ABSTRACT
The spike (S) glycoprotein and nucleocapsid (N) proteins are the crucial pathogenic proteins of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS CoV-2) virus during its interaction with the host. Even FDA-approved drugs like dexamethasone and grazoprevir are not able to curb the viral progression inside the host and are reported with adverse effects on body metabolism. In this context, we aim to report corilagin a novel, potential dual inhibitor of S and N proteins from Terminalia chebula. The bioactive compounds of T. chebula were subjected to a series of computational investigations including molecular docking simulations, molecular dynamics (MD) simulations, binding free energy calculations, and PASS pharmacological analysis. The results obtained from these studies revealed that corilagin was highly interactive with the S (-8.9 kcal/mol) and N (-9.2 kcal/mol) proteins, thereby showing dual inhibition activity. It was also found to be stable enough to induce biological activity inside the inhibitor binding pocket of the target enzymes throughout the dynamics simulation run for 100 ns. This is also confirmed by the changes in the protein conformations, evaluated using free energy landscapes. Outcomes from this investigation identify corilagin as the lead potential dual inhibitor of S and N proteins of SARS-CoV-2, which could be taken for biological studies in near future.Communicated by Ramaswamy H. Sarma.
ABSTRACT
To estimate the reproductive number (R0) of the coronavirus in the present scenario and to predict the incidence of daily and probable cumulative cases, by 20 August, 2020 for Karnataka state in India. The model used serial interval with a gamma distribution and applied 'early R' to estimate the R0 and 'projections' package in R program. This was performed to mimic the probable cumulative epidemic trajectories and predict future daily incidence by fitting the data to existing daily incidence and the estimated R0 by a model based on the assumption that daily incidence follows Poisson distribution. The maximum-likelihood (ML) value of R0 was 2.242 for COVID-19 outbreak, as on June 2020. The median with 95% CI of R0 values was 2.242 (1.50-3.00) estimated by bootstrap resampling method. The expected number of new cases for the next 60 days would progressively increase, and the estimated cumulative cases would reach 27,238 (26,008-28,467) at the end of 60th day in the future. But, if R0 value was doubled the estimated total number of cumulative cases would increase up to 432,411 (400,929-463,893) and if, R0 increase by 50%, the cases would increase up to 86,386 (80,910-91,861). The probable outbreak size and future daily cumulative incidence are largely dependent on the change in R0 values. Hence, it is vital to expedite the hospital provisions, medical facility enhancement work, and number of random tests for COVID-19 at a very rapid pace to prepare the state for exponential growth in next 2 months.