Network Crosstalk as a Basis for Drug Repurposing.

Area of Science:

• Computational Biology
• Pharmacology
• Bioinformatics

Background:

• Systematic drug repurposing is increasingly important, particularly for addressing pandemics.
• Functional interaction data enables mapping of the human interactome using functional association networks, supporting network-based drug repurposing.
• Network crosstalk-based approaches have not been previously evaluated for drug repurposing, despite their success in pathway enrichment analysis.

Purpose of the Study:

• To evaluate the performance of network crosstalk-based approaches for drug repurposing.
• To develop a new benchmark for assessing network-based drug repurposing tools using updated interaction data and integration methods.
• To compare network crosstalk-based methods against a state-of-the-art technique.

Main Methods:

• Evaluation of top-performing network crosstalk-based approaches for drug repurposing.
• Construction of a new benchmark for performance assessment of network-based drug repurposing tools.
• Comparison of network crosstalk-based methods with a state-of-the-art technique using the new benchmark.

Main Results:

• Network crosstalk-based drug repurposing methods demonstrate competitive performance.
• These methods can rival, and in some cases, outperform the current state-of-the-art technique.
• The newly developed benchmark facilitated a robust comparison of different network-based approaches.

Conclusions:

• Network crosstalk-based approaches are a viable and effective strategy for drug repurposing.
• These methods offer a promising alternative or complement to existing state-of-the-art techniques.
• Further investigation into network crosstalk for drug discovery is warranted.