Discovery of Potential, Non-Toxic Influenza Virus Inhibitor by Computational Techniques

Repurposing of SARS-CoV-2 compounds against Marburg Virus using MD simulation, mm/GBSA, PCA analysis, and free energy landscape

The significant mortality rate associated with Marburg virus infection made it the greatest hazard among infectious diseases. Drug repurposing using in silico methods has been crucial in identifying potential compounds that could prevent viral replication by targeting the virus's primary proteins. This study aimed at repurposing the drugs of SARS-CoV-2 for identifying potential candidates against the matrix protein VP40 of the Marburg virus. Virtual screening was performed where the control compound, Nilotinib, showed a binding score of -9.99 kcal/mol. Based on binding scores, hit compounds 9549298, 11960895, 44545852, 51039094, and 89670174 were selected that had a lower binding score than the control. Subsequent molecular dynamics (MD) simulation revealed that compound 9549298 consistently formed a hydrogen bond with the residue Gln290. This was observed both in molecular docking and MD simulation poses, indicating a strong and significant interaction with the protein. 11960895 had the most stable and consistent RMSD pattern exhibited in 100 ns simulation, while 9549298 had the most identical RMSD plot compared to the control molecule. MM/PBSA analysis showed that the binding free energy (ΔG) of 9549298 and 11960895 was lower than the control, with -30.84 and -38.86 kcal/mol, respectively. It was observed by the PCA (principal component analysis) and FEL (free energy landscape) analysis that compounds 9549298 and 11960895 had lesser conformational variation. Overall, this study proposed 9549298 and 11960895 as potential binders of VP40 MARV that can cause its inhibition, however it inherently lacks experimental validation. Furthermore, the study proposes in-vitro experiments as the next step to validate these computational findings, offering a practical approach to further explore these compounds' potential as antiviral agents.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.

Random Mutagenesis Analysis of the Influenza A M2 Proton Channel Reveals Novel Resistance Mutants

The influenza M2 proton channel is a major drug target, but unfortunately, the acquisition of resistance mutations greatly reduces the functional life span of a drug in influenza treatment. New M2 inhibitors that inhibit mutant M2 channels otherwise resistant to the early adamantine-based drugs have been reported, but it remains unclear whether and how easy resistance could arise to such inhibitors. We have combined a newly developed proton conduction assay with an established method for selection and screening, both Escherichia coli-based, to enable the study of M2 function and inhibition. Combining this platform with two groups of structurally different M2 inhibitors allowed us to isolate drug resistant M2 channels from a mutant library. Two groups of M2 variants emerged from this analysis. A first group appeared almost unaffected by the inhibitor, M_089 (N13I, I35L, and F47L) and M_272 (G16C and D44H), and the single-substitution variants derived from these (I35L, L43P, D44H, and L46P). Functionally, these resemble the known drug resistant M2 channels V27A, S31N, and swine flu. In addition, a second group of tested M2 variants were all still inhibited by drugs but to a lesser extent than wild type M2. Molecular dynamics simulations aided in distinguishing the two groups where drug binding to the wild type and the less resistant M2 group showed a stable positioning of the ligand in the canonical binding pose, as opposed to the drug resistant group in which the ligand rapidly dissociated from the complex during the simulations.

Virtual screening of the inhibitors targeting at the viral protein 40 of Ebola virus

BACKGROUND

The Ebola virus is highly pathogenic and destructive to humans and other primates. The Ebola virus encodes viral protein 40 (VP40), which is highly expressed and regulates the assembly and release of viral particles in the host cell. Because VP40 plays a prominent role in the life cycle of the Ebola virus, it is considered as a key target for antiviral treatment. However, there is currently no FDA-approved drug for treating Ebola virus infection, resulting in an urgent need to develop effective antiviral inhibitors that display good safety profiles in a short duration.

METHODS

This study aimed to screen the effective lead candidate against Ebola infection. First, the lead molecules were filtered based on the docking score. Second, Lipinski rule of five and the other drug likeliness properties are predicted to assess the safety profile of the lead candidates. Finally, molecular dynamics simulations was performed to validate the lead compound.

RESULTS

Our results revealed that emodin-8-beta-D-glucoside from the Traditional Chinese Medicine Database (TCMD) represents an active lead candidate that targets the Ebola virus by inhibiting the activity of VP40, and displays good pharmacokinetic properties.

CONCLUSION

This report will considerably assist in the development of the competitive and robust antiviral agents against Ebola infection.