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Network medicine has been pursued for Covid-19 drug repurposing. One suchapproach adopts structural controllability, a theory for controlling a network(the cell). Motivated to protect the cell from viral infections, we extendedthis theory to total controllability and introduced a new concept of controlhubs. Perturbation to any control hub renders the cell uncontrollable byexogenous stimuli, e.g., viral infections, so control hubs are ideal drugtargets. We developed an efficient algorithm for finding all control hubs andapplied it to the largest homogenous human protein-protein interaction network.Our new method outperforms several popular gene-selection methods, includingthat based on structural controllability. The final 65 druggable control hubsare enriched with functions of cell proliferation, regulation of apoptosis, andresponses to cellular stress and nutrient levels, revealing critical pathwaysinduced by SARS-CoV-2. These druggable control hubs led to drugs in 4 majorcategories: antiviral and anti-inflammatory agents, drugs on central nervesystems, and dietary supplements and hormones that boost immunity. Theirfunctions also provided deep insights into the therapeutic mechanisms of thedrugs for Covid-19 therapy, making the new approach an explainable drugrepurposing method. A remarkable example is Fostamatinib that has been shown tolower mortality, shorten the length of ICU stay, and reduce disease severity ofhospitalized Covid-19 patients. The drug targets 10 control hubs, 9 of whichare kinases that play key roles in cell differentiation and programmed death.One such kinase is RIPK1 that directly interacts with viral protein nsp12, theRdRp of the virus. The study produced many control hubs that were not targetsof existing drugs but were enriched with proteins on membranes and theNF-$\kappa$B pathway, so are excellent candidate targets for new drugs.

Total controllability analysis discovers explainable drugs for Covid-19 treatment