Tenofovir antiviral drug solubility enhancement with ß-cyclodextrin inclusion complex and in silico study of potential inhibitor against SARS-CoV-2 main protease (Mpro).

Tenofovir (TFR) is an antiviral drug commonly used to fight against viral diseases infection due to its good potency and high genetic barrier to drug resistance. In physiological conditions, TFR is less water soluble, more unstable, and less permeable, limiting its effective therapeutic applications. In addition to their use in treating the Coronavirus disease 2019 (COVID-19), cyclodextrins (CDs) are also being used as a molecule to develop therapies for other diseases due to its enhance solubility and stability. This study is designed to synthesize and characterization of ß-CD:TFR inclusion complex and its interaction against SARS-CoV-2 (MPro) protein (PDB ID;7cam). Several techniques were used to characterize the prepared ß-CD:TFR inclusion complex, including UV-Visible, FT-IR, XRD, SEM, TGA, and DSC, which provided appropriate evidence to confirm the formation. A 1:1 stoichiometry was determined for ß-CD:TFR inclusion complex in aqueous medium from UV-Visible absorption spectra by using the Benesi-Hildebrand method. Phase solubility studies proposed that ß-CD enhanced the excellent solubility of TFR and the stability constant was obtained at 863 ± 32 M-1. Moreover, the molecular docking confirmed the experimental results demonstrated the most desirable mode of TFR encapsulated into the ß-CD nanocavity via hydrophobic interactions and possible hydrogen bonds. Moreover, TFR was validated in the ß-CD:TFR inclusion complex as potential inhibitors against SARS-CoV-2 main protease (Mpro) receptors by using in silico methods. The enhanced solubility, stability, and antiviral activity against SARS-CoV-2 (MPro) suggest that ß-CD:TFR inclusion complexes can be further used as feasible water-insoluble antiviral drug carriers in viral disease infection.

Genomics-guided identification of potential modulators of SARS-CoV-2 entry proteases, TMPRSS2 and Cathepsins B/L.

SARS-CoV-2 requires serine protease, transmembrane serine protease 2 (TMPRSS2), and cysteine proteases, cathepsins B, L (CTSB/L) for entry into host cells. These host proteases activate the spike protein and enable SARS-CoV-2 entry. We herein performed genomic-guided gene set enrichment analysis (GSEA) to identify upstream regulatory elements altering the expression of TMPRSS2 and CTSB/L. Further, medicinal compounds were identified based on their effects on gene expression signatures of the modulators of TMPRSS2 and CTSB/L genes. Using this strategy, estradiol and retinoic acid have been identified as putative SARS-CoV-2 alleviation agents. Next, we analyzed drug-gene and gene-gene interaction networks using 809 human targets of SARS-CoV-2 proteins. The network results indicate that estradiol interacts with 370 (45%) and retinoic acid interacts with 251 (31%) human proteins. Interestingly, a combination of estradiol and retinoic acid interacts with 461 (56%) of human proteins, indicating the therapeutic benefits of drug combination therapy. Finally, molecular docking analysis suggests that both the drugs bind to TMPRSS2 and CTSL with the nanomolar to low micromolar affinity. The results suggest that these drugs can simultaneously target both the entry pathways of SARS-CoV-2 and thus can be considered as a potential treatment option for COVID-19.

Brain Disease Network Analysis to Elucidate the Neurological Manifestations of COVID-19.

Although COVID-19 largely causes respiratory complications, it can also lead to various extrapulmonary manifestations resulting in higher mortality and these comorbidities are posing a challenge to the health care system. Reports indicate that 30-60% of patients with COVID-19 suffer from neurological symptoms. To understand the molecular basis of the neurologic comorbidity in COVID-19 patients, we have investigated the genetic association between COVID-19 and various brain disorders through a systems biology-based network approach and observed a remarkable resemblance. Our results showed 123 brain-related disorders associated with COVID-19 and form a high-density disease-disease network. The brain-disease-gene network revealed five highly clustered modules demonstrating a greater complexity of COVID-19 infection. Moreover, we have identified 35 hub proteins of the network which were largely involved in the protein catabolic process, cell cycle, RNA metabolic process, and nuclear transport. Perturbing these hub proteins by drug repurposing will improve the clinical conditions in comorbidity. In the near future, we assumed that in COVID-19 patients, many other neurological manifestations will likely surface. Thus, understanding the infection mechanisms of SARS-CoV-2 and associated comorbidity is a high priority to contain its short- and long-term effects on human health. Our network-based analysis strengthens the understanding of the molecular basis of the neurological manifestations observed in COVID-19 and also suggests drug for repurposing.