Building a drug–target network and its applications

Abstract

Background: 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. Objective: 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. Methods: 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.

Keywords::

• drug–disease network
• drug–target network
• network analysis
• network integration
• target identification

Acknowledgement

We thank Byung-Chul Lee and the members of Protein Bio-Informatics Laboratory (PBIL) for helpful discussions. S Lee and K Park contributed equally to this work.

Notes