Assessing the inhibitory potential of anti-dengue compounds against Japanese encephalitis virus RNA dependent RNA polymerase: an in silico study

Structural and energetic analysis of NS5 protein inhibition by small molecules in Japanese encephalitis virus using machine learning and steered molecular dynamics approach

One of the viral diseases that affect millions of people around the world, particularly in developing countries, is Japanese encephalitis (JE). In this study, the conserved protein of this virus, that is, non-structural protein 5 (NS5), was used as a target protein for this study, and a compound library of 749 antiviral molecules was screened against NS5. The current study employed machine learning-based virtual screening combined with molecular docking. Here, three hits (24360, 123519051 and 213039) had lower binding energies (< -8 kcal/mol) than the control, S-Adenosyl-L-homocysteine (SAH). All the compounds showed significant H-bond interactions with functional residues, which were also observed by the control. Molecular dynamics simulation, MM/GBSA for binding free energy analysis, principal component analysis and free energy landscape were also performed to study the stability of the complex formation. All three compounds had similar root mean square deviation trends, which were comparable to the control, SAH. Post-MD, the 123519051-receptor complex had the highest number of H-bonds (4 to 5) after the control, out of which three exhibited the highest percentage occupancy (50%, 24% and 79%). Both docking and MD, 123519051 showed an H-bond with the residue Gly111, which was also found for the control-protein complex. 123519051 showed the lowest binding free energy with ΔGbind of -89 kJ/mol. Steered molecular dynamics depicted that 123519051 had the maximum magnitude of dissociation (1436.43 kJ/mol/nm), which was more than the control, validating its stable complex formation. This study concluded that 123519051 is a binder and could inhibit the protein NS5 of JE.Communicated by Ramaswamy H. Sarma.

Application of temperature-dependent and steered molecular dynamics simulation to screen anti-dengue compounds against Marburg virus

Marburg virus infections are extremely fatal with a fatality range of 23% to 90%, therefore there is an urgent requirement to design and develop efficient therapeutic molecules. Here, a comprehensive temperature-dependent molecular dynamics (MD) simulation method was implemented to identify the potential molecule from the anti-dengue compound library that can inhibit the function of the VP24 protein of Marburg. Virtual high throughput screening identified five effective binders of VP24 after screening 484 anti-dengue compounds. These compounds were treated in MD simulation at four different temperatures: 300, 340, 380, and 420 K. Higher temperatures showed dissociation of hit compounds from the protein. Further, triplicates of 100 ns MD simulation were conducted which showed that compounds ID = 118717693, and ID = 5361 showed strong stability with the protein molecule. These compounds were further validated using Δ G binding free energies and they showed: -30.38 kcal/mol, and -67.83 kcal/mol binding free energies, respectively. Later, these two compounds were used in steered MD simulation to detect its dissociation. Compound ID = 5361 showed the maximum pulling force of 199.02 kcal/mol/nm to dissociate the protein-ligand complex while ID = 118717693 had a pulling force of 101.11 kcal/mol/nm, respectively. This ligand highest number of hydrogen bonds with varying occupancies at 89.93%, 69.80%, 57.93%, 52.33%, and 50.63%. This study showed that ID = 5361 can bind with the VP24 strongly and has the potential to inhibit its function which can be validated in the in-vitro experiment.Communicated by Ramaswamy H. Sarma.

Structural and Dynamical Basis of VP35-RBD Inhibition by Marine Fungi Compounds to Combat Marburg Virus Infection

The Marburg virus (MBV), a deadly pathogen, poses a serious threat to world health due to the lack of effective treatments, calling for an immediate search for targeted and efficient treatments. In this study, we focused on compounds originating from marine fungi in order to identify possible inhibitory compounds against the Marburg virus (MBV) VP35-RNA binding domain (VP35-RBD) using a computational approach. We started with a virtual screening procedure using the Lipinski filter as a guide. Based on their docking scores, 42 potential candidates were found. Four of these compounds-CMNPD17596, CMNPD22144, CMNPD25994, and CMNPD17598-as well as myricetin, the control compound, were chosen for re-docking analysis. Re-docking revealed that these particular compounds had a higher affinity for MBV VP35-RBD in comparison to the control. Analyzing the chemical interactions revealed unique binding properties for every compound, identified by a range of Pi-cation interactions and hydrogen bond types. We were able to learn more about the dynamic behaviors and stability of the protein-ligand complexes through a 200-nanosecond molecular dynamics simulation, as demonstrated by the compounds' consistent RMSD and RMSF values. The multidimensional nature of the data was clarified by the application of principal component analysis, which suggested stable conformations in the complexes with little modification. Further insight into the energy profiles and stability states of these complexes was also obtained by an examination of the free energy landscape. Our findings underscore the effectiveness of computational strategies in identifying and analyzing potential inhibitors for MBV VP35-RBD, offering promising paths for further experimental investigations and possible therapeutic development against the MBV.