Technical University of Denmark, Center for Biological Sequence Analysis, Department of Systems Biology , Lyngby , Denmark.
Expert Opin Drug Metab Toxicol. 2013 Nov;9(11):1409-18. doi: 10.1517/17425255.2013.820704. Epub 2013 Aug 12.
The high failure rate of drug candidates due to toxicity, during clinical trials, is a critical issue in drug discovery. Network biology has become a promising approach, in this regard, using the increasingly large amount of biological and chemical data available and combining it with bioinformatics. With this approach, the assessment of chemical safety can be done across multiple scales of complexity from molecular to cellular and system levels in human health. Network biology can be used at several levels of complexity.
This review describes the strengths and limitations of network biology. The authors specifically assess this approach across different biological scales when it is applied to toxicity.
There has been much progress made with the amount of data that is generated by various omics technologies. With this large amount of useful data, network biology has the opportunity to contribute to a better understanding of a drug's safety profile. The authors believe that considering a drug action and protein's function in a global physiological environment may benefit our understanding of the impact some chemicals have on human health and toxicity. The next step for network biology will be to better integrate differential and quantitative data.
在临床试验中，由于毒性而导致候选药物的高失败率是药物发现中的一个关键问题。网络生物学已经成为一种很有前途的方法，它利用越来越多的可用生物和化学数据，并结合生物信息学。通过这种方法，可以在从分子到细胞和系统水平的多个复杂程度尺度上评估化学安全性。网络生物学可以在不同的复杂程度级别上使用。
这篇综述描述了网络生物学的优缺点。作者特别评估了这种方法在应用于毒性时在不同的生物学尺度上的效果。
随着各种组学技术生成的数据量的增加，已经取得了很大的进展。有了大量有用的数据，网络生物学有机会为更好地了解药物的安全性概况做出贡献。作者认为，考虑药物作用和蛋白质在全局生理环境中的功能，可以帮助我们了解某些化学物质对人类健康和毒性的影响。网络生物学的下一步将是更好地整合差异和定量数据。
