MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory of Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China.
Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
Lab Chip. 2020 May 5;20(9):1577-1585. doi: 10.1039/d0lc00024h.
The dissociation constant (Kd) is a crucial parameter for characterizing binding affinity in molecular recognition, including antigen-antibody, DNA-protein, and receptor-ligand interactions. However, conventional methods for Kd characterization usually involve a multi-step process and time-consuming operations for incubation, washing, and detection, thus causing problems, such as time delays, microbead loss, degradation of sensitive molecules, and personal errors. Here we demonstrate an automated ligand binding affinity evaluation platform (Auto-affitech) using digital microfluidics (DMF), with individual droplets at the microliter level, programmed to rapidly perform the incubation and separation of target-beads and binding ligands. Because the loss of the beads influences the detection results, we propose a new strategy for magnetic bead separation using DMF, termed the bidirectional separation method. By splitting one droplet into two asymmetric droplets, high bead retention efficiency (89.57% ± 0.05%) and high washing efficiency (99.59% ± 0.17%, with four washings) were obtained. We demonstrate the determination of Kd of an aptamer-protein system (EpCAM and its corresponding aptamer SYL3C) and an antigen-antibody system (H5N1 antigen and antibody), proving the capability and universality of Auto-affitech in various receptor-ligand systems. Integrating all the sample processing procedures, the Auto-affitech not only saves manual labor and minimizes personal errors, but also conserves samples and shortens analysis time. Overall, this platform successfully demonstrates to be an automated approach for dissociation constant evaluation and exhibits great potential for highly efficient screening of ligands.
解离常数(Kd)是分子识别中表征结合亲和力的关键参数,包括抗原-抗体、DNA-蛋白质和受体-配体相互作用。然而,Kd 特征描述的传统方法通常涉及多步过程和耗时的孵育、洗涤和检测操作,因此会导致时间延迟、微球损失、敏感分子降解和人为错误等问题。在这里,我们展示了一种使用数字微流控(DMF)的自动配体结合亲和力评估平台(Auto-affitech),其使用微升至微升级别的单个液滴,编程实现目标珠和结合配体的快速孵育和分离。由于珠的损失会影响检测结果,我们提出了一种使用 DMF 的新型磁珠分离策略,称为双向分离方法。通过将一个液滴分裂成两个不对称的液滴,可以获得 89.57%±0.05%的高珠保留效率和 99.59%±0.17%的高洗涤效率(进行四次洗涤)。我们展示了适体-蛋白质系统(EpCAM 和其相应的适体 SYL3C)和抗原-抗体系统(H5N1 抗原和抗体)中 Kd 的测定,证明了 Auto-affitech 在各种受体-配体系统中的适用性和通用性。整合所有的样品处理程序,Auto-affitech 不仅节省了劳动力和最小化了人为错误,而且还节省了样品并缩短了分析时间。总的来说,该平台成功地证明了是一种用于解离常数评估的自动化方法,并显示出在高效筛选配体方面有很大的潜力。