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Drug-Target Networks.

Ingo Vogt¹, Jordi Mestres²

¹Chemogenomics Laboratory, Research Program on Biomedical, Informatics (GRIB), Institut Municipal d'Investigació Mèdica & University Pompeu Fabra, Parc de Recerca Biomèdica, Doctor, Aiguader 88, 08003 Barcelona, Catalonia, Spain fax: +34 93 3160550.

Molecular Informatics

|July 28, 2016

Summary

This summary is machine-generated.

Network theory provides a powerful framework for analyzing complex drug-target interactions. This approach helps uncover cross-pharmacology relationships and identify novel drug targets, despite current data limitations.

Keywords:

Affinity fingerprint Chemogenomics Drug design Drug repurposing Molecular evolution Polypharmacology Target profiling

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Area of Science:

Pharmacology
Network Science
Cheminformatics

Background:

Traditional drug-target interaction models are insufficient for complex systems.
Large-scale interaction data necessitates advanced analytical tools.

Purpose of the Study:

To survey recent applications of drug-target networks.
To explore network theory's utility in chemical biology and molecular informatics.
To discuss limitations in current drug-target interaction data and network analysis.

Main Methods:

Application of network theory to drug-target interaction data.
Analysis of drug-target networks for cross-pharmacology and target identification.
Review of existing literature on drug-target network applications.

Main Results:

Drug-target networks effectively reveal cross-pharmacology relationships.
Network analysis facilitates the identification of new therapeutic targets for existing drugs.
Network theory offers a robust framework for complex systems analysis.

Conclusions:

Network theory is a valuable tool for understanding complex drug-target interactions.
Further improvements in data completeness and network projection methods are needed.
Drug-target networks hold significant potential for drug discovery and development.