Curcumin coating: a novel solution to mitigate inherent carbon nanotube toxicity.

Multi-walled Carbon Nanotubes (MWCNTs) are inert structures with high aspect ratios that are widely used as vehicles for targeted drug delivery in cancer and many other diseases. They are largely non-toxic in nature however, when cells are exposed to these nanotubes for prolonged durations or at high concentrations, they show certain adverse effects. These include cytotoxicity, inflammation, generation of oxidative stress, and genotoxicity among others. To combat such adverse effects, various moieties can be attached to the surface of these nanotubes. Curcumin is a known anti-inflammatory, antioxidant and cytoprotective compound derived from a medicinal plant called Curcuma longa. In this study, we have synthesized and characterized Curcumin coated-lysine functionalized MWCNTs and further evaluated the cytoprotective, anti-inflammatory, antioxidant and antiapoptotic effect of Curcumin coating on the surface of MWCNTs. The results show a significant decrease in the level of inflammatory molecules like IL-6, IL-8, IL-1ß, TNFα and NFκB in cells exposed to Curcumin-coated MWCNTs as compared to the uncoated ones at both transcript and protein levels. Further, compared to the uncoated samples, there is a reduction in ROS production and upregulation of antioxidant enzyme-Catalase in the cells treated with Curcumin-coated MWCNTs. Curcumin coating also helped in recovery of mitochondrial membrane potential in the cells exposed to MWCNTs. Lastly, cells exposed to Curcumin-coated MWCNTs showed reduced cell death as compared to the ones exposed to uncoated MWCNTs. Our findings suggest that coating of Curcumin on the surface of MWCNTs reduces its ability to cause inflammation, oxidative stress, and cell death.

Plant derived active compounds as potential anti SARS-CoV-2 agents: an in-silico study.

Plants are a valued potential source of drugs for a variety of diseases and are often considered less toxic to humans. We investigated antiviral compounds that may potentially target SARS-CoV-2 antigenic spike (S) and host proteins; angiotensin-converting enzyme2 (ACE2), and transmembrane serine protease2 (TMPRSS2). We scrutinized 36 phytochemicals from 15 Indian medicinal plants known to be effective against RNA viruses via molecular docking. Besides, the TMPRSS2 structure was modeled and validated using the SWISS-MODEL. Docking was performed using Autodock Vina and 4.2 followed by visualization of the docking poses on Pymol version 2.4.0 and Discovery Studio Visualizer. Molecular docking showed that 12 out of 36 active compounds interacted efficiently with S, ACE2, and TMPRSS2 proteins. The ADMET profile generated using the swissADME and pkCSM server revealed that these compounds were possessed druggable properties. The Amber 12 simulation package was used to carry out energy minimizations and molecular dynamics (MD) simulations. The total simulation time for both S protein: WFA and S protein: WND complexes was 300 ns (100 ns per replica). A total of 120 structures were extracted from the last 60 ns of each MD simulation for further analysis. MM-PBSA and MM-GBSA were employed to assess the binding energy of each ligand and the receptor-binding domain of the viral S-protein. The methods suggested that WND and WFA showed thermodynamically favorable binding energies, and the S protein had a higher affinity with WND. Interestingly, Leu455 hotspot residue in the S protein, also predicted to participate in binding with ACE2, was engaged by WND and WFA. HighlightsPlants' natural active compounds may aid in the development of COVID-19 therapeutics.MD simulation study revealed stable binding of withanolide D and withaferin A with spike proteinWithanolide D and withaferin A could be effective against SARS-CoV-2 spike protein.Discovery of druggable agents that have less or lack of binding affinity with ACE2 to avoid the organs associated with comorbidities.According to ADMET selected phytochemicals may be used as druggable compounds.Communicated by Ramaswamy H. Sarma.

QSAR modelling of HIV-1 reverse transcriptase inhibition by benzoxazinones using a combination of P_VSA and pharmacophore feature descriptors.

In pursuit of better anti-HIV drugs, a quantitative structure-activity relationship analysis using a novel set of 2D descriptors was performed on a series of HIV-1 reverse transcriptase inhibitory benzoxazinones. The QSAR models derived from the above mentioned descriptors were found to be statistically significant and exhibited superior predictive power. The results of the study justify the application of the descriptors for exploring the binding mode of the benzoxazinones to the enzyme.