Molecular insight into the role of polyethylene glycol and cholesterol on the performance of graphene-based nanomaterials in Blood-brain barrier delivery

Nanoinformatics based insights into the interaction of blood plasma proteins with carbon based nanomaterials: Implications for biomedical applications

In the past three decades, interest in using carbon-based nanomaterials (CBNs) in biomedical application has witnessed remarkable growth. Despite the rapid advancement, the translation of laboratory experimentation to clinical applications of nanomaterials is one of the major challenges. This might be attributed to poor understanding of bio-nano interface. Arguably, the most significant barrier is the complexity that arises by interplay of several factors like properties of nanomaterial (shape, size, surface chemistry), its interaction with suspending media (surface hydration and dehydration, surface reconstruction and release of free surface energy) and the interaction with biomolecules (conformational change in biomolecules, interaction with membrane and receptor). Tailoring a nanomaterial that minimally interacts with protein and lipids in the medium while effectively acts on target site in biological milieu has been very difficult. Computational methods and artificial intelligence techniques have displayed potential in effectively addressing this problem. Through predictive modelling and deep learning, computer-based methods have demonstrated the capability to create accurate models of interactions between nanoparticles and cell membranes, as well as the uptake of nanomaterials by cells. Computer-based simulations techniques enable these computational models to forecast how making particular alterations to a material's physical and chemical properties could enhance functional aspects, such as the retention of drugs, the process of cellular uptake and biocompatibility. We review the most recent progress regarding the bio-nano interface studies between the plasma proteins and CBNs with a special focus on computational simulations based on molecular dynamics and density functional theory.

Analysis of medicinal and therapeutic potential of Withania somnifera derivatives against COVID-19

Apart from chemical and allopathic drugs, several medicinal plants contain phytochemicals that are potentially useful to counter the COVID-19 pandemic. Withania somnifera (Ashwagandha), which has a good effect on some viral infections, can be considered as a candidate against the virus. In the present study, thirty-nine natural compounds of Ashwagandha were investigated in terms of their binding to the important drug targets to treat the COVID-19. Although the molecular docking calculations reveal the binding affinities of the compounds to Mpro, TMPRSS2, NSP15, PLpro, Spike RBD + ACE2, RdRp and NSP12 as targets in controlling the coronavirus enzymes, Withanoside II is expected to be the most effective compound due to the high affinity in binding with many of considered targets. Furthermore, the Withanoside III, IV, V, X, and XI have favorable binding affinities as ligands with respect to the MM/GBSA calculations. The molecular dynamics simulations MD explore a stable hydrogen bond network between ligands and the active sites residues. Also, the dynamic fluctuations of the binding site residues verify their tight binding to ligands. Moreover, the stability of ligand-protein complexes is approved by the RMSD ranges lower than 0.5 Å in equilibration zone for all mentioned complexes. The TMPRSS2-Withanolide Q and Mpro-Withanoside IV complexes are the most stable pairs using the MM/GBSA calculations and MD simulation.