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

Area of Science:

• Systems Biology
• Network Medicine

Background:

• The study addresses the need for new therapeutic strategies against viral infections, specifically Covid-19, by exploring network medicine and cellular network control.
• It extends the concept of structural controllability to total structural controllability, introducing 'control hubs' as critical nodes within cellular networks.

Approach:

• Developed an efficient algorithm to identify control hubs within the human protein-protein interaction network, including SARS-CoV-2 interactions.
• Applied the algorithm to identify 65 druggable control hubs with significant antiviral functions.

Key Points:

• Categorized potential drugs targeting these hubs into four groups: antiviral/anti-inflammatory, CNS agents, dietary supplements, and immunity enhancers.
• Highlighted Fostamatinib as a successful example; this drug is in clinical trials for Covid-19 and has shown reduced mortality and disease severity in preclinical studies.

Conclusions:

• The findings validate a novel strategy for drug discovery by targeting control hubs in cellular networks.
• This approach offers valuable insights into the molecular mechanisms of Covid-19 therapeutics, supporting interpretable drug discovery.