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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

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