Metabolomics in Drug Discovery: A Review

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International Journal of Pharmacy and Pharmaceutical Science Research Universal Research Publications. All rights reserved

ISSN: 2249-0337 Review Article Metabolomics in Drug Discovery: A Review Martis Elvis A.*, Ahire Deepak C., Singh Ruchi O. Department of Pharmaceutical Chemistry, Vivekanand Education Society’s College of Pharmacy *Email: [email protected]. Received 17 July 2011; accepted 30 July 2011 Abstract Metabolomics is up-coming omic science. Metabolomic society consistent with other post genomic sciences such as genomics, transcriptomics and proteomics. Metabolomics is emerging as a significant player in drug development process, it is a technology that aims to identify and quantifies the metabolome-the dynamic set of all small molecules present in an organism or a biological sample. Metabolic analysis provides a biochemical snapshot of the small molecules produced during cellular metabolism. Since the metabolome directly reflects physiological states, it can biochemically monitor disease states and assess drug actions, improving the preclinical to clinical translation and focusing on predictability, efficiency and improve productivity. Knowing early on how drugs impacts biochemistry would be a significant advantage, leading to fewer failures at a later stage. This paper describes about metabolomics as an important tool in drug discovery and also gives an overview metabolomic process. © 2011 Universal Research Publications. All rights reserved Key words: Omic Science, Metabolomics, Drug Discovery.

[1] Introduction: Any Pharmaceutical Company to survive in this competitive market, where newer therapeutic agents for various illnesses are being launched at very high frequency, must invest a good deal of resources in drug discovery process. They must break through and investigate numerous possibilities to invent newer, effective and safer drugs. The scenario of drug discovery process has received a many fold facelift, during the beginning of the 21st century. Figures (Fig. 1A, Fig 1B and Fig 1C) illustrates the comparison of the process in 50’s, 80’s and present day scenario.[1] Omic science encompasses studies in, transcriptomics [2], proteomics [3] , metabolomics [4] , genomics [5], fluxomics [6]. Here are some terminologies related to metabolomics: [1.1] Metabolite- It is a substance produced or used during

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metabolism. [1.2] Metabolome- The quantitative complement of all the low molecular weight molecules present in cells in a particular physiological state. It refers to the catalogue of those molecules in a specific organism, e.g. Human metabolome. [1.3] Metabolomics- Study of treasury of non-proteinaceous endogenously synthesized small molecules present in organism. Metabolomics is a comprehensive analysis of the whole metabolome under a given set of conditions. Metabolomics is the only technology that provides information about the quantitation of, the interactions between the genome, proteome and biological ‘wild card’ that is the external environment. Metabolomics is up-coming omic science. Metabolomic society is consistent with other post genomic sciences; ideally

International Journal of Pharmacy and Pharmaceutical Science Research 2011; 1(2): 67-74

Figure-1 (a): Drug discovery process in 1950’s and 1960’s

Figure-1 (b): Drug discovery process in 1980’s

Figure-1 (c): Present day drug discovery process.[50] metabolomic data sets will be combined with their other omic sciences, providing complete views into the molecular pathways of system biology. However, rather than focusing on characterizing large macromolecules (DNA, RNA and

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proteins) as happens in genomics or proteomics, metabolomics is focused on characterizing the small molecule, catabolic and metabolic products arising from the interactions of these large molecule (Fig 2). [7, 8]


[2] Metabolome Analysis: Absorption, distribution, metabolism and excretion (ADME) studies are widely used in drug discovery to optimize the balance of properties necessary to convert leads into safe drugs. Recently, metabolite characterization has become one of the main drivers in the drug discovery process, helping to optimize ADME properties and increase the success rate for

drugs. It has been a valuable and useful part of the drug development process for several decades [8]. During the past decade there has been an increased effort to address metabolism issues using high throughput technology for screening compounds, which in turn has led to strong demand for more rapid methods for metabolite identification [9].

Figure-2: The omic sciences are characterized by complex data sets of related phenomena, each of which is taken, as a whole constitutes a picture of an organism.

Figure-3: Strategies for metabolomic investigations.

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Figure-4: The circle shows particular area of metabolism that is affected, once identified, the targets, the protein or enzyme involved in creating the metabolic change can be detected.

Figure-5: A diagram of the pharmaceutical value chain, which indicates the biomarkers and this information, can be applied to various stages in the drug development process.

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Metabolite characterization earlier in process can identify metabolic pathways for drug candidate. Metabolite structural information eliminates potential harmful candidates earlier in the process & improves safety. There are two different approaches for collecting, processing and interpreting metabolomic data [10]. [2.1] Chemometric approach: The approach is based on computer-aided Pattern recognition and sophisticated statistical techniques such as principal component analysis (PCA) [11]. [2.2] Chemonomic approach: Chemonomic approach relies on spectral fitting and prior chemical or spectral knowledge about the tissue or biofluids such as Urine, Plasma, and Serum [11]. Modern approaches that generate and use metabolite structural information can accelerate the drug discovery and development process by eliminating potentially harmful candidates earlier in the process and improving the safety of new drugs [12]. [3] Methods of Characterization (Fig. 3) [13-19]: Separation methods: - Gas Chromatography, High Performance Liquid Chromatography Detection methods: - Mass Spectrometry, Nuclear Magnetic Resonance. [3.1] In- Silico Screening: It predicts & finds possible metabolites and its chemical structures and it is having ability to screen large number of structures even before synthesis [12, 20, 21]. E.g. TOPKAT, CASE/MULTI-CASE, DEREK, EXPERTHAZARD, METAPRINT. Today different techniques are combining for better resolution, such as LC-MS, Instrumental techniques LC-MSNMR have become commercially available to confirm and characterize metabolites. Hydrogen-deuterium (H-D) exchange and dramatization methods in conjunction with MS Facilitate structural elucidation and interpretation of tandem mass spectrometry (MS/MS) fragmentation processes [14]. [4] Working of Metabolomics: Multitudes of proteins are organized into signal transduction pathways that function to perceive inputs and trigger outputs. The inputs can be highly varied, from hormone or neurotransmitter signaling to changes in the physical environment, the ultimate outcome of these signaling pathways is that metabolic enzymes may be up or down regulated, and this influences the synthesis or degradation of the small molecules. In metabolomics, we measure the repertoire of small molecules in a sample (e.g. cells, tissues, organs, organisms) to understand more clearly what has changed in a system. Metabolomics as a measure of biochemistry is a more direct measure for a disease state (Fig. 4) [7]. [5] Role in Drug Discovery: Metabolomics has broad applications across the drug discovery and development processes. Metabolon’s

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proprietary technology platform in metabolomics will enable faster and more cost-effective processes [22] in the following areas: [5.1] Target Identification: Metabolon has the ability to determine accurately the treasury of biochemical changes inherent in a given disease, and then map these changes to known pathways, allowing researchers to build a biochemical hypothesis for a disease quickly. Based on this hypothesis, the enzymes and proteins critical to the disease can be elucidated and druggable disease targets identified [23, 24]. [5.2] Target validation [25]: With Metabolon’s approach of metabolic profiling, we determine the biochemical fingerprint for a specific target. The target can be validated biochemically in two ways: a. By determining any unexpected side effects inherent in it. b. By comparing the target with the actual disease. With metabolomics, it is possible to see unanticipated secondary effects inherent in a target and thus abandon a target that may carry unacceptable risk [23]. [5.3] Lead prioritization: From any screening programme, a number of leads will be found. In one of the critical decisions of the drug discovery process, one must choose which lead has highest priority. Using metabolic profiling compounds can be prioritized based on their ability to cause the desired biochemical changes. Currently, prioritization is based on strength of response and theoretical considerations of metabolism and toxicity. An incorrect guess at this point may doom an entire programme to failure. A metabolomic analysis makes it possible to classify the leads separately based on their primary and secondary responses [26, 27]. [5.4] Lead optimization: To move from a lead to a drug candidate, the lead is used as a base structure for the synthesis of hundreds of derivatives in a process known as ‘lead optimization’. In this step, chemists make many changes to the original lead and determine the effects that the changes have on activity. A metabolic profile is determined for each lead, based on profile, lead is optimized. This process repeated until final lead candidate with the lowest secondary effects is selected [28, 29]. [5.5] Mode of action: Metabolon has the ability to cluster drug candidates according to their common mechanism of action. Based on a metabolomic analysis, a hierarchical clustering or principal component analysis of compound profiles for drug candidates can be performed. The ability to cluster drug candidates according to their common mechanism of action has proved very useful in predicting the mechanism of unknown drug candidates. The predictive power of this type of analysis provides a significant benefit for prioritizing drug candidates. It can not only be put to use to predict the mode of action of the drug, but also be used to predict the toxic mechanism of action [30-34].


[5.6] Preclinical studies: Metabolon’s technology will be highly valuable in preclinical studies to differentiate drug leads based on their non-target tissue effects. Sometimes, these effects occur in the targeted tissues, but often they occur in non-targeted tissues and the undesired biochemical changes can lead to toxicity. In this case, Metabolon can evaluate compounds in advance of clinical trials to assess their relative probability for causing side effects [35-37]. [5.7] Clinical studies: Using Metabolon’s unique approach to drug development the time in clinical trials can be shortened thereby making quicker availability of the drugs in the market. Metabolon can identify subsets of patient populations within a given disorder. For this subset, the compound will have a higher safety and efficacy profile [38, 39]. Once this subset is identified, Metabolon can assist in the design of clinical trials to target that subset population. Since the design of the study is focused on patients that are more likely to respond to the drug and have fewer side effects, the enrolment necessary should be less, allowing for faster and less expensive clinical trials [8]. Phase I: These trials are small and meant to establish safety. Phase II & III: These trials establish efficacy and safety biomarkers. [5.8] Post-approval studies: Metabolon can provide comparative studies for marketing purposes to demonstrate safety and efficacy. Drug effect comparison studies are not only useful for marketing purposes, but can presented to the US Food and Drug Administration (FDA) to differentiate competitive drugs in order to avoid class labeling. In addition, technology platforms are useful for sorting the complex chemistry of clinical samples [7, 8]. [5.9] Diagnostic: Metabolon can identify biomarkers for various disorders. With these biomarkers, metabolon will associate with diagnostic companies to develop diagnostics. After reviewing a certain population of healthy and diseased analysis, Metabolon can identify biomarkers that become diagnostic of a given disease [40-44]. [6] Role in Solving Translational Chasm: Today few drug discovery projects generate a marketed drug product, because preclinical studies fail to predict the clinical experience with a drug candidate. Improving the preclinical to clinical translation is important in optimizing the pharmaceutical value chain. the gap between preclinical studies and clinical trials is referred to as the ‘Translational Chasm.” (Fig. 5) Metabolomic focusing on predictability, efficiency and Improve productivity by crossing the translational chasm via molecular system approach. Molecular system analysis of biofluid is performed; it permits molecular phenotyping primarily by proteomics and metabolomics [45-47].

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[7] Role in Reverse Translation: Crossing translation chasm in reverse direction enables discovery of second-generation drugs with improved efficacy & safety characteristics relative to first generation drug. The drug passed back to the preclinical phase from clinical trials or post marketing studies. Second-generation discovery based on Mode of Action of first generation. Plasma or serum metabolite profiling of blood samples, derived from patients treated with a first generation drug vs. placebo for a disease, yields system response profiles. Including biomarker sets that can be statistically associated with efficacy or safety outcome measures [45, 46-49]. [8] Conclusion: Metabolomics is emerging science; it enables faster & more cost effective process in drug discovery & development process. It offers toolkit, which can be potentially applied to identification of biomarkers, biochemical pathway studies, and diagnostic monitoring and tracking of mechanisms associated with disease. It offers promise that yet to be fulfilled by post-genomic sciences. It increases efficacy and safety of drugs. Genomics & proteomics tell what might happen but metabolomics tells what actually did happen. Metabolic profile gives knowledge & information rather than just data. References: 1) E. Ratt, D. Trist, Continuing evolution of the drug discovery process in the pharmaceutical industry. Pure and Applied Chemistry. 73 (2001) 67–75. 2) Z. Wang, M. Gerstein, M. Snyde, RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics. 10 (2009) 57-63. 3) P.R. Graves, T.A.J. Haystead, Molecular Biologist’s Guide to Proteomics. Microbiology and Molecular Biology Reviews. 66 (2002) 39-63. 4) D.B. Kell, Metabolomics and systems biology: making sense of the soup. Current Opinion in Microbiology. 7 (2004) 296–307. 5) R.W. Hendrix, Bacteriophage genomics. Current Opinion in Microbiology. 6 (2003) 506–511. 6) J. Krömer, L. Quek, L, Nielsen, 13C-Fluxomics: A tool for measuring metabolic phenotypes. Australian Biochemist. 40 (2009) 17-20. 7) J. Ryal, Metabolomics – An Important Emerging Science. Drug Discovery metabolomics, Business Briefing: Pharmatech 2004. Available from http://www.touchbriefings.com/pdf/890/Ryals.pdf. 8) D.S. Wishart, Metabolomics for Drug Discovery. Development and Monitoring. Drug Discovery, 2005. Available from http://www.touchhealthsciences.com/articles/metabolo mics-drug-discovery-development-andmonitoring?page=0,1


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Source of support: Nil; Conflict of interest: None declared

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