Repurposing of approved drug molecules for viral infectious diseases: a molecular modelling approach.

The identification of new viral drugs has become a task of paramount significance due to the frequent occurrence of viral infections and especially during the current pandemic. Despite the recent advancements, the development of antiviral drugs has not made parallel progress. Reduction of time frame and cost of the drug development process is the major advantage of drug repurposing. Therefore, in this study, a drug repurposing strategy using molecular modelling techniques, i.e. biological activity prediction, virtual screening, and molecular dynamics simulation was employed to find promising repurposing candidates for viral infectious diseases. The biological activities of non-redundant (4171) drug molecules were predicted using PASS analysis, and 1401 drug molecules were selected which showed antiviral activities in the analysis. These drug molecules were subjected to virtual screening against the selected non-structural viral proteins. A series of filters, i.e. top 10 drug molecules based on binding affinity, mean value of binding affinity, visual inspection of protein-drug complexes, and number of H-bond between protein and drug molecules were used to narrow down the drug molecules. Molecular dynamics simulation analysis was carried out to validate the intrinsic atomic interactions and binding conformations of protein-drug complexes. The binding free energies of drug molecules were assessed by employing MMPBSA analysis. Finally, nine drug molecules were prioritized, as promising repurposing candidates with the potential to inhibit the selected non-structural viral proteins.Communicated by Ramaswamy H. Sarma.

Modeling Covid-19 contagious effect between asset markets and commodity futures in India

For the purpose of optimizing an investment portfolio in the Indian market, this research provides an understanding of the connectedness, volatility transmission and investment scenario between different pairs of commodity futures and assets, observing the impact of Covid-19. To do that, we derived a daily dataset spanning from 2016 to 2021 bifurcated into two panels comprising the pre & post-Covid-19 onset periods. First, we employed wavelet coherence plots to check the directional connectedness between asset and commodity futures. The DCC-GARCH model was then applied on both the data panels to investigate and compare volatility transmission. Hedge ratios and optimum portfolio weights have been estimated to demonstrate a comparative investment scenario. We observe a significant long-term volatility transmission from the asset markets to commodity futures for both the onset panel. Commodity futures provide effective hedging and diversification efficiency against the asset markets. DCC, hedge ratio and optimum portfolio weights show the heterogeneous patterns of investment for pre & post-Covid-19 period. Gold, bond, bullion futures and exchange rates are recognized as a gauge of the economy in crisis. This work will provide significant insight to readers about portfolio construction and required changes in portfolio weights in normal and crisis market conditions.