Van Eyk, Dunn - Proteomic and Genomic Analysis of Cardiovascular Disease - 2003 (522919), страница 99
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3:471–476.MacLennan, D. H., et al. 1990. Ryanodine receptor gene is a candidate for predisposition to malignant hyperthermia.Nature 343:559–561.35921Proteomics: A Post-Genomic Platformfor Drug Discovery and DevelopmentStephen T. RapundaloThe recent completion of the sequencing of the human genome [1, 2] has markedthe beginning of a new era in modern biology and medicine. It has spawned avariety of technologies and techniques for genomic research, gene discovery, andin particular functional genomics. Most importantly it already has provided an enormous information load that needs to be converted into a comprehensive understanding of gene function and regulation, and to new approaches in the diagnosis, prevention and treatment of diseases.Despite the power of genomic technologies and the information derived fromtheir use, it is clear that gene function, and in reality cell function, is manifestedby the activity of its protein product(s).
The poor correlation between mRNA andprotein levels (i.e., coefficients of only 0.5) [3] clearly demonstrates that genes maybe present, mutated, but not necessarily transcribed, or if so, then not translated.Proteomics, or the analysis of global patterns of gene expression at the protein level, has the potential to yield information about a system of interest that cannot beobtained by gene profiling alone, namely relative protein abundance, post-translational modifications (e.g., phosphorylation, glycosylation, acetylation, demethylation), turnover/activity, localization, and protein-protein interactions, all of whichundergo differential regulation as a result of various physiological, pharmacological or disease stimuli.
Accordingly, the true value of the genome sequence information will only be realized after a function has been assigned to all of the encoded proteins. Proteomics, and its many variant and encompassing technologicalapproaches, is destined to provide that functional information for all proteins, andbridge the gap between genomics and systems’ phenotypes.The fact that proteins constitute the vast majority of pharmaceutical targets underscores a further need to comprehend their function, location, and interactionwith other proteins in order to design new drug therapies. In turn, there is an urgency to apply high-throughput technologies for protein expression analysis, analogous to those in use for RNA profiling. Since most proteins don’t act alone,there is a need to focus on mapping protein-protein interactions and protein complexes to better understand disease pathways and the mode of action of existingdrugs. One would anticipate the identification of many more drug targets by selecting alternative points in cellular protein networks that would ultimately lead tothe development of agents with greater efficacy, specificity and safety.
This muchProteomic and Genomic Analysis of Cardiovascular Disease.Edited by Jennifer E. van Eyk, Michael J. DunnCopyright © 2003 WILEY-VCH Verlag GmbH & Co. KGaA, WeinheimISBN: 3-527-30596-336021 Proteomics in Pharmaceutical R & Dis true – whether as drug targets, or even as new drugs themselves, proteins arekey to the future of therapeutics as never before. The challenge for pharmaceutical and biotech research is to unlock the secrets of the biological systems ofchoice through modern proteomic analysis and to mine the colossal amount of information that can be unraveled from them.
This chapter describes how companies primarily, but academic investigators too, are developing their proteomicstrategies and applications in the pursuit of novel disease modifying/preventingagents and diagnostic/prognostic markers.21.1Perspectives on the Drug Discovery and Development ProcessThe pharmaceutical industry has been exceedingly attentive to the rapid strides ingenomic research and of its significant implications for identifying potentially useful molecular targets suitable for drug discovery and development.
Elucidation ofthe approximately 30,000 protein-encoding human gene sequences [1, 2] has inturn provided estimates of 3,000 to 5,000 potentially interesting protein drug targets [4]. This vastly outnumbers by an order of magnitude the number of molecular targets, i.e. about 500 gene products, accounting for all marketed drugs [5, 6].Although a significant number of proteins will belong to well-characterized families with predicted biological function, the biomedical community and pharmaceutical industry are anticipating many proteins that will be entirely novel with unknown structure and function [7]. The challenge for pharmaceutical research nowis to identify those targets amenable to drug intervention through the elucidationof the genetic and molecular pathophysiology of human diseases and development of novel biomedicine [8–10].Pharmaceutical research organizations have historically favored disease-orientedstrategies seeking to identify and validate the role of “novel” candidate targets thatare hypothesis-driven.
Typically companies were aligned by therapeutic area andperformed drug discovery and development in sequential and disciplined steps, asreviewed comprehensively by Williams [11]. This involved the identification of putative targets using low-throughput strategies. Targets were then validated thoroughly using molecular, biochemical, cellular or in vivo means before initiation ofa drug discovery effort. Thus, their relationship with a disease state was often wellestablished before chemical screening was initiated. Any identified lead compounds were optimized upon completion of chemical library profiling.
At thisstage candidate selection relied on further in vitro studies, whole animal investigations of efficacy, metabolism, pharmacokinetics and toxicokinetics, and perhapsthe development of second-generation or “backup” compounds with improvedproperties.
A broad goal of the pre-clinical evaluation was the integration ofknowledge gained from this phase into the decision-making process related to thedesign and implementation of early clinical studies. Phase 1 clinical studies, conducted in healthy subjects or, in some cases, patients, primarily would provide information on acute tolerability and safety, drug plasma levels, routes of metabo-21.1 Perspectives on the Drug Discovery and Development Processlism and elimination, and initial estimates of therapeutic variability. In turn, thedata could be used for selection of drug formulation, dosing regimens and routesof administration in the target patient population as part of the Phase II studiesevaluating efficacy.
Finally, it is in Phase III that large clinical trials are developedto provide evidence of efficacy and safety in the broader target patient population,and that adverse reaction profiles are scrutinized. This information then guidesproduct labeling and patient dosing regimens.In recent years the pharmaceutical industry has relied on technological innovations in an attempt to maximize efficiency in the drug discovery and developmentprocess. Advances in biology such as mapping of the human genome were supposed to help maintain full drug discovery pipelines. Yet the integration of novelbiotechnologies with traditional methods of drug discovery, such as screening rational design and/or combinatorial chemical libraries, has proven difficult.
Manycompounds created this way lacked characteristics that would have made themsuitable for use as safe and efficacious clinical therapies. Thus, there has been aclear fall in drug discovery and development productivity. The industry’s output ofnew and approved drug entities has only seen a modest increase despite an enormous growth of research and development funding allocations. Instead of narrowing the list of potential novel compounds that may be useful as therapies, technological advances, especially automation, have broadened it – greatly increasing thenumber of compounds validated without yet delivering commensurate growth insafe and effective drugs. It is apparent that new science and techniques are developing faster than can be utilized practically by big pharma.The last several years has been marked by a noticeable paradigm shift in the approaches that pharmaceutical companies are taking towards the discovery and development of new therapeutic agents.
As illustrated in Fig. 21.1, the process isnow one that has necessitated the acquisition and application of new skill sets, including a variety of high-throughput technologies, bioinformatics, genomics, proteomics, and metabonomics, among others. In short, this evolving paradigm aimsto integrate different information sets that ultimately will lead to a systems biology approach to the study of biological function.
The hope is that a seamless integration of target discovery, validation, drug design, safety, and clinical validation,coupled with the use of automation technologies, will result in a more efficientR&D process, and a higher quality of drug candidates entering the market.A first critical step in the drug discovery process is how to identify key targetsin disease pathways.
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