Abediterol

The COVID-19 pandemic infection has claimed many lives and added to the social, economic, and psychological distress. The contagious disease has quickly spread to almost 218 countries and territories following the regional outbreak in China. As the number of infected populations increases exponentially, there is a pressing demand for anti-COVID drugs and vaccines. Virtual screening provides possible leads while extensively cutting down the time and resources required for ab-initio drug design. We report structure-based virtual screening of a hundred plus library of quinoline drugs with established antiviral, antimalarial, antibiotic or kinase inhibitor activity. In this study, targets having a role in viral entry, viral assembly, and viral replication have been selected. The targets include: 1) RBD of receptor-binding domain spike protein S 2) M^pro Chymotrypsin main protease 3) P^pro Papain protease 4) RNA binding domain of Nucleocapsid Protein, and 5) RNA Dependent RNA polymerase from SARS-COV-2. An in-depth analysis of the interactions and G-score compared to the controls like hydroxyquinoline and remdesivir has been presented. The salient results are (1) higher scoring of antivirals as potential drugs (2) potential of afatinib by scoring as better inhibitor, and (3) biological explanation of the potency of afatinib. Further MD simulations and MM-PBSA calculations showed that afatinib works best to interfere with the the activity of RNA dependent RNA polymerase of SARS-COV-2, thereby inhibiting replication process of single stranded RNA virus. Communicated by Ramaswamy H. Sarma.

There are few studies in humans dealing with the relationship between physico-chemical properties of drugs and their systemic bioavailability after administration via oral inhalation route (Fpulm). Getting further insight in the determinants of Fpulm after oral pulmonary inhalation could be of value for drugs considered for a systemic delivery as a result of poor oral bioavailability, as well as for drugs considered for a local delivery to anticipate their undesirable systemic effects. To better delineate the parameters influencing the systemic delivery after oral pulmonary inhalation in humans, we studied the influence of physico-chemical and permeability properties obtained in silico on the rate and extent of Fpulm in a series of 77 compounds with or without marketing approval for pulmonary delivery, and intended either for local or for systemic delivery. Principal component analysis (PCA) showed mainly that Fpulm was positively correlated with Papp and negatively correlated with %TPSA, without a significant influence of solubility and ionization fraction, and no apparent link with lipophilicity and drug size parameters. As a result of the small sample set, the performance of the different models as predictive of Fpulm were quite average with random forest algorithm displaying the best performance. As a whole, the different models captured between 50 and 60% of the variability with a prediction error of less than 20%. Tmax data suggested a significant positive influence of lipophilicity on absorption rate while charge apparently had no influence. A significant linear relationship between Cmax and dose (R² = "0.79) highlighted that Cmax was primarily dependent on dose and absorption rate and could be used to estimate Cmax in humans for new inhaled drugs.