical activity, and organisms living in a species-rich environment need to evolve defensive and competitive mechanisms to survive. A collection of plant, animal and microbial samples from rich ecosystems might give rise to novel biological activities. One example of a successful use of this strategy is the screening for antitumour agents by the National Cancer Institute, started in the 1960s. Paclitaxel was identified from Pacific yew tree Taxus brevifolia. Paclitaxel showed anti-tumour activity by a previously undescribed mechanism (stabilization of microtubules) and is now approved for clinical use for the treatment of lung, breast and ovarian cancer, as well as for Kaposi's sarcoma.
Ethnobotany is the study of the use of plants in the society, and ethnopharmacology, an area inside ethnobotany, is focused on medicinal use of plants. Both can be used in selecting starting materials for future drugs. Artemisinin, an antimalarial agent from sweet wormtree Artemisia annua, used in Chinese medicine since 200BC is one drug used as part of combination therapy for multiresistant Plasmodium falciparum.
Structural elucidation
The elucidation of the chemical structure is critical to avoid the re-discovery of a chemical agent that is already known for its structure and chemical activity. Mass spectrometry, often used to determine structure, is a method in which individual compounds are identified based on their mass/charge ratio, after ionization. Chemical compounds exist in nature as mixtures, so the combination of liquid chromatography and mass spectrometry (LC-MS) is often used to separate the individual chemicals. Databases of mass spectras for known compounds are available. Nuclear magnetic resonance spectroscopy is another important technique for determining chemical structures of natural products. NMR yields information about individual hydrogen and carbon atoms in the structure, allowing detailed reconstruction of the molecule’s architecture.
See also
- Antitarget
- Drug Discovery Hit to Lead see discussion for MERGE suggestion
- Drug development
- Pre-clinical development
- Protein structure prediction
- Drug design
- Rational drug design
- Drug metabolism
- Compound management
- Bioinformatics
- Cheminformatics
- Biomedical informatics
- Orphan drug
- Pharmaceutical company
- Pharmacognosy
- Physiologically-based pharmacokinetic modelling
- Simcyp Simulator
- Pharmacogenetics
- Simulations Plus
- High-throughput screening
- Natural product
- Molecular modelling
- Molecular Conceptor
References
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Further reading
- Gad, Shayne C. (2005). Drug discovery handbook. Hoboken, N.J: Wiley-Interscience/J. Wiley. ISBN 0-471-21384-5.
- Madsen, Ulf; Krogsgaard-Larsen, Povl; Liljefors, Tommy (2002). Textbook of drug design and discovery. Washington, DC: Taylor & Francis. ISBN 0-415-28288-8.
External links
- Introduction to Drug Discovery - Combinatorial Chemistry Review
- In Focus "Medical Research involving Minors: Medical, legal and ethical aspects" (German Reference Centre for Ethics in the Life Sciences)
- International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH)
- Food and Drug Administration (FDA)
- CDER Drug and Biologic Approval Reports
- Pharmaceutical Research and Manufacturers of America (PhRMA)
- European Medicines Agency (EMEA)
- Pharmaceuticals and Medical Devices Agency (PMDA)
- WHO Model List of Essential Medicines
- Innovation and Stagnation: Challenge and Opportunity on the Critical Path to New Medical Products - FDA
- Priority Medicines for Europe and the World Project "A Public Health Approach to Innovation" - WHO
- International Union of Basic and Clinical Pharmacology
- IUPHAR Committee on Receptor Nomenclature and Drug Classification
- Advanced Cell Classifier program for high-content screen analysis (ETH Zurich)
- Drugdiscovery@home Early in silico drug discovery by volunteer computing.
- In the Pipeline Blog on drug discovery by medicinal chemist Derek Lowe.
- Drug Information Association (DIA)
- ↑ Anson, Blake D.; Ma, Junyi; He, Jia-Qiang (1 May 2009). "Identifying Cardiotoxic Compounds". Genetic Engineering & Biotechnology News. TechNote. 29 (9). Mary Ann Liebert. pp. 34–35. ISSN 1935-472X. OCLC 77706455. Archived from the original on 25 July 2009. Retrieved 25 July 2009.
- ↑ Steven M. Paul, Daniel S. Mytelka, Christopher T. Dunwiddie, Charles C. Persinger, Bernard H. Munos, Stacy R. Lindborg & Aaron L. Schacht (2010). "How to improve R&D productivity: the pharmaceutical industry's grand challenge". Nature Reviews Drug Discovery. 9 (3): 203–214. doi:10.1038/nrd3078. PMID 20168317.
- ↑ Hopkins, A. L., Groom, C. R. and Alexander, A. (2004). "Ligand efficiency: a useful metric for lead selection". Drug Discovery Today. 9 (10): 430–431. doi:10.1016/S1359-6446(04)03069-7. PMID 15109945.
- ↑ Ryckmans, T.; et al. (2009). "Rapid assessment of a novel series of selective CB2 agonists using parallel synthesis protocols: A Lipophilic Efficiency (LipE) analysis". Bioorg. Med. Chem. Lett. 19 (15): 4406–4409. doi:10.1016/j.bmcl.2009.05.062. PMID 19500981.
- ↑ Leeson, P. D.; et al. (2007). "The influence of drug-like concepts on
decision-making in medicinal chemistry". Nat. Rev. Drug Disc. 7 (11): 881–890. doi:10.1038/nrd2445. PMID 17971784. line feed character in
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at position 39 (help) - ↑ 6.0 6.1 Feher M, Schmidt JM (2003). "Property distributions: differences between drugs, natural products, and molecules from combinatorial chemistry". J Chem Inf Comput Sci. 43 (1): 218–27. doi:10.1021/ci0200467. PMID 12546556.
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