首页> 外文OA文献 >Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening and knowledge of transporters: where drug discovery went wrong and how to fix it.
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Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening and knowledge of transporters: where drug discovery went wrong and how to fix it.

机译:使用多种有效药物靶点,表型筛选和转运蛋白知识在系统生物学时代寻找新型药物:药物发现出错以及如何解决。

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摘要

Despite the sequencing of the human genome, the rate of innovative and successful drug discovery in the pharmaceutical industry has continued to decrease. Leaving aside regulatory matters, the fundamental and interlinked intellectual issues proposed to be largely responsible for this are: (a) the move from 'function-first' to 'target-first' methods of screening and drug discovery; (b) the belief that successful drugs should and do interact solely with single, individual targets, despite natural evolution's selection for biochemical networks that are robust to individual parameter changes; (c) an over-reliance on the rule-of-5 to constrain biophysical and chemical properties of drug libraries; (d) the general abandoning of natural products that do not obey the rule-of-5; (e) an incorrect belief that drugs diffuse passively into (and presumably out of) cells across the bilayers portions of membranes, according to their lipophilicity; (f) a widespread failure to recognize the overwhelmingly important role of proteinaceous transporters, as well as their expression profiles, in determining drug distribution in and between different tissues and individual patients; and (g) the general failure to use engineering principles to model biology in parallel with performing 'wet' experiments, such that 'what if?' experiments can be performed in silico to assess the likely success of any strategy. These facts/ideas are illustrated with a reasonably extensive literature review. Success in turning round drug discovery consequently requires: (a) decent systems biology models of human biochemical networks; (b) the use of these (iteratively with experiments) to model how drugs need to interact with multiple targets to have substantive effects on the phenotype; (c) the adoption of polypharmacology and/or cocktails of drugs as a desirable goal in itself; (d) the incorporation of drug transporters into systems biology models, en route to full and multiscale systems biology models that incorporate drug absorption, distribution, metabolism and excretion; (e) a return to 'function-first' or phenotypic screening; and (f) novel methods for inferring modes of action by measuring the properties on system variables at all levels of the 'omes. Such a strategy offers the opportunity of achieving a state where we can hope to predict biological processes and the effect of pharmaceutical agents upon them. Consequently, this should both lower attrition rates and raise the rates of discovery of effective drugs substantially.
机译:尽管对人类基因组进行了测序,但制药行业中创新和成功发现药物的比率一直在下降。除了监管问题,提议对此起主要作用的基本和相互联系的知识问题是:(a)从“功能第一”的筛查和药物发现方法向“目标第一”的方法转变; (b)相信,尽管自然进化选择了对个体参数变化都具有鲁棒性的生化网络,但成功的药物应该并且确实只能与单个个体目标相互作用; (c)过度依赖5法则来限制药品资料库的生物物理和化学特性; (d)普遍放弃不遵守5条规则的天然产品; (e)根据药物的亲脂性,错误地认为药物会通过膜的双层部分被动地扩散进入细胞(并可能从细胞中扩散出去); (f)普遍未能认识到蛋白质转运蛋白及其在决定不同组织与个别患者之间以及之间的药物分布方面的极其重要的作用; (g)普遍未能在进行“湿式”实验的同时使用工程原理对生物学建模,例如“假设条件如何”?可以在计算机上进行实验以评估任何策略的可能成功。这些事实/想法在相当广泛的文献综述中得到了说明。因此,要成功扭转药物发现的局面,需要:(a)人体生化网络的体面系统生物学模型; (b)使用这些方法(反复进行实验)来模拟药物如何需要与多个目标相互作用才能对表型产生实质性影响; (c)采用多元药理学和/或药物混合物本身就是一个理想的目标; (d)将药物转运蛋白纳入系统生物学模型,并逐步纳入包含药物吸收,分布,代谢和排泄的全面和多尺度系统生物学模型; (e)返回“功能优先”或表型筛选; (f)通过测量“ omes”所有级别的系统变量的属性来推断作用方式的新颖方法。这样的策略为实现一种状态提供了机会,在这种状态下我们可以预测生物过程以及药剂对它们的影响。因此,这既应降低损耗率,又应显着提高有效药物的发现率。

著录项

  • 作者

    Kell, Douglas B;

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  • 年度 2013
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  • 原文格式 PDF
  • 正文语种 eng
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