Abstract
Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic diseases. Nipah virus (NiV) of Paramyxoviridae family and Henipavirus genus is transmitted by Pteropus bats. Climate-induced changes in bat migration patterns and food availability enhances the virus's adaptability, in turn increasing the potential for transmission and outbreak risk. NiV infection has high human fatality rate. With no antiviral drugs or vaccines available, exploring the complex machinery involved in viral RNA synthesis presents a promising target for therapy. Drug repurposing provides a fast-track approach by identifying existing drugs with potential to target NiV RNA-dependent RNA polymerase (L), bypassing the time-consuming process of developing novel compounds. To facilitate this, we developed an attention-based deep learning model that utilizes pharmacophore properties of the active sites and their binding efficacy with NiV L protein. Around 500 FDA-approved drugs were filtered and assessed for their ability to bind NiV L protein. Compared to the control Remdesivir, we identified Cangrelor, an antiplatelet drug for cardiovascular diseases, with stronger binding affinity to NiV L (glide score of -12.30 kcal/mol). Molecular dynamics simulations further revealed stable binding (RMSD of 3.54 Å) and a post-MD binding energy of -181.84 kcal/mol. The strong binding of Cangrelor is illustrated through trajectory analysis, principal component analysis, and solvent accessible surface area, further confirming the stable interaction with the active site of NiV RdRp. Cangrelor can interact with NiV L protein and may potentially interfere with its replication. These findings suggest that Cangrelor will be a potential drug candidate that can effectively interact with the NiV L protein and potentially disrupt the viral replication. Further in vivo studies are warranted to explore its potential as a repurposable antiviral drug.