Lipid Specific Membrane Interaction of Aptamers and Cytotoxicity

We aim to discover diagnostic tools to detect phosphatidylserine (PS) externalization on apoptotic cell surface using PS binding aptamers, AAAGAC and TAAAGA, and hence to understand chemotherapy drug efficacy when inducing apoptosis into cancer cells. The entropic fragment-based approach designed aptamers have been investigated to inspect three aspects: lipid specificity in aptamers’ membrane binding and bilayer physical properties-induced regulation of binding mechanisms, the apoptosis-induced cancer cell surface binding of aptamers, and the aptamer-induced cytotoxicity. The liposome binding assays show preferred membrane binding of aptamers due to presence of PS in predominantly phosphatidylcholine-contained liposomes. Two membrane stiffness reducing amphiphiles triton X-100 and capsaicin were found to enhance membrane’s aptamer adsorption suggesting that bilayer physical properties influence membrane’s adsorption of drugs. Microscopic images of fluorescence-tagged aptamer treated LoVo cells show strong fluorescence intensity only if apoptosis is induced. Aptamers find enhanced PS molecules to bind with on the surface of apoptotic over nonapoptotic cells. In cytotoxicity experiments, TAAAGA (over poor PS binding aptamer CAGAAAAAAAC) was found cytotoxic towards RBL cells due to perhaps binding with nonapoptotic externalized PS randomly and thus slowly breaching plasma membrane integrity. In these three experimental investigations, we found aptamers to act on membranes at comparable concentrations and specifically with PS binding manner. Earlier, we reported the origins of actions through molecular mechanism studies—aptamers interact with lipids using mainly charge-based interactions. Lipids and aptamers hold distinguishable charge properties, and hence, lipid–aptamer association follows distinguishable energetics due to electrostatic and van der Waals interactions. We discover that our PS binding aptamers, due to lipid-specific interactions, appear as diagnostic tools capable of detecting drug-induced apoptosis in cancer cells

Bioprospecting of Meliaceae family phytomolecules for the treatment of monkeypox virus infection: a QSAR modeling and MD simulation approach

Recent monkeypox virus (MPXV) infections show the risk of MPXV transmission that persists today and the significance of surveillance and quick response methods to stop the virus’s spread. Currently, the monkeypox virus infection is not specifically treated. In this study, QSAR models were designed using known inhibitors of cysteine proteinase from the vaccinia virus, where the Random Forest model and Ridge model had showed the best correlation between predicted and observed EC50. These models were used to screen Maliaceae family phytochemicals against MPXV cysteine proteinase. The compound, IMPHY010637 was detected in top 5 from both the QSAR screening models and showed best docked score (-8.6 kcal/mol) and thus selected for further investigation. Further, the IMPHY010637 showed interaction with the catalytic residue His241 of the protein as reported in earlier studies. The ADMET analysis of the compound showed the acceptable drug-like properties of IMPHY010637. However, these properties could be improved after experimental validation of protein-ligand binding. Both docked complex and poses created in 100 ns MD simulation of the protein-ligand complex showed the presence of multiple hydrogen bonds. RMSD and conformation analysis showed stable binding of IMPHY010637 with the cysteine proteinase of MPXV at its active site. Compared to the known inhibitor, IMPHY010637 showed better binding with the protein as observed by the PCA and MM/GBSA analysis. This study concluded IMPHY010637 as a potential inhibitor for the cysteine proteinase of MPXV using computational methods that could be tested in in-vitro experiments. Communicated by Ramaswamy H. Sarma</p

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 ΔG 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</p

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population