Yang Yongliang, Zeng Bixi, Sun Zhiyong, Esfahani Amir Monemian, Hou Jing, Jiao Nian-Dong, Liu Lianqing, Chen Liangliang, Basson Marc D, Dong Lixin, Yang Ruiguo, Xi Ning
Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48823, USA.
Departments of Surgery and Biomedical Sciences, University of North Dakota, Grand Forks, ND, 58202, USA.
IEEE Trans Nanotechnol. 2019;18:509-517. doi: 10.1109/tnano.2019.2915507. Epub 2019 May 14.
Increasingly targeted in drug discovery, protein-protein interactions challenge current high throughput screening technologies in the pharmaceutical industry. Developing an effective and efficient method for screening small molecules or compounds is critical to accelerate the discovery of ligands for enzymes, receptors and other pharmaceutical targets. Here, we report developments of methods to increase the signal-to-noise ratio (SNR) for screening protein-protein interactions using atomic force microscopy (AFM) force spectroscopy. We have demonstrated the effectiveness of these developments on detecting the binding process between focal adhesion kinases (FAK) with protein kinase B (Akt1), which is a target for potential cancer drugs. These developments include optimized probe and substrate functionalization processes and redesigned probe-substrate contact regimes. Furthermore, a statistical-based data processing method was developed to enhance the contrast of the experimental data. Collectively, these results demonstrate the potential of the AFM force spectroscopy in automating drug screening with high throughput.
在药物研发中，蛋白质-蛋白质相互作用越来越成为研究目标，这对制药行业当前的高通量筛选技术提出了挑战。开发一种有效且高效的小分子或化合物筛选方法对于加速酶、受体及其他药物靶点配体的发现至关重要。在此，我们报告了利用原子力显微镜（AFM）力谱法提高蛋白质-蛋白质相互作用筛选信噪比（SNR）的方法进展。我们已经证明了这些进展在检测粘着斑激酶（FAK）与蛋白激酶B（Akt1）之间结合过程中的有效性，Akt1是潜在抗癌药物的靶点。这些进展包括优化探针和底物功能化过程以及重新设计探针-底物接触模式。此外，还开发了一种基于统计的数据处理方法以增强实验数据的对比度。总体而言，这些结果证明了AFM力谱法在高通量自动化药物筛选中的潜力。
