可药性
药物发现
铅(地质)
计算生物学
片段(逻辑)
鉴定(生物学)
药物靶点
计算机科学
虚拟筛选
药物开发
药品
医学
化学信息学
药理学
小分子
生物
生物信息学
遗传学
算法
古生物学
基因
作者
Fredrik Edfeldt,R.H.A. Folmer,Alexander L. Breeze
标识
DOI:10.1016/j.drudis.2011.02.002
摘要
F A l w i p T s a p i c c 2 e g Target druggability – ligandability It is estimated that only 1% of drug discovery projects make it to market industry-wide. There is increasing regulatory pressure for new products to show significant improvement over existing therapies. Despite genomic initiatives, only three new targets are addressed each year with synthetic drugs [1]. Late-stage failure in clinical trials are costly, therefore significant cost savings will be achieved by improving the selection of protein targets and selecting winning projects early on in the process. Thus, pharmaceutical companies face a major challenge today: we need to reduce attrition throughout the drug discovery process to reduce cost and increase success rates while, at the same time, exploiting novel mechanisms for new drugs – to differentiate from competitors. The term ‘druggability’ usually refers to the likelihood of finding orally bioavailable small molecules that bind to a particular target in a disease-modifying way [2]. Unless there are other known compounds, either on the market or in clinical trials, acting on a particular target, intrinsic druggability is unknown. It is, therefore, useful to distinguish the ability of a target to bind small molecules from the more complex pharmacokinetic and pharmacodynamic mechanisms included in the term druggability. In recent years, the term druggability has increasingly
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