Quantifying the Interactions between Biomolecules: Guidelines for Assay Design and Data Analysis

被引:41
|
作者
Tonge, Peter J. [1 ,2 ]
机构
[1] SUNY Stony Brook, Dept Chem, Ctr Adv Study Drug Act, John S Toll Dr, Stony Brook, NY 11794 USA
[2] SUNY Stony Brook, Dept Radiol, Ctr Adv Study Drug Act, John S Toll Dr, Stony Brook, NY 11794 USA
来源
ACS INFECTIOUS DISEASES | 2019年 / 5卷 / 06期
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
binding; concentration (dose)-response curves; IC50; nonlinear regression; replicates; reproducibility; SURFACE-PLASMON RESONANCE; SLOW-BINDING INHIBITION; KINETICS; PROTEIN; LIGAND; EQUILIBRIUM; MECHANISM; RECEPTOR; CONSTANTS; IMPACT;
D O I
10.1021/acsinfecdis.9b00012
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
The accurate and precise determination of binding interactions plays a central role in fields such as drug discovery where structure-activity relationships guide the selection and optimization of drug leads. Binding is often assessed by monitoring the response caused by varying one of the binding partners in a functional assay or by using methods where the concentrations of free and/or bound ligand can be directly determined. In addition, there are also many approaches where binding leads to a change in the properties of the binding partner(s) that can be directly quantified such as an alteration in mass or in a spectroscopic signal. The analysis of data resulting from these techniques invariably relies on computer software that enable rapid fitting of the data to nonlinear multiparameter equations. The objective of this Perspective is to serve as a reminder of the basic assumptions that are used in deriving these equations and thus that should be considered during assay design and subsequent data analysis. The result is a set of guidelines for authors considering submitting their work to journals such as ACS Infectious Diseases.
引用
收藏
页码:796 / 808
页数:25
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