Therapeutic Strategies in the Fight against COVID-19: From Bench to Bedside.

In December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in China. This virus rapidly spread worldwide and was declared a global pandemic by the World Health Organization (WHO) in March 2020. High incidence, long incubation period, and diverse clinical signs of the disease posed a huge challenge globally. The efforts of health systems have been focused on repurposing existing drugs or developing innovative therapies to reduce the morbidity and mortality associated with SARS-CoV-2. In addition, most of the large pharmaceutical companies are intensely working on vaccine development to swiftly deliver safe and effective vaccines to prevent further spread of the virus. In this review, we will discuss the latest data on therapeutic strategies undergoing clinical trials. Additionally, we will provide a summary of vaccines currently under development.

Discovery of new TLR7 agonists by a combination of statistical learning-based QSAR, virtual screening, and molecular dynamics.

Search for new antiviral medications has surged in the past two years due to the COVID-19 crisis. Toll-like receptor 7 (TLR7) is among one of the most important TLR proteins of innate immunity that is responsible for broad antiviral response and immune system control. TLR7 agonists, as both vaccine adjuvants and immune response modulators, are among the top drug candidates for not only our contemporary viral pandemic but also other diseases. The agonists of TLR7 have been utilized as vaccine adjuvants and antiviral agents. In this study, we hybridized a statistical learning-based QSAR model with molecular docking and molecular dynamics simulation to extract new antiviral drugs by drug repurposing of the DrugBank database. First, we manually curated a dataset consisting of TLR7 agonists. The molecular descriptors of these compounds were extracted, and feature engineering was done to restrict the number of features to 45. We applied a statistically inspired modification of the partial least squares (SIMPLS) method to build our QSAR model. In the next stage, the DrugBank database was virtually screened structurally using molecular docking, and the top compounds for the guanosine binding site of TLR were identified. The result of molecular docking was again screened by the ligand-based approach of QSAR to eliminate compounds that do not display strong EC50 values by the previously trained model. We then subjected the final results to molecular dynamics simulation and compared our compounds with imiquimod (an FDA-approved TLR7 agonist) and compound 1 (the most active compound against TLR7 in vitro, EC50 = 0.2 nM). Our results evidently demonstrate that cephalosporins and nucleotide analogues (especially acyclic nucleotide analogues such as adefovir and cidofovir) are computationally potent agonists of TLR7. We finally reviewed some publications about cephalosporins that, just like pieces of a puzzle, completed our conclusion.