Deciphering virus host interaction analysis to unravel core virus network signatures and computational drug...

Cervical cancer (CC) is a major contributor to cancer-related deaths. Human papillomavirus (HPV) genotypes, especially HPV16 and HPV18, are the primary causes of CC-related infections. Although the oncogenic potential of HPV is well established, the molecular mechanisms underlying cancer initiation and persistence remain unclear. In this study, the common proteins between the virus-host interaction network and CC proteome datasets were analyzed to identify proteins involved in HPV-driven oncogenesis. Network topology analysis revealed two key viral proteins, viz. VE7_HPV16 and VE6_HPV18, along with subsequent sequence analysis, identified short linear motifs (SLiMs) in each target that may act as potential hotspots for therapeutic interventions. Different in silico validations, such as active site prediction, protein-protein docking and blind docking analysis, were performed to evaluate the therapeutic potential of the SLiMs-containing regions. In the next step, a structure-based virtual screening approach was employed to identify possible antivirals that bind to the active sites (SLiMs-containing regions) of these proteins. Ten candidate drugs, Pleconaril, Pirodavir, Saquinavir, Delavirdine, and Tipranavir for VE7_HPV16 and Beclabuvir, Velpatasvir, Paritaprevir, Odalasvir, and Ledipasvir for VE6_HPV18, were predicted to exhibit high binding affinities with their respective viral targets. Additionally, Molecular Dynamics (MD) simulations were performed to examine the stability of the protein-ligand complexes and evaluate the role of SLiMs-containing regions in modulating virus-host interactions. Collectively, this comprehensive analysis of the virus-host network identified key HPV protein targets and proposed antiviral drug candidates to impede viral contributions to cervical carcinogenesis.