Total network controllability analysis discovers explainable drugs for Covid-19 treatment

Area of Science:

• Network medicine
• Systems biology
• Computational biology

Background:

• Network medicine and drug repurposing are crucial for combating diseases like Covid-19.
• Structural controllability in cellular networks is a key concept for understanding disease mechanisms.
• Extending controllability theory to identify cellular defense mechanisms against viral infections is of significant interest.

Purpose of the Study:

• To extend structural controllability to total structural controllability.
• To introduce and define the concept of control hubs within cellular networks.
• To identify control hubs as potential drug targets for therapeutic intervention against viral infections.

Main Methods:

• Developed an efficient algorithm to identify all control hubs in a network.
• Applied the algorithm to a large human protein-protein interaction network, including SARS-CoV-2 interactions.
• Analyzed identified control hubs for druggability and enrichment of antiviral functions.

Main Results:

• Identified 65 druggable control hubs with significant antiviral functions.
• Categorized potential drugs targeting these hubs into four groups: antiviral/anti-inflammatory, CNS-acting, dietary supplements, and immunity enhancers.
• Demonstrated the efficacy of Fostamatinib, a repurposed drug, in preclinical Covid-19 studies, showing reduced mortality and disease severity.

Conclusions:

• Validated a novel strategy using control hubs as drug targets for interpretable drug discovery.
• Provided insights into molecular mechanisms of potential Covid-19 therapeutics.
• Established the general applicability of this approach for drug repurposing in other diseases.