Xin Hong, Bernal Alejandro, Amato Frank A, Pinhasov Albert, Kauffman Jack, Brenneman Douglas E, Derian Claudia K, Andrade-Gordon Patricia, Plata-Salamán Carlos R, Ilyin Sergey E
Johnson & Johnson Pharmaceutical Research & Development LLC, Welsh and McKean Roads, Spring House, PA 19477-0776, USA.
J Biomol Screen. 2004 Jun;9(4):286-93. doi: 10.1177/1087057104263533.
The drug discovery process pursued by major pharmaceutical companies for many years starts with target identification followed by high-throughput screening (HTS) with the goal of identifying lead compounds. To accomplish this goal, significant resources are invested into automation of the screening process or HTS. Robotic systems capable of handling thousands of data points per day are implemented across the pharmaceutical sector. Many of these systems are amenable to handling cell-based screening protocols as well. On the other hand, as companies strive to develop innovative products based on novel mechanisms of action(s), one of the current bottlenecks of the industry is the target validation process. Traditionally, bioinformatics and HTS groups operate separately at different stages of the drug discovery process. The authors describe the convergence and integration of HTS and bioinformatics to perform high-throughput target functional identification and validation. As an example of this approach, they initiated a project with a functional cell-based screen for a biological process of interest using libraries of small interfering RNA (siRNA) molecules. In this protocol, siRNAs function as potent gene-specific inhibitors. siRNA-mediated knockdown of the target genes is confirmed by TaqMan analysis, and genes with impacts on biological functions of interest are selected for further analysis. Once the genes are confirmed and further validated, they may be used for HTS to yield lead compounds.
多年来,大型制药公司所采用的药物研发过程始于靶点识别,随后是高通量筛选(HTS),目的是识别先导化合物。为实现这一目标,大量资源被投入到筛选过程或高通量筛选的自动化中。制药行业广泛采用了每天能够处理数千个数据点的机器人系统。其中许多系统也适用于处理基于细胞的筛选方案。另一方面,随着公司努力基于新的作用机制开发创新产品,目前该行业的瓶颈之一是靶点验证过程。传统上,生物信息学和高通量筛选团队在药物研发过程的不同阶段独立运作。作者描述了高通量筛选与生物信息学的融合与整合,以进行高通量靶点功能识别和验证。作为这种方法的一个例子,他们启动了一个项目,使用小干扰RNA(siRNA)分子文库对感兴趣的生物学过程进行基于细胞的功能筛选。在这个方案中,siRNA作为有效的基因特异性抑制剂发挥作用。通过TaqMan分析确认siRNA介导的靶基因敲低,并选择对感兴趣的生物学功能有影响的基因进行进一步分析。一旦基因得到确认和进一步验证,它们可用于高通量筛选以产生先导化合物。