Computational identification of potential dengue RdRp inhibitors through docking, ADMET, and molecular dynamics

Dengue fever, caused by the dengue virus (DENV), remains a significant global health threat due to the lack of specific antiviral treatments or vaccines. Currently, no approved antivirals target DENV RNA-dependent RNA polymerase (RdRp), a crucial enzyme for viral replication. This study explores the inhibitory potential of antiviral compounds against DENV3 and DENV2 through molecular docking and molecular dynamics simulations. Twenty-four antiviral agents were evaluated using multiple criteria, including Lipinski's Rule of Five (RO5), computational ADME predictions, toxicity profiles, bioactivity scores, and bioavailability radar. Cepharanthine showed the highest binding affinity for DENV3 (-8.21 kcal/mol), while Conessine exhibited the strongest binding with DENV2 (-8.35 kcal/mol). Molecular dynamics simulations (100 ns) revealed that Conessine forms a more stable complex with DENV2, with lower RMSD, RMSF and energy values, highlighting its potential as a DENV2 inhibitor. Most compounds adhered to RO5, Cepharanthine showing some deviations, whereas Conessine fully complied, demonstrating superior drug-likeness. Both compounds showed high gastrointestinal absorption, but Conessine exhibited better bioavailability and a more favourable toxicity profile. Bioactivity scores revealed that Conessine has strong GPCR activity and balanced performance across multiple targets, while Cepharanthine showed limited activity. Overall, Conessine stood out as a potential lead due to its drug-like characteristics, robustness, and lower predicted toxicity. These findings provide new evidence for Conessine as a candidate dengue RdRp inhibitor. However, as this research is based solely on computational analysis, further in vitro and in vivo investigations are required to confirm and advance these results toward clinical application.