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

BACKGROUND: The active pursuit of network medicine for drug repurposing, particularly for combating Covid-19, has stimulated interest in the concept of structural controllability in cellular networks. We sought to extend this theory, focusing on the defense rather than control of the cell against viral infections. Accordingly, we extended structural controllability to total structural controllability and introduced the concept of control hubs. Perturbing any control hub may render the cell uncontrollable by exogenous stimuli like viral infections, so control hubs are ideal drug targets. RESULTS: We developed an efficient algorithm to identify all control hubs, applying it to a largest homogeneous network of human protein interactions, including interactions between human and SARS-CoV-2 proteins. Our method recognized 65 druggable control hubs with enriched antiviral functions. Utilizing these hubs, we categorized potential drugs into four groups: antiviral and anti-inflammatory agents, drugs acting on the central nervous system, dietary supplements, and compounds enhancing immunity. An exemplification of our approach's effectiveness, Fostamatinib, a drug initially developed for chronic immune thrombocytopenia, is now in clinical trials for treating Covid-19. Preclinical trial data demonstrated that Fostamatinib could reduce mortality rates, ICU stay length, and disease severity in Covid-19 patients. CONCLUSIONS: Our findings confirm the efficacy of our novel strategy that leverages control hubs as drug targets. This approach provides insights into the molecular mechanisms of potential therapeutics for Covid-19, making it a valuable tool for interpretable drug discovery. Our new approach is general and applicable to repurposing drugs for other diseases.

Comparative genomics of the medicinal plants Lonicera macranthoides and L. japonica provides insight into genus genome evolution and hederagenin-based saponin biosynthesis.

Lonicera macranthoides (LM) and L. japonica (LJ) are medicinal plants widely used in treating viral diseases, such as COVID-19. Although the two species are morphologically similar, their secondary metabolite profiles are significantly different. Here, metabolomics analysis showed that LM contained ~86.01 mg/g hederagenin-based saponins, 2000-fold higher than LJ. To gain molecular insights into its secondary metabolite production, a chromosome-level genome of LM was constructed, comprising 9 pseudo-chromosomes with 40 097 protein-encoding genes. Genome evolution analysis showed that LM and LJ were diverged 1.30-2.27 million years ago (MYA). The two plant species experienced a common whole-genome duplication event that occurred ∼53.9-55.2 MYA before speciation. Genes involved in hederagenin-based saponin biosynthesis were arranged in clusters on the chromosomes of LM and they were more highly expressed in LM than in LJ. Among them, oleanolic acid synthase (OAS) and UDP-glycosyltransferase 73 (UGT73) families were much more highly expressed in LM than in LJ. Specifically, LmOAS1 was identified to effectively catalyse the C-28 oxidation of ß-Amyrin to form oleanolic acid, the precursor of hederagenin-based saponin. LmUGT73P1 was identified to catalyse cauloside A to produce α-hederin. We further identified the key amino acid residues of LmOAS1 and LmUGT73P1 for their enzymatic activities. Additionally, comparing with collinear genes in LJ, LmOAS1 and LmUGT73P1 had an interesting phenomenon of 'neighbourhood replication' in LM genome. Collectively, the genomic resource and candidate genes reported here set the foundation to fully reveal the genome evolution of the Lonicera genus and hederagenin-based saponin biosynthetic pathway.