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原文_Network pharmacology:the next paradigm in drug discovery

原文_Network pharmacology:the next paradigm in drug discovery

原文_Network pharmacology:the next paradigm in drug discovery

Network pharmacology:the next paradigm in drug discovery

Andrew L Hopkins

The dominant paradigm in drug discovery is the concept of designing maximally selective ligands to act on individual drug targets.However,many effective drugs act via modulation of multiple proteins rather than single targets.Advances in systems biology are revealing a phenotypic robustness and a network structure that strongly suggests that exquisitely selective compounds,compared with multitarget drugs,may exhibit lower than desired clinical ef?cacy.This new appreciation of the role of

polypharmacology has signi?cant implications for tackling the two major sources of attrition in drug development—ef?cacy and toxicity.Integrating network biology and polypharmacology holds the promise of expanding the current opportunity space for druggable targets.However,the rational design of polypharmacology faces considerable challenges in the need for new methods to validate target combinations and optimize multiple structure-activity relationships while maintaining drug-like properties.Advances in these areas are creating the foundation of the next paradigm in drug discovery:network pharmacology.

Over the past decade,there has been a signi?cant decrease in the rate that new drug candidates are being translated into effective therapies in the clinic.In particular,there has been a worrying rise in late-stage attrition in phase 2and phase 3(ref.1).Currently,the two single most important reasons for attrition in clinical development are (i)lack of ef?cacy and (ii)clinical safety or toxicology,which each account for 30%of failures 1.These late-stage attrition rates are at the heart of much of the relative decline in productivity of the pharmaceutical industry.Moreover,the decline in productivity is creating a major ?nancial shock to the pharmaceutical industry.Owing to patents expiring on the current generation of marketed drugs,from 2010onward,phar-maceutical companies will face the ?rst fall in revenue in four decades.Many reasons have been proposed for this decline in pharmaceu-tical research and development productivity.However,the funda-mental problem may not be technological,environmental or even scienti?c but philosophical—there may be issues with the core assumptions that frame our approach to drug discovery.The increase in the rate of drugs failing in late-stage clinical development over the past decade has been concurrent with the dominance of the assump-tion that the goal of drug discovery is to design exquisitely selective ligands that act on a single disease target.This philosophy of rational drug design,or more speci?cally,the ‘one gene,one drug,one disease’paradigm,arose from a congruence between genetic reductionism and new molecular biology technologies that enabled the isolation and characterization of individual ‘disease-causing’genes 2,thereby enabling the full realization of Ehrlich’s philosophy of ‘magic bullets’targeting individual chemoreceptors 3.The underlying assumption of the current approach is that safer,more effective drugs will result from

designing very selective ligands where undesirable and potentially toxic side activities have been removed.However,after nearly two decades of focusing on developing highly selective ligands,the clinical attrition ?gures challenge this hypothesis.

Need for a one-two punch

Clinical attrition rates are not the only data to challenge the current paradigm in drug http://www.jjswz.tw/doc/60cd8d075a8102d276a22fda.htmlrge-scale functional genomics studies in a variety of model organisms have revealed that under laboratory conditions,many single-gene knockouts by themselves exhibit little or no effect on phenotype,with approximately 19%of genes being essential across a number of model organisms 4–6.In addition to the 19%lethality rate,systematic genome-wide homozygous gene deletion experiments in yeast reveal that only 15%of knockouts result in a ?tness defect in ideal conditions 7.A project to delete each of the druggable genes 8in the mouse genome and pro?le each knockout across a battery of phenotypic assays has revealed that as few as 10%of knockouts demonstrate phenotypes that may be of value for drug target validation 4,9–11.

This robustness of phenotype can be understood in terms of redundant functions and alternative compensatory signaling routes http://www.jjswz.tw/doc/60cd8d075a8102d276a22fda.htmlwork analysis of biological pathways and interactions has revealed that much of the robustness of biological systems can derive from the structure of the network 13,14.The scale-free nature of many biological networks results in systems that are resilient against random deletion of any one node but that are also critically dependent on a few highly connected hubs.The inherent robustness of interaction networks,as an underlying property,has profound implications for drug discovery;instead of searching for the ‘disease-causing’genes,network biology suggests that the strategy should be to identify the perturbations in the disease-causing network 15.

Network biology analysis predicts that if,in most cases,deletion of individual nodes has little effect on disease networks,modulating

Published online 20October 2008;doi:10.1038/nchembio.118

Division of Biological Chemistry and Drug Discovery,College of Life Science,University of Dundee,Dow Street,Dundee DD13DF,UK.Correspondence should be addressed to A.L.H.([email protected]://www.jjswz.tw/doc/60cd8d075a8102d276a22fda.html).

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82VOLUME 4NUMBER 11NOVEMBER 2008NATURE CHEMICAL BIOLOGY

? 2008 N a t u r e P u b l i s h i n g G r o u p h t t p ://w w w .n a t u r e .c o m /n a t u r e c h e m i c a l b i o l o g y

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