Noble Denis
University Laboratory of Physiology, Parks Road, Oxford OX1 3PT, UK.
Trends Biotechnol. 2003 Aug;21(8):333-7. doi: 10.1016/S0167-7799(03)00162-8.
The successful identification of drug targets requires an understanding of the high-level functional interactions between the key components of cells, organs and systems, and how these interactions change in disease states. This information does not reside in the genome, or in the individual proteins that genes code for, it is to be found at a higher level. Genomics will succeed in revolutionising pharmaceutical research and development only if these interactions are also understood by determining the logic of healthy and diseased states. The rapid growth in biological databases, models of cells, tissues and organs, and in computing power has made it possible to explore functionality all the way from the level of genes to whole organs and systems. Combined with genomic and proteomic data, in silico simulation technology is set to transform all stages of drug discovery and development. The major obstacle to achieving this will be obtaining the relevant experimental data at levels higher than genomics and proteomics.
成功识别药物靶点需要了解细胞、器官和系统的关键组成部分之间的高层次功能相互作用,以及这些相互作用在疾病状态下如何变化。这些信息并不存在于基因组中,也不存在于基因编码的单个蛋白质中,而是存在于更高层次上。只有通过确定健康和疾病状态的逻辑来理解这些相互作用,基因组学才能成功地彻底改变药物研发。生物数据库、细胞、组织和器官模型以及计算能力的快速增长,使得从基因水平到整个器官和系统的功能探索成为可能。结合基因组和蛋白质组数据,计算机模拟技术将改变药物发现和开发的各个阶段。实现这一目标的主要障碍将是获得高于基因组学和蛋白质组学水平的相关实验数据。