- Email: [email protected]
Medicinal Bioprospecting of the Amazon Rainforest: A Modern Eldorado?
Opinion
Medicinal Bioprospecting of the Amazon Rainforest: A Modern Eldorado? Aleksandra Skirycz,1,4,* Sylwia Kierszniowska,2 Michaël Méret,2 Lothar Willmitzer,1 and George Tzotzos3,4 Ignorant of the New World, Europeans believed in El Dorado, a hidden city of immense wealth in gold. Many consider the Amazonian forest to be a medicinal treasure chest and potentially the largest drug dispensary in the world. Yet, the quest to obtain drugs from indigenous tropical plants remains elusive. Here, we assess the potential of new technologies to tap into the metabolic diversity of tropical plants. We also consider how regulations affect access to plant resources. We conclude that, although the road to this medicinal El Dorado may be long and arduous, many other smaller but still valuable finds are hidden along the way.
Trends Metabolomics can speed up the identification of natural product scaffolds used in combinatorial chemistry, thus expanding the value of combinatorial chemistry libraries. Improved efficiency of dereplication toolkits is likely to accelerate drug discovery.
The Shifting Paradigms in Small-Molecule Drug Discovery
Novel methods to track protein–metabolite interactions in a cell-wide manner can be exploited to assist natural drug discovery.
The Amazonian rainforests are known to harbor the largest plant diversity in the world, with an estimated 30 000 vascular plant species [1,2]. Although numerous Amazonian plants have been screened for secondary metabolites, it can be argued that our current knowledge of the chemical diversity of the Amazonian plant biome represents only a fraction of that diversity [3].
Genetic engineering can help to reconstitute plant biosynthetic pathways in simple organisms, such as yeast, thus overcoming supply problems with natural products.
Here, we examine how new technologies can be applied to explore the chemical diversity of tropical plants, and how challenges posed by the complex interplay between metabolism, genetic, and environmental factors can be turned into bioprospecting (see Glossary) opportunities. We focus on emergent applications of metabolomics, small molecule–protein interactomics, and chemoinformatics, because these are particularly relevant in drug discovery efforts. We also discuss how regulatory policies affect access to plant resources and consequently affect technology transfer. We use Brazil as a case in point because it is a country with one of the richest biodiversities in the world, and has adequate research and regulatory oversight capacities. Crude drugs and other herbal formulations from medicinal plants have been used for thousands of years and are still used widely in many parts of the world. Morphine, isolated from opium during the early 19th century, is believed to be the first bioactive compound extracted from a plant. Its isolation was followed by that of numerous other early drugs, such as codeine, digitoxin, quinine, and others [4,5]. Yet, of the 10 000–15 000 higher plants documented to have medicinal properties, only approximately 200 are used in Western medicine [6,7]. It is estimated that only 5–15% of higher plants have been systematically investigated for medicinal properties [6]. Traditionally, the search for bioactive natural products involves either random collection and screening of plant material or the use of ethnobotanical knowledge. The latter is based on the selection and screening of plants based on the medicinal knowledge of traditional or indigenous peoples (TMK/IMK) [8]. A relevant example from the Brazilian Amazon is the small tree Pilocarpus
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Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany 2 MetaSysX GmbH, Potsdam, Germany 3 Department of Agriculture, Food and Environmental Sciences, Marche Polytechnic University, Ancona, Italy 4 Previous affiliation: ITV Institute, Vale. S.A., Belem, Brazil
*Correspondence: [email protected] (A. Skirycz).
http://dx.doi.org/10.1016/j.tibtech.2016.03.006 © 2016 Elsevier Ltd. All rights reserved.
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microphyllus, known as jaborandi and associated with iron-rich soils of the Flona de Carajasi. Jaborandi is used by indigenous tribes to treat mouth ulcers, colds, and flu. The earliest written reports referring to its medicinal properties date back to the 16th century. More recently, jaborandi was found to induce both sweating and salivation. This background knowledge led to the development of the imidazole alkaloid pilocarpine, which is the main constituent of the US Food and Drug Administration (FDA)-approved antiglaucoma drug Timpilo. Worldwide, the use of natural products as the source of novel drugs peaked during 1970–1980. During the 40-year period between 1940 and 2010, 48.6% of the anticancer agents approved for medical treatment were natural products or compounds derived thereof. These include the major structural classes of Vinca alkaloids, epipodophyllotoxin lignans, taxane diterpenoids, and camptothecin quinolone alkaloid derivatives [9]. However, since the early 1980s and until recently, the demand for plant extracts for drug discovery has been in decline for several reasons [10,11]. In summary, the interest of ‘Big Pharma’ companies in natural product development (NPD) programs dwindled because of: (i) supply problems; (ii) low yields; and (iii) the complex structures of compounds, which pose serious challenges for de novo chemical synthesis or structural modificationsii. The isolation and screening of natural products is typically followed by three sequential stages: lead identification, lead optimization, and lead development [12]. It has been estimated that only one in 5000 lead compounds will gain approval for use after clinical trials. It will take an average of 10 years for a drug to reach the market, with an estimated average cost exceeding US$1.3 billion [13] from US$800 million less than a decade ago [14]. As a consequence, the interest of Big Pharma industry shifted to drug development strategies using new technologies, such as highthroughput screening (HTS) and combinatorial chemistry (CC). The initial optimism that came with this new drug development paradigm has not been vindicated. The first FDAapproved combinatorial chemistry drug, sorafenib, intended for the treatment of renal carcinoma, was approved in 2005 [15]. In fact, it has been suggested that the small number of new chemical entities (NCEs) reaching the market and the ensuing productivity crisis may be due to the strategic decision of the pharmaceutical sector to favor combinatorial instead of natural product libraries [16]. The relative lack of success of CC and HTS to generate large numbers of drug leads or NCEs has rekindled interest in NPD programs. Novel drugs derived from natural products comprise approximately 60% of all FDA-approved drugs over the period 1981–2010 [16]. In the decade between 2000 and 2010, 38 natural product-derived drugs were approved for use in various medical indications. Of the more than 100 natural product-derived drugs in clinical development, 91 were plant derived [9]. Natural products are likely to continue being important in drug development on account of: (i) their pharmacophore-like properties, which are deemed to be superior to combinatorial library compounds [17]; and (ii) the exploration of the chemical space of natural products resulting from the combination of systems biology, bio-, and chemoinformatic tools and new high throughput analytic technologies (e.g., quantitative metabolomics), which have opened up new horizons for drug discovery [18].
Metabolite Complexity and Natural Product Discovery Drug discovery exploits the richness of the 200 000 different metabolites that are predicted to be found in plants [19]. However, this large repertoire of natural products also represents a hurdle, two aspects of which are discussed below. Often, it is the combination of metabolites, rather than a single compound, that produces a certain medicinal effect. To demonstrate the point, flowers and fruits of the herbaceous plant Psychotria colorata are traditionally used by Amazonian natives to treat pain. The potent analgesic effect of Psychotria was confirmed in rodents [20]. Subsequent research identified several active alkaloids, the most important of which were hodgkinsine, an opioid agonist, and
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Glossary Botanical drug: as defined in the United States Federal Food, Drug, and Cosmetic Act, a botanical product that is marketed as diagnosing, mitigating, treating, or curing a disease. Chemical space: chemical compounds can be characterized by different parameters, such as their molecular mass, topological features, or hydrophilicity (‘descriptors’). ‘Chemical space’ is used in reference to the group of compounds, describing the diversity of the descriptors that the group covers. Cheminformatics: also referred to as chemical informatics, the application of in silico techniques for mining the chemical space. Combinatorial library: a repository of a large number of chemical compounds obtained by means of combinatorial synthesis, using combinations of pre-set smaller chemical structures. Combinatorial chemistry (CC): parallel organic synthesis techniques generating hundreds of thousands of compounds. Convention on Biological Diversity (CBD): a multilateral treaty developed to create national strategies for the conservation and sustainable use of biological diversity. Dereplication: the process of identification and elimination of known compounds from processed experimental data (e.g., natural product extracts). Ethnobotany: a scientific discipline devoted to study of the traditional human knowledge of plants and their medical, religious, and other uses. US Food and Drug Administration (FDA)-approved drugs: in the USA, the FDA must accept a compound as a drug before it can be sold. The approval procedure obliges the manufacturer to present the results of clinical trials. Drugs are primarily single compounds. This paradigm is in contrast to herbal supplements, which can be sold without any prior research and are a mixture of compounds, often crude extracts. IC50: concentration of compound that causes 50% inhibition of the measured physiological phenomena; e.g., cell proliferation. High-throughput screening: techniques allowing the testing of large number of compounds.
psychotridine, an N-methyl-D-aspartate receptor (NMDAR) antagonist [21,22]. Both compounds act in concentrations comparable to morphine and dizocilpine respectively, which are two of the most widely used antinociceptive drugs. The strong analgesic properties of the Psychotria extract can be explained by the additive effects of its alkaloid constituents. It is likely that additive, synergistic, or antagonistic interactions may underpin the medicinal properties of plant extracts containing hundreds or even thousands of different metabolites. This observation forces a change in thinking about drug discovery. Another aspect of metabolic complexity is related to the diversity present within any living species. The concentration and composition of secondary metabolites is highly variable depending on the genotype, the environment, and genotype environment interactions. For instance, pilocarpine extracted from jaborandi grown in semiagricultural fashion contains low amounts of the compound. According to local gatherers, the redness of leaves, suggestive of some kind of abiotic or biotic stress, which is possibly absent in the agricultural setting, is positively correlated with alkaloid content. Accordingly, treatment of jaborandi seedlings with the stress hormones, salicylic and jasmonic acid, enhances pilocarpine accumulation several fold [23]. Whether jasmonate or salicylate treatment could be used to promote pilocarpine synthesis in field conditions and/or cell cultures needs to be tested. Germplasm collections, such as the one owned by the Brazilian Agricultural Research Corporation (EMBRAPA) for Pilocarpus [24], and tested under varying environmental conditions, are crucial resources for maximizing metabolite yields by selecting optimal genotype–environment combinations, thus providing a good start for domestication efforts. The metabolic differences related to genetic and environmental diversity are a significant hurdle, because they multiply the number of samples and parameters to be considered. At the same time, the diversity arising from genetic interactions with the environment provides unique opportunities to select the most desirable metabolic profiles [25].
Interactomics: a scientific discipline examining the complete set of biological interactions present within an organism. Medical bioprospecting: the characterization of living organisms (e.g., plant species) in respect to the presence of commercially valuable chemical compounds. Metabolomics: a scientific discipline examining the complete set of metabolites within an organism. Natural product: chemical compound produced by living organisms. Pharmacophore: the ensemble of steric and electronic features that is necessary to ensure the optimal supramolecular interactions with a specific biological target structure and to trigger (or to block) its biological response. Selectivity index (SI): the therapeutic concentration of the compound responsible for the medicinal effect in relation to the concentration causing cytotoxicity.
Below, we address how recent technological progress enables the exploration and exploitation of metabolite complexity, even when plant material is limited.
Technological Progress and Bioprospecting Progress in metabolomics research holds the promise to revolutionize natural product research. Although the first mass spectrometry (MS)-based metabolomics experiments were performed during the 1970s [26], the term ‘metabolomics’ was not coined until 1998 [27]. MSbased metabolomics can detect hundreds of compounds in a single measurement and, when coupled with gas or liquid chromatographic separation techniques, can lead to the identification of several thousands of molecules simultaneously [28] (Box 1). Public or ‘in-house’ databases containing spectral and chromatographic information relating to reference compounds are typically the principal source of metabolic annotation; alternative approaches exploit isotope labeling [29] and MS/MS fragmentation patterns. Although still far from straightforward because of the high complexity and diversity of natural products, annotation has improved significantly over the past 20 years aided by the development of statistical methods for the selection of metabolites associated with particular biological properties, including medicinal activity [30,31]. A relatively new strategy in metabolomics research is the use of multivariate analysis to integrate small-molecule profiling (fingerprinting) with meta-information on medicinal function. Importantly, not only single compounds, but also combinations of compounds can be selected in this way. Research progress in metabolomics is also directly linked to the emergence of a new discipline, referred to as ‘interactomics’. In general, small molecules, including drugs, affect physiological processes by noncovalent and reversible binding to receptor proteins. As a result, pharmaceutical companies routinely use in vitro screens comprising recombinant proteins of interest
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Box 1. Metabolomics ‘Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under a given set of conditions. Metabolites are the result of the interaction of the system's genome with its environment and are not merely the end product of gene expression but also form part of the regulatory system in an integrated manner’ [61]. A great advantage in using metabolomics to profile natural products from plants is that changes in the metabolome occur further downstream than changes in the transcriptome or proteome. Other advantages are that: (i) whole-genome sequences are not needed; (ii) metabolomics is cheaper due to higher throughput compared with other ‘omics’ technologies; and (iii) databases of genome-wide metabolites are becoming increasingly available [62]. Different approaches to metabolomic analysis include: (i) targeted analysis, referring to the identification and quantification of a small set of known target metabolites; (ii) metabolite profiling, similar to target analysis but extending to a larger range of known and/or unknown target metabolites; and (iii) metabolic fingerprinting, intended to generate sample ‘signatures’ for screening against a larger sample set, thus identifying mutual differences. One successful example of combining MS-based metabolomics with bioinformatics tools in drug discovery comes from a group in China [63]. They subjected five Panax herbs to metabolite fingerprinting with the use of ultra-performance liquid chromatography coupled with a quadrupole time-of-flight (TOF) MS (UPLC-QTOFMS) and subsequently applied principal component analysis (PCA) to the data. The authors were able to identify compounds with different bioactivities from plants belonging to the same species but originate from different geographical locations. Comprehensive reviews of the available analytic platforms for biomarker discovery using metabolomics are available elsewhere [64–67].
(e.g., proteins associated with particular cancer types). Automated set-ups allow the screening of large chemical compound libraries. Rather than looking at the individual protein–smallmolecule interactions, small-molecule or protein baits are used to pull down interacting molecules in a cell-wide manner, thus providing new opportunities for the isolation of compounds with unique chemical properties (Box 2). An ever-increasing number of studies have been published recently, demonstrating that it is possible to retrieve protein–small molecule complexes from the complex cellular lysates [32–36]. High-throughput ‘omics’ technologies for the isolation and screening of chemical compounds generate massive amounts of chemical data. A key challenge in speeding up the isolation of Box 2. Methods for Protein–Metabolite Interaction Studies Protein–metabolite interaction (PMI) studies rely on using a single, known protein or metabolite to determine its interacting partners from complex cellular lysates. Affinity chromatography, starting with either a protein or small-molecule bait, is the most common strategy. For instance, a protein of interest can be epitope tagged and expressed in the organism and/or system of choice. Protein and metabolite complexes are then immunoprecipitated from the-native lysate using commercial antibodies designed against the epitope (protein–small molecule PMI) [32]. Conversely, small molecules (ligands) can be chemically coupled to, for example, beaded agarose resin, to capture interacting proteins, again starting from the complex cellular extract (small molecule–protein PMI) [33,34]. The main disadvantage of the affinity approach is the need for bait modification. Tagged proteins may be affected in terms of their localization, activity, and reactivity. This effect is exacerbated in the case of metabolites: chemical coupling may block the structure of the immobilized ligand and thereby disturb the binding. For this reason, several alternative approaches have been developed. These rely on stability differences between proteins bound, or not bound, to small molecules and comprise drug affinity responsive target stability (DARTS) and cellular thermal shift assay (CETSA). In combination with proteomics, both DARTS and CESTA allow the unbiased identification of protein partners of any given small molecule [35,68]. Interactomic approaches offer unprecedented opportunities for medicinal bioprospecting. Using epitope-tagged proteins of interest to pull down small-molecule partners from complex medicinal extracts is just one possibility. Conversely, DARTS or CESTA can be used as a method of choice for the unbiased cell-wide identification of protein receptors of natural compounds of interest. The identification of protein target(s) not only sheds light on mechanisms of drug action, but is also a prerequisite for modulating the binding properties of small molecules through chemical modifications, the most important parameters being binding strength and dissociation rates. Importantly, both DARTS and CESTA require only a small amount of starting material and can be easily automated, allowing the testing of multiple compounds in a relatively short amount of time.
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novel biologically active compounds is the dereplication of extracts early enough during the drug discovery process. As early as 1994, it was estimated that the savings for each dereplicated natural product amounted to US$50 000 in the time spent on isolation and identification [37]. Dereplication has now become a hallmark in metabolomics research [38,39]. Due to the volume of data to be analyzed, their manual interpretation is almost impossible. Therefore, numerous computational resources have been developed that provide software tools for matching spectral and structural information, as well as comprehensive information on previously isolated compounds, the source organisms, and corresponding bioactivities [40,41]. At the same time, chemical compound public and private databases are rapidly proliferating, with an increasing number dedicated specifically to natural products research. Fifteen such natural product-specific databases were recently reported [41].
New Technology Approaches to Overcome Sourcing Issues Sourcing of plant material from the tropics is recognized as one of the major hurdles for research and/or drug development. For conventional natural product screening, samples of 500–1000 g dry weight are often required from different plant tissues. The bulk material needs to be rapidly dried and bagged for transportation [42]. The disadvantage of this procedure is that plant tissue metabolism is not quenched and, therefore, it is not possible to study the chemical variation characteristics of plants grown under natural environmental conditions. Plant tissue metabolism can be quenched by immersing the samples in dry ice or liquid nitrogen, but the logistics of doing so in the Amazon are formidable. The problem can be circumvented by storing samples in a lowreactivity solvent with quenching capabilities before transportation for further laboratory processing. A novel protocol that is particularly amenable for metabolic fingerprinting with liquid chromatography (LC)-MS has been reported in the literature [43]. Last but not least, metabolic fingerprinting can be performed with samples in the mg range. Whereas early tests may require small amounts of sample (mg–mg), the demand for increasing quantities of a compound grows with the need for safety and toxicology studies, formulation development, and so on. An example is the fern Metaxja rostata, which is harvested from the Costa Rica rain forest. Bioactivity-guided isolation from Metaxja roots yielded 2-deprenylrheediaxanthone B, a compound with cytotoxic and cytostatic activity towards multiple colorectal cancer cell lines. Due to its relatively low IC50 and high selectivity index (SI), it is considered to be a promising lead compound [20,44]. Given that kilograms of plant rootlets are required to obtain meaningful amounts of the compound, alternative sources and/or semisynthetic approaches are needed for animal tests. In a few cases, the problem can be circumvented by cell cultures obtained from medicinal species [45–49]. A more likely scenario would involve the application of ‘omics’ technologies for enzymatic pathway dissection, powerful genome-editing tools [50], and the introduction of whole biosynthetic pathways to simple organisms, such as bacteria and yeast [51]. The recently published semisynthetic production of the potent antimalarial compound artemisinin using Baker's yeast Saccharomyces cerevisiae [52] provides an example of how novel molecular techniques can address supply difficulties that have marred natural product research in the past.
Policy Issues Related to Access to, and Supply of, Plant Material A quarter of a century ago, some believed that the then-emerging ‘new’ biotechnology held the promise of enabling biodiversity-rich developing countries to leverage their biological resource endowment to meet conservation objectives through sustainable economic development. The prevalent view at the time was that bioprospecting could generate new sources of income, which, in turn, could be invested in conservation programs [53] (Figure 1, Key Figure). Whether this would be a plausible scenario depended not only on scientific and technological advancements and drug development strategies, but also on policies regulating access to genetic resources (Box 3).
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Key Figure
Ideal Case Relation between Bioprospecting and Biodiversity Conservation, as Delineated by CBD
Bioprospecng
Conservaon
Research
Product(s)
Income Figure 1.
The Convention on Biological Diversity (CBD), which was established in 1993, is a landmark international agreement that recognizes the sovereign rights of States over their natural resources. A legally binding supplementary agreement to CBD, known as the Nagoya Protocol on Access To Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilisation (ABS), was agreed upon by the signatories of CBD. ABS sets the rules for access to biodiversity based on mutual benefit sharing between sovereign States and third parties [54]. Expectations that CBD and the Nagoya Protocol would promote novel and sustainable uses of biodiversity and catalyze research partnerships and income generation without compromising conservation imperatives have been largely unmet. Significantly, the expected increase in medical discoveries from bioprospecting inspired by ABS-type agreements has not materialized [55]. The Nagoya Protocol moves in the right direction to allay fears that advanced industrialized countries would be the main beneficiaries of innovations arising from biodiversity. However, it is Box 3. Examples of Bioprospecting Partnerships A landmark bioprospecting partnership deal involved the pharmaceutical company Merck and the National Biodiversity Institute of Costa Rica (INBio). According to this deal, Merck paid in advance US$1.1 million for bioprospecting rights and agreed to royalty payments that would result from the discovery of any new drugs. In 2008, Merck abandoned its efforts to develop drugs through the INBio agreement, opting for alternative routes of drug development. In 2012, Merck gave away its entire natural product library of some 100 000 extracts. INBio was left fighting for financial survival [69]. It is possible that this type of bioprospecting partnership model may have not met the pace of isolation of natural product extracts required for testing in high-throughput models favored by the pharmaceutical industry. More risk-friendly institutions, such as academic laboratories, public research institutes, or small biotech companies, may be more amenable to bioprospecting partnerships [70]. The International Cooperative Biodiversity Groups (ICBG) program provides a blueprint for this type of partnership between biodiversity source countries, public research institutes, and international development agencies [11] (www.cbd.int/doc/publications/cbd-ts-38-en.pdf; www.cbd.int/doc/ case-studies/abs/cs-abs-icbg.pdf).
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Box 4. Brazil as an Example of Overregulation
Outstanding Questions
In Brazil, Provisional Measure (PM) 2.186-16 of 2001 provides the legal framework for access to, and benefit sharing of (ABS), genetic resources in compliance with the obligations arising from the adoption of CBD and the Nagoya Protocol. If indigenous or local communities are involved, their explicit agreement and, in most cases, an independent anthropological report are required, although the type of information that must be presented in research proposals and in adjunct anthropological reports is not clearly specified. In addition, specific Decrees provide guidance for the implementation of PM 2.186-16 with respect to noncommercial and commercial authorizations. For commercial authorizations, Decree 6159/2007 requires a specific contract referred to as the Contract for the Use of Genetic Heritage and Benefit Sharing. Contracts must be approved by the Genetic Heritage Management Council (CGEN) before any technological development and/or filing of patents arising from the use of genetic resources and may only be granted to registered Brazilian Institutions. In compliance with this Decree, the National Intellectual Property Institute (INPI) issued resolutions 134/2006 and 207/2009, which require applicants to submit information to INPI on the provenance of the genetic material and/or traditional knowledge (www.bio.org/sites/default/files/BIO%20Brazil%20Bioprospecting%20& %20Genetic%20Resources%20FINAL.pdf).
Can access to biodiversity leverage research partnerships, technology transfer, and investment? What is the likely impact of the implementation of the Nagoya Protocol on bioprospecting? To what extent can ‘omics’ technologies be used to capture the value of biodiversity and be linked to biodiversity conservation efforts?
PM 2.186-16 of 2001 is implemented by CGEN, which comprises numerous federal research organizations and groups representing indigenous communities. CGEN-accredited institutions, such as IBAMA, CNPq, and the National Institute of Historic and Artistic Heritage (IPHAN), issue access authorizations. Authorization procedures are convoluted, cumbersome, and lacking in clarity, and, thus, are open to different interpretations. The result is that companies can be put in situations of ‘exposed illegality,’ which is a major disincentive for innovation [71]. in 2012, IBAMA issued fines amounting to US$45 million to 35 different Brazil-based cosmetic and pharmaceutical companies for failure to comply with the Provisional Measure provisions (www.scidev.net/global/ biodiversity/news/brazil-fines-35-firms-us-44-million-for-biopiracy.html). Not surprisingly, even for noncommercial academic research, only 200 permits were issued by CGEN in the 10-year period from 2003 to2013 (http://portal.fiocruz.br/ sites/portal.fiocruz.br/files/documentos/abs_implementation_brazil.pdf).
declaratory in nature and voluntary, lacking contractual obligations. This means that, without adequate governance, its implementation is likely to be imperfect [55]. The interpretation and implementation of the CBD and the Nagoya Protocol by biodiversity-rich countries will determine to a large extent their ability to capitalize successfully on their biological resources (Box 4).
Concluding Remarks The route for drug development from natural products is long, technologically complex, and expensive [56]. Biodiversity will continue to be a valuable source of novel drugs. New technologies, in particular metabolomics, interactomics, chemo-, and bioinformatics, are key to accelerating drug discovery. Compared with conventional natural product discovery methods, they allow the rapid isolation, screening, and fingerprinting of natural products from mg-sample quantities. Here, we make a strong case that these technologies can be a game-changer in the exploration of the largely untapped chemical diversity of Amazonian plants. In view of the ever-increasing threat of losing valuable natural resources due to climate change and unsustainable economic activities, the knowledge acquired from the metabolic profiling of Amazonian plants can have an important role in improving the efficiency of cultivation programs (see Outstanding Questions), as well as providing quality input to conservation efforts. The technologies covered here, in combination with ethnobotanical information or the application of ecological criteria for plant selection and secondary metabolite isolation [25], can be used for the targeted screening of the chemical diversity of rare endemic plants and/or those threatened with extinction, offering a viable alternative to high-throughput screening. Whether these technologies can be used to leverage research partnerships and technology investment is an open question. We take Brazil as a case in point because it has made significant investments in life sciences research and development over the past decade and, in our view, the human resources and infrastructural capacities for the application of ‘omics’ technologies are now available, albeit unevenly distributed [57]. A plausible scenario for research partnerships
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would be the development and sharing of chemical compound libraries. As mentioned above, chemical compound libraries form the foundation of drug discovery efforts. However, their intrinsic value cannot be exploited unless they are coupled to high-throughput bioactivity screening of compounds screened against different cell types. It is unrealistic to expect any single research institute, private or public, to generate libraries covering even a small fraction of the chemical space of Amazonian plants or having the necessary screens. As a consequence, sharing of libraries offers mutual benefits to partners. Although public research institutes and companies treasure their chemical libraries, they are willing to share them because this is considered to be ‘precompetitive’ research. Precompetitive library sharing has taken place between academic research partners, public research institutions, and industry, and even between competing enterprises, as exemplified by the chemical library sharing between AstraZeneca and Bayeriii. Pharmaceutical companies, such as AstraZeneca, have made their chemical libraries available to a network of more than 130 academic research centers (Academic Drug Discovery Consortium) and company libraries have been made available to the research community through the Joint European Compound Library [58]. These paradigms can be a model for the development of similar initiatives involving Brazil or other countries of the Amazonia. Other types of technology transfer can also be envisaged. Chemical informatics methods in combination with network pharmacology can be used to evaluate the therapeutic properties of herbs that are used in traditional medicine (botanical drugs), thus turning the latter into a valuable resource for drug discovery [59]. Botanical drugs have great potential for use in official healthcare systems both in industrialized and developing countries. Systems biology coupled with ‘omics’ technologies and traditional knowledge can provide solid scientific evidence in support of the functional claims of botanical drugs as well as to facilitate their safety assessment and efficacy evaluation [60] (Box 1). The disadvantage is that opportunities such as those mentioned above will not generate an Eldorado-type rush by the pharmaceutical industry to the chemical riches of the Amazon. Additional incentives need to be made available. None is more important than the rationalization of the regulatory system for biodiversity access and benefit sharing. Significant relocation of human and capital resources to the tropical regions of Brazil is unlikely to occur until bottlenecks in regulatory policies are overcome. Unless the present regimes regulating access and benefit sharing are radically rationalized, large-scale cooperation between research institutions and private enterprises is unlikely. Regulatory systems, such as that in Brazil (Box 4) are too restrictive and unfriendly because research partnerships, particularly with foreign research institutes, are effectively discouraged. Biodiversity access regulation needs to evolve in ways that encourage research partnerships and the involvement of the private sector in technology transfer. A step in the right direction would be the simplification and rationalization of the multitude of regulatory instruments to take into account relevant scientific developments. For example, administrative procedures pertaining to precompetitive research (e.g., access biodiversity, material transfer agreements, etc.) can be greatly relaxed without compromising ownership issues. Likewise, regulations could be simplified with better definition of what constitutes IMK/TMK. Models do exist (Box 3) and can be used as templates to suit specific situations. The active involvement of the scientific community in shaping access regulations is essential, because science advances much faster than regulatory policies. The road to the medicinal El Dorado of tropical plants may be long and arduous, but many other smaller but still valuable finds are likely to be hidden along the way. Acknowledgments We would like to thank Jose. O. Siqueira for supporting our work.
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Resources i
http://www.icmbio.gov.br/portal/images/Carajas.pdf
ii
http://www.scripps.edu/shen/NPLI/whynaturalproducts.html
iii
http://www.statnews.com/2015/11/20/pharma-company-compound-libraries/
References 1. Silman, M.R. (2011) Plant species diversity in Amazonian forests. In In Tropical Rainforest Responses to Climatic Change (Bush, M. et al., eds), pp. 285–314, Springer-Verlag
26. Pauling, L. et al. (1971) Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography. Proc. Natl. Acad. Sci. U.S.A. 68, 2374–2376
2. Pimm, S.L. et al. (2014) The biodiversity of species and their rates of extinction, distribution, and protection. Science 344, 987–996
27. Oliver, S.G. et al. (1998) Systematic functional analysis of the yeast genome. Trends Biotechnol. 16, 373–378
3. Feeley, K.J. and Silman, M.R. (2009) Extinction risks of Amazonian plant species. Proc. Natl. Acad. Sci. U.S.A. 106, 12382–12387
28. Kueger, S. et al. (2012) High-resolution plant metabolomics: from mass spectral features to metabolites and from whole-cell analysis to subcellular metabolite distributions. Plant J. 70, 39–50
4. Kinghorn, A.D. (2001) Pharmacognosy in the 21st century. J. Pharm. Pharmacol. 53, 135–148 5. Butler, M.S. (2004) The role of natural product chemistry in drug discovery. J. Nat. Prod. 67, 2141–2153 6. McChesney, J.D. et al. (2007) Plant natural products: back to the future or into extinction? Phytochemistry 68, 2015–2022 7. Birari, R.B. and Bhutani, K.K. (2007) Pancreatic lipase inhibitors from natural sources: unexplored potential. Drug. Discov. Today 12, 879–889 8. Gu, R. et al. (2014) Prospecting for bioactive constituents from traditional medicinal plants through ethnobotanical approaches. Biol. Pharm. Bull. 37, 903–915
29. Giavalisco, P. et al. (2011) Elemental formula annotation of polar and lipophilic metabolites using (13) C, (15) N and (34) S isotope labelling, in combination with high-resolution mass spectrometry. Plant J. 68, 364–376 30. Ching, J. et al. (2012) Identification of active compounds from medicinal plant extracts using gas chromatography-mass spectrometry and multivariate data analysis. J. Sep. Sci. 35, 53–59 31. Okada, T. et al. (2010) Metabolomics of medicinal plants: the importance of multivariate analysis of analytical chemistry data. Curr. Comput. Aided. Drug Des. 6, 179–196 32. Li, X. et al. (2010) Extensive in vivo metabolite-protein interactions revealed by large-scale systematic analyses. Cell 143, 639–650
9. Krause, J. and Tobin, G. (2013) Discovery, development and regulation of natural products. In In Using Old Solutions to New Problems–Natural Drug Discovery in the 21st Century (Kulka, M., ed.), pp. 3–35, InTech
33. Wulff, J.E. et al. (2007) The natural product avrainvillamide binds to the oncoprotein nucleophosmin. J. Am. Chem. Soc. 129, 14444– 14451
10. Koehn, F.E. and Carter, G.T. (2005) The evolving role of natural products in drug discovery. Nat. Rev. Drug. Discov. 4, 206–220
34. Burgett, A.W. et al. (2011) Natural products reveal cancer cell dependence on oxysterol-binding proteins. Nat. Chem. Biol. 7, 639–647
11. Kingston, D.G. (2011) Modern natural products drug discovery and its relevance to biodiversity conservation. J. Nat. Prod. 74, 496–511 12. Balunas, M.J. and Kinghorn, A.D. (2005) Drug discovery from medicinal plants. Life Sci. 78, 431–441
35. Lomenick, B. et al. (2009) Target identification using drug affinity responsive target stability (DARTS). Proc. Natl. Acad. Sci. U.S.A. 106, 21984–21989 36. Savitski, M.M. et al. (2014) Tracking cancer drugs in living cells by thermal profiling of the proteome. Science 346, 1255784
13. Honig, P. and Lalonde, R. (2010) The economics of drug development: a grim reality and a role for clinical pharmacology. Clin. Pharmacol. Ther. 87, 247–251
37. Corley, D.G. and Durley, R.C. (1994) Strategies for database dereplication of natural products. J. Nat. Prod. 57, 1484–1490
14. DiMasi, J.A. et al. (2003) The price of innovation: new estimates of drug development costs. J. Health Econ. 22, 151–185
38. Hubert, J. et al. (2015) Dereplication strategies in natural product research: how many tools and methodologies behind the same concept? Phytochem. Rev. 1–41
15. Harvey, A.L. (2008) Natural products in drug discovery. Drug. Discov. Today 13, 894–901 16. Ogbourne, S.M. and Parsons, P.G. (2014) The value of nature's natural product library for the discovery of new chemical entities: the discovery of ingenol mebutate. Fitoterapia 98, 36–44 17. Grabowski, K. and Schneider, G. (2007) Properties and architecture of drugs and natural products revisited. Curr. Chem. Biol. 1, 115–127 18. Gu, J. et al. (2013) Use of natural products as chemical library for drug discovery and network pharmacology. PLoS One 8, e62839 19. Roessner, U. et al. (2001) Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 13, 11–29 20. Elisabetsky, E. et al. (1995) Analgesic activity of Psychotria colorata (Willd. ex R & S.) Muell. Arg. J Ethnopharmacol. 48, 77–83 21. Amador, T.A. et al. (1996) Effects of Psychotria colorata alkaloids in brain opioid system. Neurochem. Res. 21, 97–102 22. Amador, T.A. et al. (2001) Involvement of NMDA receptors in the analgesic properties of psychotridine. Phytomedicine 8, 202–206 23. Avancini, G. et al. (2003) Induction of pilocarpine formation in jaborandi leaves by salicylic acid and methyljasmonate. Phytochemistry 63, 171–175 24. Moura, E.F. et al. (2005) Genetic diversity in a jaborandi (Pilocarpus microphyllus Stapf.) germplasm bank assessed by RAPD markers. Rev. Bras. Pl. Med. Botucatu. 7, 1–8 25. Coley, P.D. et al. (2003) Using ecological criteria to design plant collection strategies for drug discovery. Front. Ecol. Environ. 1, 421–428
39. Gaudencio, S.P. and Pereira, F. (2015) Dereplication: racing to speed up the natural products discovery process. Nat. Prod. Rep. 32, 779–810 40. Hufsky, F. et al. (2014) New kids on the block: novel informatics methods for natural product discovery. Nat. Prod. Rep. 31, 807–817 41. Mohamed, A. et al. (2015) Current status and prospects of computational resources for natural product dereplication: a review. Brief. Bioinform. http://dx.doi.org/10.1093/bib/bbv042 42. McCloud, T.G. (2010) High throughput extraction of plant, marine and fungal specimens for preservation of biologically active molecules. Molecules 15, 4526–4563 43. Maier, T.S. et al. (2010) Proposal for field sampling of plants and processing in the lab for environmental metabolic fingerprinting. Plant Methods 6, 6 44. Kainz, K.P. et al. (2013) 2-deprenyl-rheediaxanthone B isolated from Metaxya rostrata induces active cell death in colorectal tumor cells. PLoS One 8, e65745 45. Malik, S. et al. (2016) Biotechnological approaches to the production of shikonins: a critical review with recent updates. Crit. Rev. Biotechnol. 36, 327–340 46. Murthy, H.N. et al. (2014) Ginsenosides: prospective for sustainable biotechnological production. Appl. Microbiol. Biotechnol. 98, 6243–6254 47. Cusido, R.M. et al. (2014) A rational approach to improving the biotechnological production of taxanes in plant cell cultures of Taxus spp. Biotechnol. Adv. 32, 1157–1167
Trends in Biotechnology, October 2016, Vol. 34, No. 10
789
48. Abreu, I.N. et al. Production of pilocarpine in callus of jaborandi (Pilocarpus microphyllus stapf). In Vitro Cell. Dev. Biol.–Plant 41, 806-811
60. Liu, Y. and Wang, M.W. (2008) Botanical drugs: challenges and opportunities: contribution to Linnaeus Memorial Symposium 2007. Life Sci. 82, 445–449
49. Andreazza, N.L. et al. (2015) Characterisation of the membrane transport of pilocarpine in cell suspension cultures of Pilocarpus microphyllus. J. Plant Physiol. 175, 37–47
61. Rochfort, S. (2005) Metabolomics reviewed: a new ‘omics’ platform technology for systems biology and implications for natural products research. J. Nat. Prod. 68, 1813–1820
50. Boettcher, M. and McManus, M.T. (2015) Choosing the right tool for the job: RNAi, TALEN, or CRISPR. Mol. Cell 58, 575–585
62. Kell, D.B. (2007) Metabolomic biomarkers: search, discovery and validation. Expert Rev. Mol. Diagn. 7, 329–333
51. Ro, D.K. et al. (2006) Production of the antimalarial drug precursor artemisinic acid in engineered yeast. Nature 440, 940–943
63. Xie, G. et al. Ultra-performance LC/TOF MS analysis of medicinal Panax herbs for metabolomic research. J. Sep. Sci. 31, 10151026
52. Paddon, C.J. et al. (2013) High-level semi-synthetic production of the potent antimalarial artemisinin. Nature 496, 528–532
64. Monteiro, M.S. et al. (2013) Metabolomics analysis for biomarker discovery: advances and challenges. Curr. Med. Chem. 20, 257–271
53. Dalton, R. (2004) Bioprospectors hunt for fair share of profits. Nature 427, 576
65. Dias, D.A. et al. (2012) A historical overview of natural products in drug discovery. Metabolites 2, 303–336
54. Schindel, D.E. and du Plessis, P. (2014) Biodiversity: reap the benefits of the Nagoya protocol. Nature 515, 37
66. Roessner, U. and Bowne, J. (2009) What is metabolomics all about? Biotechniques 46, 363–365
55. Kursar, T.A. (2011) What are the implications of the Nagoya Protocol for Research on biodiversity? BioScience 61, 256–257
67. Hubert, J. et al. (2014) Identification of natural metabolites in mixture: a pattern recognition strategy based on (13)C NMR. Anal. Chem. 86, 2955–2962
56. Kessel, M. and Frank, F. (2007) A better prescription for drugdevelopment financing. Nat. Biotechnol. 25, 859–866
68. Hulce, J.J. et al. (2013) Proteome-wide mapping of cholesterolinteracting proteins in mammalian cells. Nat. Methods 10, 259–264
57. Kihara, E. and Soares, E.E. (2011) The Brazilian Life Science Industry, PricewaterhouseCoopers 58. Besnard, J. et al. (2015) The Joint European Compound Library: boosting precompetitive research. Drug Discov. Today 20, 181– 186 59. Ding, W. et al. (2014) Traditional Chinese herbs as chemical resource library for drug discovery of anti-infective and anti-inflammatory. J. Ethnopharmacol. 155, 589–598
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69. Wade, L. (2014) Costa Rica. Celebrated biodiversity institute faces financial crisis. Science 346, 1440 70. Glaser, K.B. and Mayer, A.M. (2009) A renaissance in marine pharmacology: from preclinical curiosity to clinical reality. Biochem. Pharmacol. 78, 440–448 71. Barreto, D.W. (2012) The Brazilian genetic heritage: protect it or use it commercially? J. Braz. Chem. Soc. 23, 194–196
Medicinal Bioprospecting of the Amazon Rainforest: A Modern Eldorado? Aleksandra Skirycz,1,4,* Sylwia Kierszniowska,2 Michaël Méret,2 Lothar Willmitzer,1 and George Tzotzos3,4 Ignorant of the New World, Europeans believed in El Dorado, a hidden city of immense wealth in gold. Many consider the Amazonian forest to be a medicinal treasure chest and potentially the largest drug dispensary in the world. Yet, the quest to obtain drugs from indigenous tropical plants remains elusive. Here, we assess the potential of new technologies to tap into the metabolic diversity of tropical plants. We also consider how regulations affect access to plant resources. We conclude that, although the road to this medicinal El Dorado may be long and arduous, many other smaller but still valuable finds are hidden along the way.
Trends Metabolomics can speed up the identification of natural product scaffolds used in combinatorial chemistry, thus expanding the value of combinatorial chemistry libraries. Improved efficiency of dereplication toolkits is likely to accelerate drug discovery.
The Shifting Paradigms in Small-Molecule Drug Discovery
Novel methods to track protein–metabolite interactions in a cell-wide manner can be exploited to assist natural drug discovery.
The Amazonian rainforests are known to harbor the largest plant diversity in the world, with an estimated 30 000 vascular plant species [1,2]. Although numerous Amazonian plants have been screened for secondary metabolites, it can be argued that our current knowledge of the chemical diversity of the Amazonian plant biome represents only a fraction of that diversity [3].
Genetic engineering can help to reconstitute plant biosynthetic pathways in simple organisms, such as yeast, thus overcoming supply problems with natural products.
Here, we examine how new technologies can be applied to explore the chemical diversity of tropical plants, and how challenges posed by the complex interplay between metabolism, genetic, and environmental factors can be turned into bioprospecting (see Glossary) opportunities. We focus on emergent applications of metabolomics, small molecule–protein interactomics, and chemoinformatics, because these are particularly relevant in drug discovery efforts. We also discuss how regulatory policies affect access to plant resources and consequently affect technology transfer. We use Brazil as a case in point because it is a country with one of the richest biodiversities in the world, and has adequate research and regulatory oversight capacities. Crude drugs and other herbal formulations from medicinal plants have been used for thousands of years and are still used widely in many parts of the world. Morphine, isolated from opium during the early 19th century, is believed to be the first bioactive compound extracted from a plant. Its isolation was followed by that of numerous other early drugs, such as codeine, digitoxin, quinine, and others [4,5]. Yet, of the 10 000–15 000 higher plants documented to have medicinal properties, only approximately 200 are used in Western medicine [6,7]. It is estimated that only 5–15% of higher plants have been systematically investigated for medicinal properties [6]. Traditionally, the search for bioactive natural products involves either random collection and screening of plant material or the use of ethnobotanical knowledge. The latter is based on the selection and screening of plants based on the medicinal knowledge of traditional or indigenous peoples (TMK/IMK) [8]. A relevant example from the Brazilian Amazon is the small tree Pilocarpus
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Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany 2 MetaSysX GmbH, Potsdam, Germany 3 Department of Agriculture, Food and Environmental Sciences, Marche Polytechnic University, Ancona, Italy 4 Previous affiliation: ITV Institute, Vale. S.A., Belem, Brazil
*Correspondence: [email protected] (A. Skirycz).
http://dx.doi.org/10.1016/j.tibtech.2016.03.006 © 2016 Elsevier Ltd. All rights reserved.
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microphyllus, known as jaborandi and associated with iron-rich soils of the Flona de Carajasi. Jaborandi is used by indigenous tribes to treat mouth ulcers, colds, and flu. The earliest written reports referring to its medicinal properties date back to the 16th century. More recently, jaborandi was found to induce both sweating and salivation. This background knowledge led to the development of the imidazole alkaloid pilocarpine, which is the main constituent of the US Food and Drug Administration (FDA)-approved antiglaucoma drug Timpilo. Worldwide, the use of natural products as the source of novel drugs peaked during 1970–1980. During the 40-year period between 1940 and 2010, 48.6% of the anticancer agents approved for medical treatment were natural products or compounds derived thereof. These include the major structural classes of Vinca alkaloids, epipodophyllotoxin lignans, taxane diterpenoids, and camptothecin quinolone alkaloid derivatives [9]. However, since the early 1980s and until recently, the demand for plant extracts for drug discovery has been in decline for several reasons [10,11]. In summary, the interest of ‘Big Pharma’ companies in natural product development (NPD) programs dwindled because of: (i) supply problems; (ii) low yields; and (iii) the complex structures of compounds, which pose serious challenges for de novo chemical synthesis or structural modificationsii. The isolation and screening of natural products is typically followed by three sequential stages: lead identification, lead optimization, and lead development [12]. It has been estimated that only one in 5000 lead compounds will gain approval for use after clinical trials. It will take an average of 10 years for a drug to reach the market, with an estimated average cost exceeding US$1.3 billion [13] from US$800 million less than a decade ago [14]. As a consequence, the interest of Big Pharma industry shifted to drug development strategies using new technologies, such as highthroughput screening (HTS) and combinatorial chemistry (CC). The initial optimism that came with this new drug development paradigm has not been vindicated. The first FDAapproved combinatorial chemistry drug, sorafenib, intended for the treatment of renal carcinoma, was approved in 2005 [15]. In fact, it has been suggested that the small number of new chemical entities (NCEs) reaching the market and the ensuing productivity crisis may be due to the strategic decision of the pharmaceutical sector to favor combinatorial instead of natural product libraries [16]. The relative lack of success of CC and HTS to generate large numbers of drug leads or NCEs has rekindled interest in NPD programs. Novel drugs derived from natural products comprise approximately 60% of all FDA-approved drugs over the period 1981–2010 [16]. In the decade between 2000 and 2010, 38 natural product-derived drugs were approved for use in various medical indications. Of the more than 100 natural product-derived drugs in clinical development, 91 were plant derived [9]. Natural products are likely to continue being important in drug development on account of: (i) their pharmacophore-like properties, which are deemed to be superior to combinatorial library compounds [17]; and (ii) the exploration of the chemical space of natural products resulting from the combination of systems biology, bio-, and chemoinformatic tools and new high throughput analytic technologies (e.g., quantitative metabolomics), which have opened up new horizons for drug discovery [18].
Metabolite Complexity and Natural Product Discovery Drug discovery exploits the richness of the 200 000 different metabolites that are predicted to be found in plants [19]. However, this large repertoire of natural products also represents a hurdle, two aspects of which are discussed below. Often, it is the combination of metabolites, rather than a single compound, that produces a certain medicinal effect. To demonstrate the point, flowers and fruits of the herbaceous plant Psychotria colorata are traditionally used by Amazonian natives to treat pain. The potent analgesic effect of Psychotria was confirmed in rodents [20]. Subsequent research identified several active alkaloids, the most important of which were hodgkinsine, an opioid agonist, and
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Glossary Botanical drug: as defined in the United States Federal Food, Drug, and Cosmetic Act, a botanical product that is marketed as diagnosing, mitigating, treating, or curing a disease. Chemical space: chemical compounds can be characterized by different parameters, such as their molecular mass, topological features, or hydrophilicity (‘descriptors’). ‘Chemical space’ is used in reference to the group of compounds, describing the diversity of the descriptors that the group covers. Cheminformatics: also referred to as chemical informatics, the application of in silico techniques for mining the chemical space. Combinatorial library: a repository of a large number of chemical compounds obtained by means of combinatorial synthesis, using combinations of pre-set smaller chemical structures. Combinatorial chemistry (CC): parallel organic synthesis techniques generating hundreds of thousands of compounds. Convention on Biological Diversity (CBD): a multilateral treaty developed to create national strategies for the conservation and sustainable use of biological diversity. Dereplication: the process of identification and elimination of known compounds from processed experimental data (e.g., natural product extracts). Ethnobotany: a scientific discipline devoted to study of the traditional human knowledge of plants and their medical, religious, and other uses. US Food and Drug Administration (FDA)-approved drugs: in the USA, the FDA must accept a compound as a drug before it can be sold. The approval procedure obliges the manufacturer to present the results of clinical trials. Drugs are primarily single compounds. This paradigm is in contrast to herbal supplements, which can be sold without any prior research and are a mixture of compounds, often crude extracts. IC50: concentration of compound that causes 50% inhibition of the measured physiological phenomena; e.g., cell proliferation. High-throughput screening: techniques allowing the testing of large number of compounds.
psychotridine, an N-methyl-D-aspartate receptor (NMDAR) antagonist [21,22]. Both compounds act in concentrations comparable to morphine and dizocilpine respectively, which are two of the most widely used antinociceptive drugs. The strong analgesic properties of the Psychotria extract can be explained by the additive effects of its alkaloid constituents. It is likely that additive, synergistic, or antagonistic interactions may underpin the medicinal properties of plant extracts containing hundreds or even thousands of different metabolites. This observation forces a change in thinking about drug discovery. Another aspect of metabolic complexity is related to the diversity present within any living species. The concentration and composition of secondary metabolites is highly variable depending on the genotype, the environment, and genotype environment interactions. For instance, pilocarpine extracted from jaborandi grown in semiagricultural fashion contains low amounts of the compound. According to local gatherers, the redness of leaves, suggestive of some kind of abiotic or biotic stress, which is possibly absent in the agricultural setting, is positively correlated with alkaloid content. Accordingly, treatment of jaborandi seedlings with the stress hormones, salicylic and jasmonic acid, enhances pilocarpine accumulation several fold [23]. Whether jasmonate or salicylate treatment could be used to promote pilocarpine synthesis in field conditions and/or cell cultures needs to be tested. Germplasm collections, such as the one owned by the Brazilian Agricultural Research Corporation (EMBRAPA) for Pilocarpus [24], and tested under varying environmental conditions, are crucial resources for maximizing metabolite yields by selecting optimal genotype–environment combinations, thus providing a good start for domestication efforts. The metabolic differences related to genetic and environmental diversity are a significant hurdle, because they multiply the number of samples and parameters to be considered. At the same time, the diversity arising from genetic interactions with the environment provides unique opportunities to select the most desirable metabolic profiles [25].
Interactomics: a scientific discipline examining the complete set of biological interactions present within an organism. Medical bioprospecting: the characterization of living organisms (e.g., plant species) in respect to the presence of commercially valuable chemical compounds. Metabolomics: a scientific discipline examining the complete set of metabolites within an organism. Natural product: chemical compound produced by living organisms. Pharmacophore: the ensemble of steric and electronic features that is necessary to ensure the optimal supramolecular interactions with a specific biological target structure and to trigger (or to block) its biological response. Selectivity index (SI): the therapeutic concentration of the compound responsible for the medicinal effect in relation to the concentration causing cytotoxicity.
Below, we address how recent technological progress enables the exploration and exploitation of metabolite complexity, even when plant material is limited.
Technological Progress and Bioprospecting Progress in metabolomics research holds the promise to revolutionize natural product research. Although the first mass spectrometry (MS)-based metabolomics experiments were performed during the 1970s [26], the term ‘metabolomics’ was not coined until 1998 [27]. MSbased metabolomics can detect hundreds of compounds in a single measurement and, when coupled with gas or liquid chromatographic separation techniques, can lead to the identification of several thousands of molecules simultaneously [28] (Box 1). Public or ‘in-house’ databases containing spectral and chromatographic information relating to reference compounds are typically the principal source of metabolic annotation; alternative approaches exploit isotope labeling [29] and MS/MS fragmentation patterns. Although still far from straightforward because of the high complexity and diversity of natural products, annotation has improved significantly over the past 20 years aided by the development of statistical methods for the selection of metabolites associated with particular biological properties, including medicinal activity [30,31]. A relatively new strategy in metabolomics research is the use of multivariate analysis to integrate small-molecule profiling (fingerprinting) with meta-information on medicinal function. Importantly, not only single compounds, but also combinations of compounds can be selected in this way. Research progress in metabolomics is also directly linked to the emergence of a new discipline, referred to as ‘interactomics’. In general, small molecules, including drugs, affect physiological processes by noncovalent and reversible binding to receptor proteins. As a result, pharmaceutical companies routinely use in vitro screens comprising recombinant proteins of interest
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Box 1. Metabolomics ‘Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under a given set of conditions. Metabolites are the result of the interaction of the system's genome with its environment and are not merely the end product of gene expression but also form part of the regulatory system in an integrated manner’ [61]. A great advantage in using metabolomics to profile natural products from plants is that changes in the metabolome occur further downstream than changes in the transcriptome or proteome. Other advantages are that: (i) whole-genome sequences are not needed; (ii) metabolomics is cheaper due to higher throughput compared with other ‘omics’ technologies; and (iii) databases of genome-wide metabolites are becoming increasingly available [62]. Different approaches to metabolomic analysis include: (i) targeted analysis, referring to the identification and quantification of a small set of known target metabolites; (ii) metabolite profiling, similar to target analysis but extending to a larger range of known and/or unknown target metabolites; and (iii) metabolic fingerprinting, intended to generate sample ‘signatures’ for screening against a larger sample set, thus identifying mutual differences. One successful example of combining MS-based metabolomics with bioinformatics tools in drug discovery comes from a group in China [63]. They subjected five Panax herbs to metabolite fingerprinting with the use of ultra-performance liquid chromatography coupled with a quadrupole time-of-flight (TOF) MS (UPLC-QTOFMS) and subsequently applied principal component analysis (PCA) to the data. The authors were able to identify compounds with different bioactivities from plants belonging to the same species but originate from different geographical locations. Comprehensive reviews of the available analytic platforms for biomarker discovery using metabolomics are available elsewhere [64–67].
(e.g., proteins associated with particular cancer types). Automated set-ups allow the screening of large chemical compound libraries. Rather than looking at the individual protein–smallmolecule interactions, small-molecule or protein baits are used to pull down interacting molecules in a cell-wide manner, thus providing new opportunities for the isolation of compounds with unique chemical properties (Box 2). An ever-increasing number of studies have been published recently, demonstrating that it is possible to retrieve protein–small molecule complexes from the complex cellular lysates [32–36]. High-throughput ‘omics’ technologies for the isolation and screening of chemical compounds generate massive amounts of chemical data. A key challenge in speeding up the isolation of Box 2. Methods for Protein–Metabolite Interaction Studies Protein–metabolite interaction (PMI) studies rely on using a single, known protein or metabolite to determine its interacting partners from complex cellular lysates. Affinity chromatography, starting with either a protein or small-molecule bait, is the most common strategy. For instance, a protein of interest can be epitope tagged and expressed in the organism and/or system of choice. Protein and metabolite complexes are then immunoprecipitated from the-native lysate using commercial antibodies designed against the epitope (protein–small molecule PMI) [32]. Conversely, small molecules (ligands) can be chemically coupled to, for example, beaded agarose resin, to capture interacting proteins, again starting from the complex cellular extract (small molecule–protein PMI) [33,34]. The main disadvantage of the affinity approach is the need for bait modification. Tagged proteins may be affected in terms of their localization, activity, and reactivity. This effect is exacerbated in the case of metabolites: chemical coupling may block the structure of the immobilized ligand and thereby disturb the binding. For this reason, several alternative approaches have been developed. These rely on stability differences between proteins bound, or not bound, to small molecules and comprise drug affinity responsive target stability (DARTS) and cellular thermal shift assay (CETSA). In combination with proteomics, both DARTS and CESTA allow the unbiased identification of protein partners of any given small molecule [35,68]. Interactomic approaches offer unprecedented opportunities for medicinal bioprospecting. Using epitope-tagged proteins of interest to pull down small-molecule partners from complex medicinal extracts is just one possibility. Conversely, DARTS or CESTA can be used as a method of choice for the unbiased cell-wide identification of protein receptors of natural compounds of interest. The identification of protein target(s) not only sheds light on mechanisms of drug action, but is also a prerequisite for modulating the binding properties of small molecules through chemical modifications, the most important parameters being binding strength and dissociation rates. Importantly, both DARTS and CESTA require only a small amount of starting material and can be easily automated, allowing the testing of multiple compounds in a relatively short amount of time.
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novel biologically active compounds is the dereplication of extracts early enough during the drug discovery process. As early as 1994, it was estimated that the savings for each dereplicated natural product amounted to US$50 000 in the time spent on isolation and identification [37]. Dereplication has now become a hallmark in metabolomics research [38,39]. Due to the volume of data to be analyzed, their manual interpretation is almost impossible. Therefore, numerous computational resources have been developed that provide software tools for matching spectral and structural information, as well as comprehensive information on previously isolated compounds, the source organisms, and corresponding bioactivities [40,41]. At the same time, chemical compound public and private databases are rapidly proliferating, with an increasing number dedicated specifically to natural products research. Fifteen such natural product-specific databases were recently reported [41].
New Technology Approaches to Overcome Sourcing Issues Sourcing of plant material from the tropics is recognized as one of the major hurdles for research and/or drug development. For conventional natural product screening, samples of 500–1000 g dry weight are often required from different plant tissues. The bulk material needs to be rapidly dried and bagged for transportation [42]. The disadvantage of this procedure is that plant tissue metabolism is not quenched and, therefore, it is not possible to study the chemical variation characteristics of plants grown under natural environmental conditions. Plant tissue metabolism can be quenched by immersing the samples in dry ice or liquid nitrogen, but the logistics of doing so in the Amazon are formidable. The problem can be circumvented by storing samples in a lowreactivity solvent with quenching capabilities before transportation for further laboratory processing. A novel protocol that is particularly amenable for metabolic fingerprinting with liquid chromatography (LC)-MS has been reported in the literature [43]. Last but not least, metabolic fingerprinting can be performed with samples in the mg range. Whereas early tests may require small amounts of sample (mg–mg), the demand for increasing quantities of a compound grows with the need for safety and toxicology studies, formulation development, and so on. An example is the fern Metaxja rostata, which is harvested from the Costa Rica rain forest. Bioactivity-guided isolation from Metaxja roots yielded 2-deprenylrheediaxanthone B, a compound with cytotoxic and cytostatic activity towards multiple colorectal cancer cell lines. Due to its relatively low IC50 and high selectivity index (SI), it is considered to be a promising lead compound [20,44]. Given that kilograms of plant rootlets are required to obtain meaningful amounts of the compound, alternative sources and/or semisynthetic approaches are needed for animal tests. In a few cases, the problem can be circumvented by cell cultures obtained from medicinal species [45–49]. A more likely scenario would involve the application of ‘omics’ technologies for enzymatic pathway dissection, powerful genome-editing tools [50], and the introduction of whole biosynthetic pathways to simple organisms, such as bacteria and yeast [51]. The recently published semisynthetic production of the potent antimalarial compound artemisinin using Baker's yeast Saccharomyces cerevisiae [52] provides an example of how novel molecular techniques can address supply difficulties that have marred natural product research in the past.
Policy Issues Related to Access to, and Supply of, Plant Material A quarter of a century ago, some believed that the then-emerging ‘new’ biotechnology held the promise of enabling biodiversity-rich developing countries to leverage their biological resource endowment to meet conservation objectives through sustainable economic development. The prevalent view at the time was that bioprospecting could generate new sources of income, which, in turn, could be invested in conservation programs [53] (Figure 1, Key Figure). Whether this would be a plausible scenario depended not only on scientific and technological advancements and drug development strategies, but also on policies regulating access to genetic resources (Box 3).
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Key Figure
Ideal Case Relation between Bioprospecting and Biodiversity Conservation, as Delineated by CBD
Bioprospecng
Conservaon
Research
Product(s)
Income Figure 1.
The Convention on Biological Diversity (CBD), which was established in 1993, is a landmark international agreement that recognizes the sovereign rights of States over their natural resources. A legally binding supplementary agreement to CBD, known as the Nagoya Protocol on Access To Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilisation (ABS), was agreed upon by the signatories of CBD. ABS sets the rules for access to biodiversity based on mutual benefit sharing between sovereign States and third parties [54]. Expectations that CBD and the Nagoya Protocol would promote novel and sustainable uses of biodiversity and catalyze research partnerships and income generation without compromising conservation imperatives have been largely unmet. Significantly, the expected increase in medical discoveries from bioprospecting inspired by ABS-type agreements has not materialized [55]. The Nagoya Protocol moves in the right direction to allay fears that advanced industrialized countries would be the main beneficiaries of innovations arising from biodiversity. However, it is Box 3. Examples of Bioprospecting Partnerships A landmark bioprospecting partnership deal involved the pharmaceutical company Merck and the National Biodiversity Institute of Costa Rica (INBio). According to this deal, Merck paid in advance US$1.1 million for bioprospecting rights and agreed to royalty payments that would result from the discovery of any new drugs. In 2008, Merck abandoned its efforts to develop drugs through the INBio agreement, opting for alternative routes of drug development. In 2012, Merck gave away its entire natural product library of some 100 000 extracts. INBio was left fighting for financial survival [69]. It is possible that this type of bioprospecting partnership model may have not met the pace of isolation of natural product extracts required for testing in high-throughput models favored by the pharmaceutical industry. More risk-friendly institutions, such as academic laboratories, public research institutes, or small biotech companies, may be more amenable to bioprospecting partnerships [70]. The International Cooperative Biodiversity Groups (ICBG) program provides a blueprint for this type of partnership between biodiversity source countries, public research institutes, and international development agencies [11] (www.cbd.int/doc/publications/cbd-ts-38-en.pdf; www.cbd.int/doc/ case-studies/abs/cs-abs-icbg.pdf).
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Box 4. Brazil as an Example of Overregulation
Outstanding Questions
In Brazil, Provisional Measure (PM) 2.186-16 of 2001 provides the legal framework for access to, and benefit sharing of (ABS), genetic resources in compliance with the obligations arising from the adoption of CBD and the Nagoya Protocol. If indigenous or local communities are involved, their explicit agreement and, in most cases, an independent anthropological report are required, although the type of information that must be presented in research proposals and in adjunct anthropological reports is not clearly specified. In addition, specific Decrees provide guidance for the implementation of PM 2.186-16 with respect to noncommercial and commercial authorizations. For commercial authorizations, Decree 6159/2007 requires a specific contract referred to as the Contract for the Use of Genetic Heritage and Benefit Sharing. Contracts must be approved by the Genetic Heritage Management Council (CGEN) before any technological development and/or filing of patents arising from the use of genetic resources and may only be granted to registered Brazilian Institutions. In compliance with this Decree, the National Intellectual Property Institute (INPI) issued resolutions 134/2006 and 207/2009, which require applicants to submit information to INPI on the provenance of the genetic material and/or traditional knowledge (www.bio.org/sites/default/files/BIO%20Brazil%20Bioprospecting%20& %20Genetic%20Resources%20FINAL.pdf).
Can access to biodiversity leverage research partnerships, technology transfer, and investment? What is the likely impact of the implementation of the Nagoya Protocol on bioprospecting? To what extent can ‘omics’ technologies be used to capture the value of biodiversity and be linked to biodiversity conservation efforts?
PM 2.186-16 of 2001 is implemented by CGEN, which comprises numerous federal research organizations and groups representing indigenous communities. CGEN-accredited institutions, such as IBAMA, CNPq, and the National Institute of Historic and Artistic Heritage (IPHAN), issue access authorizations. Authorization procedures are convoluted, cumbersome, and lacking in clarity, and, thus, are open to different interpretations. The result is that companies can be put in situations of ‘exposed illegality,’ which is a major disincentive for innovation [71]. in 2012, IBAMA issued fines amounting to US$45 million to 35 different Brazil-based cosmetic and pharmaceutical companies for failure to comply with the Provisional Measure provisions (www.scidev.net/global/ biodiversity/news/brazil-fines-35-firms-us-44-million-for-biopiracy.html). Not surprisingly, even for noncommercial academic research, only 200 permits were issued by CGEN in the 10-year period from 2003 to2013 (http://portal.fiocruz.br/ sites/portal.fiocruz.br/files/documentos/abs_implementation_brazil.pdf).
declaratory in nature and voluntary, lacking contractual obligations. This means that, without adequate governance, its implementation is likely to be imperfect [55]. The interpretation and implementation of the CBD and the Nagoya Protocol by biodiversity-rich countries will determine to a large extent their ability to capitalize successfully on their biological resources (Box 4).
Concluding Remarks The route for drug development from natural products is long, technologically complex, and expensive [56]. Biodiversity will continue to be a valuable source of novel drugs. New technologies, in particular metabolomics, interactomics, chemo-, and bioinformatics, are key to accelerating drug discovery. Compared with conventional natural product discovery methods, they allow the rapid isolation, screening, and fingerprinting of natural products from mg-sample quantities. Here, we make a strong case that these technologies can be a game-changer in the exploration of the largely untapped chemical diversity of Amazonian plants. In view of the ever-increasing threat of losing valuable natural resources due to climate change and unsustainable economic activities, the knowledge acquired from the metabolic profiling of Amazonian plants can have an important role in improving the efficiency of cultivation programs (see Outstanding Questions), as well as providing quality input to conservation efforts. The technologies covered here, in combination with ethnobotanical information or the application of ecological criteria for plant selection and secondary metabolite isolation [25], can be used for the targeted screening of the chemical diversity of rare endemic plants and/or those threatened with extinction, offering a viable alternative to high-throughput screening. Whether these technologies can be used to leverage research partnerships and technology investment is an open question. We take Brazil as a case in point because it has made significant investments in life sciences research and development over the past decade and, in our view, the human resources and infrastructural capacities for the application of ‘omics’ technologies are now available, albeit unevenly distributed [57]. A plausible scenario for research partnerships
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would be the development and sharing of chemical compound libraries. As mentioned above, chemical compound libraries form the foundation of drug discovery efforts. However, their intrinsic value cannot be exploited unless they are coupled to high-throughput bioactivity screening of compounds screened against different cell types. It is unrealistic to expect any single research institute, private or public, to generate libraries covering even a small fraction of the chemical space of Amazonian plants or having the necessary screens. As a consequence, sharing of libraries offers mutual benefits to partners. Although public research institutes and companies treasure their chemical libraries, they are willing to share them because this is considered to be ‘precompetitive’ research. Precompetitive library sharing has taken place between academic research partners, public research institutions, and industry, and even between competing enterprises, as exemplified by the chemical library sharing between AstraZeneca and Bayeriii. Pharmaceutical companies, such as AstraZeneca, have made their chemical libraries available to a network of more than 130 academic research centers (Academic Drug Discovery Consortium) and company libraries have been made available to the research community through the Joint European Compound Library [58]. These paradigms can be a model for the development of similar initiatives involving Brazil or other countries of the Amazonia. Other types of technology transfer can also be envisaged. Chemical informatics methods in combination with network pharmacology can be used to evaluate the therapeutic properties of herbs that are used in traditional medicine (botanical drugs), thus turning the latter into a valuable resource for drug discovery [59]. Botanical drugs have great potential for use in official healthcare systems both in industrialized and developing countries. Systems biology coupled with ‘omics’ technologies and traditional knowledge can provide solid scientific evidence in support of the functional claims of botanical drugs as well as to facilitate their safety assessment and efficacy evaluation [60] (Box 1). The disadvantage is that opportunities such as those mentioned above will not generate an Eldorado-type rush by the pharmaceutical industry to the chemical riches of the Amazon. Additional incentives need to be made available. None is more important than the rationalization of the regulatory system for biodiversity access and benefit sharing. Significant relocation of human and capital resources to the tropical regions of Brazil is unlikely to occur until bottlenecks in regulatory policies are overcome. Unless the present regimes regulating access and benefit sharing are radically rationalized, large-scale cooperation between research institutions and private enterprises is unlikely. Regulatory systems, such as that in Brazil (Box 4) are too restrictive and unfriendly because research partnerships, particularly with foreign research institutes, are effectively discouraged. Biodiversity access regulation needs to evolve in ways that encourage research partnerships and the involvement of the private sector in technology transfer. A step in the right direction would be the simplification and rationalization of the multitude of regulatory instruments to take into account relevant scientific developments. For example, administrative procedures pertaining to precompetitive research (e.g., access biodiversity, material transfer agreements, etc.) can be greatly relaxed without compromising ownership issues. Likewise, regulations could be simplified with better definition of what constitutes IMK/TMK. Models do exist (Box 3) and can be used as templates to suit specific situations. The active involvement of the scientific community in shaping access regulations is essential, because science advances much faster than regulatory policies. The road to the medicinal El Dorado of tropical plants may be long and arduous, but many other smaller but still valuable finds are likely to be hidden along the way. Acknowledgments We would like to thank Jose. O. Siqueira for supporting our work.
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Resources i
http://www.icmbio.gov.br/portal/images/Carajas.pdf
ii
http://www.scripps.edu/shen/NPLI/whynaturalproducts.html
iii
http://www.statnews.com/2015/11/20/pharma-company-compound-libraries/
References 1. Silman, M.R. (2011) Plant species diversity in Amazonian forests. In In Tropical Rainforest Responses to Climatic Change (Bush, M. et al., eds), pp. 285–314, Springer-Verlag
26. Pauling, L. et al. (1971) Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography. Proc. Natl. Acad. Sci. U.S.A. 68, 2374–2376
2. Pimm, S.L. et al. (2014) The biodiversity of species and their rates of extinction, distribution, and protection. Science 344, 987–996
27. Oliver, S.G. et al. (1998) Systematic functional analysis of the yeast genome. Trends Biotechnol. 16, 373–378
3. Feeley, K.J. and Silman, M.R. (2009) Extinction risks of Amazonian plant species. Proc. Natl. Acad. Sci. U.S.A. 106, 12382–12387
28. Kueger, S. et al. (2012) High-resolution plant metabolomics: from mass spectral features to metabolites and from whole-cell analysis to subcellular metabolite distributions. Plant J. 70, 39–50
4. Kinghorn, A.D. (2001) Pharmacognosy in the 21st century. J. Pharm. Pharmacol. 53, 135–148 5. Butler, M.S. (2004) The role of natural product chemistry in drug discovery. J. Nat. Prod. 67, 2141–2153 6. McChesney, J.D. et al. (2007) Plant natural products: back to the future or into extinction? Phytochemistry 68, 2015–2022 7. Birari, R.B. and Bhutani, K.K. (2007) Pancreatic lipase inhibitors from natural sources: unexplored potential. Drug. Discov. Today 12, 879–889 8. Gu, R. et al. (2014) Prospecting for bioactive constituents from traditional medicinal plants through ethnobotanical approaches. Biol. Pharm. Bull. 37, 903–915
29. Giavalisco, P. et al. (2011) Elemental formula annotation of polar and lipophilic metabolites using (13) C, (15) N and (34) S isotope labelling, in combination with high-resolution mass spectrometry. Plant J. 68, 364–376 30. Ching, J. et al. (2012) Identification of active compounds from medicinal plant extracts using gas chromatography-mass spectrometry and multivariate data analysis. J. Sep. Sci. 35, 53–59 31. Okada, T. et al. (2010) Metabolomics of medicinal plants: the importance of multivariate analysis of analytical chemistry data. Curr. Comput. Aided. Drug Des. 6, 179–196 32. Li, X. et al. (2010) Extensive in vivo metabolite-protein interactions revealed by large-scale systematic analyses. Cell 143, 639–650
9. Krause, J. and Tobin, G. (2013) Discovery, development and regulation of natural products. In In Using Old Solutions to New Problems–Natural Drug Discovery in the 21st Century (Kulka, M., ed.), pp. 3–35, InTech
33. Wulff, J.E. et al. (2007) The natural product avrainvillamide binds to the oncoprotein nucleophosmin. J. Am. Chem. Soc. 129, 14444– 14451
10. Koehn, F.E. and Carter, G.T. (2005) The evolving role of natural products in drug discovery. Nat. Rev. Drug. Discov. 4, 206–220
34. Burgett, A.W. et al. (2011) Natural products reveal cancer cell dependence on oxysterol-binding proteins. Nat. Chem. Biol. 7, 639–647
11. Kingston, D.G. (2011) Modern natural products drug discovery and its relevance to biodiversity conservation. J. Nat. Prod. 74, 496–511 12. Balunas, M.J. and Kinghorn, A.D. (2005) Drug discovery from medicinal plants. Life Sci. 78, 431–441
35. Lomenick, B. et al. (2009) Target identification using drug affinity responsive target stability (DARTS). Proc. Natl. Acad. Sci. U.S.A. 106, 21984–21989 36. Savitski, M.M. et al. (2014) Tracking cancer drugs in living cells by thermal profiling of the proteome. Science 346, 1255784
13. Honig, P. and Lalonde, R. (2010) The economics of drug development: a grim reality and a role for clinical pharmacology. Clin. Pharmacol. Ther. 87, 247–251
37. Corley, D.G. and Durley, R.C. (1994) Strategies for database dereplication of natural products. J. Nat. Prod. 57, 1484–1490
14. DiMasi, J.A. et al. (2003) The price of innovation: new estimates of drug development costs. J. Health Econ. 22, 151–185
38. Hubert, J. et al. (2015) Dereplication strategies in natural product research: how many tools and methodologies behind the same concept? Phytochem. Rev. 1–41
15. Harvey, A.L. (2008) Natural products in drug discovery. Drug. Discov. Today 13, 894–901 16. Ogbourne, S.M. and Parsons, P.G. (2014) The value of nature's natural product library for the discovery of new chemical entities: the discovery of ingenol mebutate. Fitoterapia 98, 36–44 17. Grabowski, K. and Schneider, G. (2007) Properties and architecture of drugs and natural products revisited. Curr. Chem. Biol. 1, 115–127 18. Gu, J. et al. (2013) Use of natural products as chemical library for drug discovery and network pharmacology. PLoS One 8, e62839 19. Roessner, U. et al. (2001) Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 13, 11–29 20. Elisabetsky, E. et al. (1995) Analgesic activity of Psychotria colorata (Willd. ex R & S.) Muell. Arg. J Ethnopharmacol. 48, 77–83 21. Amador, T.A. et al. (1996) Effects of Psychotria colorata alkaloids in brain opioid system. Neurochem. Res. 21, 97–102 22. Amador, T.A. et al. (2001) Involvement of NMDA receptors in the analgesic properties of psychotridine. Phytomedicine 8, 202–206 23. Avancini, G. et al. (2003) Induction of pilocarpine formation in jaborandi leaves by salicylic acid and methyljasmonate. Phytochemistry 63, 171–175 24. Moura, E.F. et al. (2005) Genetic diversity in a jaborandi (Pilocarpus microphyllus Stapf.) germplasm bank assessed by RAPD markers. Rev. Bras. Pl. Med. Botucatu. 7, 1–8 25. Coley, P.D. et al. (2003) Using ecological criteria to design plant collection strategies for drug discovery. Front. Ecol. Environ. 1, 421–428
39. Gaudencio, S.P. and Pereira, F. (2015) Dereplication: racing to speed up the natural products discovery process. Nat. Prod. Rep. 32, 779–810 40. Hufsky, F. et al. (2014) New kids on the block: novel informatics methods for natural product discovery. Nat. Prod. Rep. 31, 807–817 41. Mohamed, A. et al. (2015) Current status and prospects of computational resources for natural product dereplication: a review. Brief. Bioinform. http://dx.doi.org/10.1093/bib/bbv042 42. McCloud, T.G. (2010) High throughput extraction of plant, marine and fungal specimens for preservation of biologically active molecules. Molecules 15, 4526–4563 43. Maier, T.S. et al. (2010) Proposal for field sampling of plants and processing in the lab for environmental metabolic fingerprinting. Plant Methods 6, 6 44. Kainz, K.P. et al. (2013) 2-deprenyl-rheediaxanthone B isolated from Metaxya rostrata induces active cell death in colorectal tumor cells. PLoS One 8, e65745 45. Malik, S. et al. (2016) Biotechnological approaches to the production of shikonins: a critical review with recent updates. Crit. Rev. Biotechnol. 36, 327–340 46. Murthy, H.N. et al. (2014) Ginsenosides: prospective for sustainable biotechnological production. Appl. Microbiol. Biotechnol. 98, 6243–6254 47. Cusido, R.M. et al. (2014) A rational approach to improving the biotechnological production of taxanes in plant cell cultures of Taxus spp. Biotechnol. Adv. 32, 1157–1167
Trends in Biotechnology, October 2016, Vol. 34, No. 10
789
48. Abreu, I.N. et al. Production of pilocarpine in callus of jaborandi (Pilocarpus microphyllus stapf). In Vitro Cell. Dev. Biol.–Plant 41, 806-811
60. Liu, Y. and Wang, M.W. (2008) Botanical drugs: challenges and opportunities: contribution to Linnaeus Memorial Symposium 2007. Life Sci. 82, 445–449
49. Andreazza, N.L. et al. (2015) Characterisation of the membrane transport of pilocarpine in cell suspension cultures of Pilocarpus microphyllus. J. Plant Physiol. 175, 37–47
61. Rochfort, S. (2005) Metabolomics reviewed: a new ‘omics’ platform technology for systems biology and implications for natural products research. J. Nat. Prod. 68, 1813–1820
50. Boettcher, M. and McManus, M.T. (2015) Choosing the right tool for the job: RNAi, TALEN, or CRISPR. Mol. Cell 58, 575–585
62. Kell, D.B. (2007) Metabolomic biomarkers: search, discovery and validation. Expert Rev. Mol. Diagn. 7, 329–333
51. Ro, D.K. et al. (2006) Production of the antimalarial drug precursor artemisinic acid in engineered yeast. Nature 440, 940–943
63. Xie, G. et al. Ultra-performance LC/TOF MS analysis of medicinal Panax herbs for metabolomic research. J. Sep. Sci. 31, 10151026
52. Paddon, C.J. et al. (2013) High-level semi-synthetic production of the potent antimalarial artemisinin. Nature 496, 528–532
64. Monteiro, M.S. et al. (2013) Metabolomics analysis for biomarker discovery: advances and challenges. Curr. Med. Chem. 20, 257–271
53. Dalton, R. (2004) Bioprospectors hunt for fair share of profits. Nature 427, 576
65. Dias, D.A. et al. (2012) A historical overview of natural products in drug discovery. Metabolites 2, 303–336
54. Schindel, D.E. and du Plessis, P. (2014) Biodiversity: reap the benefits of the Nagoya protocol. Nature 515, 37
66. Roessner, U. and Bowne, J. (2009) What is metabolomics all about? Biotechniques 46, 363–365
55. Kursar, T.A. (2011) What are the implications of the Nagoya Protocol for Research on biodiversity? BioScience 61, 256–257
67. Hubert, J. et al. (2014) Identification of natural metabolites in mixture: a pattern recognition strategy based on (13)C NMR. Anal. Chem. 86, 2955–2962
56. Kessel, M. and Frank, F. (2007) A better prescription for drugdevelopment financing. Nat. Biotechnol. 25, 859–866
68. Hulce, J.J. et al. (2013) Proteome-wide mapping of cholesterolinteracting proteins in mammalian cells. Nat. Methods 10, 259–264
57. Kihara, E. and Soares, E.E. (2011) The Brazilian Life Science Industry, PricewaterhouseCoopers 58. Besnard, J. et al. (2015) The Joint European Compound Library: boosting precompetitive research. Drug Discov. Today 20, 181– 186 59. Ding, W. et al. (2014) Traditional Chinese herbs as chemical resource library for drug discovery of anti-infective and anti-inflammatory. J. Ethnopharmacol. 155, 589–598
790
Trends in Biotechnology, October 2016, Vol. 34, No. 10
69. Wade, L. (2014) Costa Rica. Celebrated biodiversity institute faces financial crisis. Science 346, 1440 70. Glaser, K.B. and Mayer, A.M. (2009) A renaissance in marine pharmacology: from preclinical curiosity to clinical reality. Biochem. Pharmacol. 78, 440–448 71. Barreto, D.W. (2012) The Brazilian genetic heritage: protect it or use it commercially? J. Braz. Chem. Soc. 23, 194–196