AlphaFold-driven structure-guided identification of NS5 RdRp-targeting antiviral leads against Kyasanur Forest...

With no approved antiviral treatments currently available, Kyasanur Forest Disease Virus (KFDV) remains a serious and neglected tick-borne flavivirus posing a significant public health concern endemic to India. To address this therapeutic gap, we employed AlphaFold-based structural modelling integrated with structure-based lead identification targeting the RNA-dependent RNA polymerase (RdRp) domain of the viral NS5 protein. The predicted NS5 model exhibited high structural confidence, with pLDDT scores approaching 90 and a pTM score of 0.8, and was further validated using Verify3D, PROCHECK, and ERRAT. Structural architecture analysis revealed a conserved MTase-RdRp organization comprising canonical motifs A-G and essential catalytic aspartate residues, closely resembling RdRp structures from related flaviviruses such as Tick-Borne Encephalitis Virus. A structure-based virtual screening workflow was implemented using Schrödinger Maestro to evaluate 1388 compounds from DrugBank and MedChem libraries. Initial screening using Glide Extra Precision (XP) docking followed by Induced-Fit Docking (IFD) shortlisted high-affinity binders interacting with key catalytic residues. The stability and dynamics of selected complexes were assessed through 200 ns molecular dynamics simulations, along with post-simulation MM/GBSA binding free energy calculations. Among the identified hits, Enoxaparin exhibited low conformational deviations (RMSD ∼2.80 Å; RMSF ∼1.32 Å), enhanced active-site rigidity, and favorable binding free energy (-63.12 kcal/mol), suggesting effective restriction of RdRp flexibility required for viral replication. Although the hit compounds displayed suboptimal drug-like properties, they provide promising scaffolds for further optimization. Overall, this study presents a robust computational framework and candidate leads to support experimental validation and antiviral development against KFDV.