Despite the availability of COVID-19 vaccines, additional more potent vaccines are still required against the emerging variations of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the present investigation, we have identified a promising vaccine candidate against the Omicron (B.1.1.529) using immunoinformatics approaches. Various available tools like, the Immune Epitope Database server resource, and NetCTL-1.2, have been used for the identification of the promising T-cell and B-cell epitopes. The molecular docking was performed to check the interaction of TLR-3 receptors and validated 3D model of vaccine candidate. The codon optimization was done followed by cloning using SnapGene. Finally, In-silico immune simulation profile was also checked. The identified T-cell and B-cell epitopes have been selected based on their antigenicity (VaxiJen v2.0) and, allergenicity (AllerTOP v2.0). The identified epitopes with antigenic and non-allergenic properties were fused with the specific peptide linkers. In addition, the 3D model was constructed by the PHYRE2 server and validated using ProSA-web. The validated 3D model was further docked with the Toll-like receptor 3 (TLR3) and showed good interaction with the amino acids which indicate a promising vaccine candidate against the Omicron variant of SARS-CoV-2. Finally, the codon optimization,
In-silico
cloning and immune simulation profile was found to be satisfactory. Overall, the designed vaccine candidate has a potential against variant of SARS-Cov-2. However, further experimental studies are required to confirm.
Candidal vulvovaginitis involving multispecies of Candida and epithelium-bound biofilm poses a drug-resistant
pharmacotherapeutic
challenge. The present study aims for a disease-specific predominant
causative organism resolution for the development of a tailored vaginal
drug delivery system. The proposed work fabricates a luliconazole-loaded
nanostructured lipid carrier-based transvaginal gel for combating Candida albicans biofilm and disease amelioration. The interaction
and binding affinity of luliconazole against the proteins of C. albicans and biofilm were assessed using in silico tools.
A systematic QbD analysis was followed to prepare the proposed nanogel
using a modified melt emulsification–ultrasonication–gelling
method. The DoE optimization was logically implemented to ascertain
the effect of independent process variables (excipients concentration;
sonication time) on dependent formulation responses (particle size;
polydispersity index; entrapment efficiency). The optimized formulation
was characterized for final product suitability. The surface morphology
and dimensions were spherical and ≤300 nm, respectively. The
flow behavior of an optimized nanogel (semisolid) was non-Newtonian
similar to marketed preparation. The texture pattern of a nanogel
was firm, consistent, and cohesive. The release kinetic model followed
was Higuchi (nanogel) with a % cumulative drug release of 83.97 ±
0.69% in 48 h. The % cumulative drug permeated across a goat vaginal
membrane was found to be 53.148 ± 0.62% in 8 h. The skin-safety
profile was examined using a vaginal irritation model (in vivo) and
histological assessments. The drug and proposed formulation(s) were
checked against the pathogenic strains of C. albicans (vaginal clinical isolates) and in vitro established biofilms. The
visualization of biofilms was done under a fluorescence microscope
revealing mature, inhibited, and eradicated biofilm structures.
The present study aims to design, develop and characterize kNGR (Asn-Gly-Arg) peptide-conjugated lipid–polymer-based nanoparticles for the target-specific delivery of anticancer bioactive(s), i.e., Paclitaxel (PTX). The kNGR-PEG-DSPE conjugate was synthesized and characterized by using spectral analysis. The dual-targeted PLGA–lecithin–PEG core-shell nanoparticles (PLNs-kNGR-NPs) were synthesized using a modified nanoprecipitation process, and their physiological properties were determined. The results support that, compared to other NPs, PLNs-kNGR-NPs are highly cytotoxic, owing to higher apoptosis and intracellular uptake. The significance of rational nanoparticle design for synergistic treatment is shown by the higher tumor volume inhibition percentage rate (59.7%), compared to other designed formulations in Balb/c mice in the HT-1080 tumor-induced model. The overall results indicate that the PLNs-kNGR-NPs-based hybrid lipid–polymer nanoparticles present the highest therapeutic efficacy against solid tumor overexpressing the CD13 receptors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.