KAIST, Department of Bio and Brain Engineering, 335 Gwahak-ro, Yuseong-gu, Daejeon, 305-701 Korea, Republic of Korea +82 42 350 4317 ; +82 42 350 4310 ;
Expert Opin Drug Discov. 2009 Nov;4(11):1177-89. doi: 10.1517/17460440903322234. Epub 2009 Oct 13.
One of the most recent and important developments in drug discovery is a new drug development approach of building and analyzing networks that contain relationships among drugs and targets, diseases, genes and other components. These networks and their integrations provide useful information for finding new targets as well as new drugs.
This review article aims to review recent developments in various types of networks and suggest the future direction of these network studies for drug discovery.
Databases and networks are integrated into a more complete network to better present the relationships among drugs, targets, genes, phenotypes and diseases. After discussing the limitations and obstacles of the recent research, we suggest several strategies to build a successful and practical drug-target network.
RESULTS/CONCLUSION: A useful, integrated network can be built from various databases and networks by resolving several issues, such as limited coverage and inconsistency. This integrated network can be completed by the prediction of missing links, biological network comparison and drug target identification. Possible applications are multi-target drug development, drug repurposing, estimation of drug effect on target perturbations in the whole system and extraction of the suitable purpose of the drug-target sub-network.
药物发现领域最近出现了一个非常重要的新进展，即建立和分析包含药物与靶点、疾病、基因和其他成分之间关系的网络。这些网络及其整合为寻找新靶点和新药提供了有用的信息。
本文旨在综述各种类型网络的最新进展，并为药物发现中的网络研究提出未来的方向。
将数据库和网络整合到一个更完整的网络中，以更好地呈现药物、靶点、基因、表型和疾病之间的关系。在讨论了近期研究的局限性和障碍之后，我们提出了几种构建成功实用的药物-靶点网络的策略。
结果/结论：通过解决覆盖范围有限和不一致等问题，可以从各种数据库和网络中构建出有用的综合网络。通过预测缺失的链接、生物网络比较和药物靶点识别，可以完成这个综合网络。可能的应用包括多靶点药物开发、药物重定位、估计药物对整个系统中靶点扰动的影响以及提取药物-靶点子网络的合适用途。
