DrugBank database is mined to hunt prospective Ebola virus (EBOV) VP35 inhibitors utilizing docking calculations, molecular dynamics, molecular mechanics/generalized Born surface area binding energy calculations, and density functional theory computations. The results suggest that DB14875 and DB07800 can serve as effective inhibitors of VP35, indicating their potency to be developed into anti-EBOV medications.

Ebola virus (EBOV), one of the deadliest diseases, is responsible for infecting individuals with hemorrhagic fever syndrome, which remains an ongoing worldwide health concern. The extremely deadly nature and virulence of EBOV illness illuminate the imperative need to evolve effective curative agents. Viral protien (VP35) acts as an Achilles heel for EBOV reproduction and also interacts with numerous human proteins, which leads to impairing the immune system. Herein, the DrugBank database, containing >14000 investigational and approved drugs, is mined to hunt prospective inhibitors toward VP35 utilizing various computational approaches. Docking technique performance is initially validated to predict the VP35-inhibitor binding pose upon the accessible experimental data. Molecular dynamics simulations (MDS) are then conducted in triplicate on the top potent drug candidates, followed by binding energy (ΔG _binding) estimations using molecular mechanics/generalized Born surface area (MM/GBSA) approach. Upon MM/GBSA//250 ns MDS, DB14875 and DB07800 revealed better binding energy against VP35 than 1D9, reference inhibitor, with ΔG _binding values of −36.6, −35.6, and −29.3 kcal mol⁻¹, respectively. Post-MD analyses demonstrate great stability for the identified drug candidates complexed with VP35 over 250 ns MDS. Ultimately, the density functional theory computations are executed, and their outcomes elucidate favorable molecular reactivity of the identified drug candidates. Conclusively, these findings suggest promising inhibitors for VP35, warranting further experimental assays.