Winnifrith Adam, Brown Steven R, Jedryszek Piotr, Grant C, Kay Philip E, Thomas Adam M, Bradbury Jacob D, Lanyon-Hogg Thomas
Department of Pharmacology, University of Oxford OX1 3QT UK
Synthace 4th Floor The Westworks, 195 Wood Lane London W12 7FQ UK.
RSC Chem Biol. 2025 Mar 17;6(5):772-779. doi: 10.1039/d4cb00291a. eCollection 2025 May 8.
Biochemical assays are essential tools in biological research and drug discovery, but optimisation of these assays is often a challenging and lengthy process due to the wide range of input variables and the complex effects of these variables on one another. Traditional 'one-factor-at-a-time' optimisation is both time-consuming and fails to explore the full range of input combinations. In contrast, the modern 'design of experiments' (DoE) approach enables simultaneous investigation of multiple input variables and their interactions, leading to more information-rich and efficient experimentation. We therefore sought to apply DoE to the optimisation of a new fluorescence-based assay for the enzyme RecBCD, a helicase-nuclease-ATPase complex involved in bacterial stress responses. A novel 'functional data analysis' (FDA) approach was used to predict the shape of RecBCD reaction curves in response to different combinations of input variables, which successfully identified assay conditions suitable for drug screening. Collectively, this work delivers a new assay for the antibiotic target RecBCD and demonstrates the potential of DoE and FDA to accelerate biochemical assay development.
生化分析是生物学研究和药物发现中的重要工具，但由于输入变量范围广泛以及这些变量之间的复杂相互作用，这些分析方法的优化通常是一个具有挑战性且耗时的过程。传统的“一次一个因素”优化方法既耗时又无法探索所有输入组合。相比之下，现代的“实验设计”（DoE）方法能够同时研究多个输入变量及其相互作用，从而实现更丰富的信息和更高效的实验。因此，我们试图将DoE应用于一种新的基于荧光的RecBCD酶分析方法的优化，RecBCD是一种参与细菌应激反应的解旋酶-核酸酶-ATP酶复合物。一种新颖的“功能数据分析”（FDA）方法被用于预测RecBCD反应曲线在不同输入变量组合下的形状，该方法成功确定了适合药物筛选的分析条件。总的来说，这项工作为抗生素靶点RecBCD提供了一种新的分析方法，并证明了DoE和FDA在加速生化分析方法开发方面的潜力。
