排名(信息检索)
离群值
计算机科学
度量(数据仓库)
酶抑制
功能(生物学)
实验数据
生物系统
生化工程
组合化学
化学
数据挖掘
酶
数学
生物化学
情报检索
统计
生物
人工智能
工程类
进化生物学
作者
Gary W. Caldwell,Zhengyin Yan,Wensheng Lang,John A. Masucci
标识
DOI:10.2174/156802612800672844
摘要
A major strategy used in drug design is the inhibition of enzyme activity. The ability to accurately measure the concentration of the inhibitor which is required to inhibit a given biological or biochemical function by half is extremely important in ranking compounds. Since the concept of the half maximal inhibitory concentration (IC(50)) is used extensively for studying reversible inhibition enzymatic reactions, it is important to clearly understand the experimental design and the mathematical modeling techniques used to generate IC(50) values. The most important part of the experimental design is to measure the rate of production of [P] during the linear phase of the time course of the reaction and to prove that the enzyme-catalyzed reaction is reversible. The most important part of the mathematical modeling is to select the correct model and to have a firm understanding on how to handle outliers in the data. These topics are discussed in greater detail along with a discussion on how much quantitative and mechanistic information can be reasonably deduced from an experiment.
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