ABSTRACT
Canine parvovirus (CPV-2) is one of the most important pathogens of dogs of all ages, causing pandemic infections that are characterized by fatal hemorrhagic enteritis. The CPV-2 vaccine is recommended as a core vaccine for pet animals. Despite the intensive practice of active immunization, CPV-2 remains a global threat. In this study, a multi-epitope vaccine against CPV-2 was designed, targeting the highly conserved capsid protein (VP2) via in silico approaches. Several immunoinformatics methods, such as epitope screening, molecular docking, and simulation were used to design a potential vaccine construct. The partial protein sequences of the VP2 gene of CPV-2 and protein sequences retrieved from the NCBI were screened to predict highly antigenic proteins through antigenicity, trans-membrane-topology screening, an allergenicity assessment, and a toxicity analysis. Homologous VP2 protein sequences typically linked to the disease were identified using NCBI BLAST, in which four conserved regions were preferred. Overall, 10 epitopes, DPIGGKTGI, KEFDTDLKP, GTDPDDVQ, GGTNFGYIG, GTFYFDCKP, NRALGLPP, SGTPTN, LGLPPFLNSL, IGGKTG, and VPPVYPN, were selected from the conserved regions to design the vaccine construct. The molecular docking demonstrated the higher binding affinity of these epitopes with dog leukocyte antigen (DLA) molecules. The selected epitopes were linked with Salmonella enterica flagellin FliC adjuvants, along with the PADRE sequence, by GGS linkers to construct a vaccine candidate with 272 nucleotides. The codon adaptation and in silico cloning showed that the generated vaccine can be expressed by the E. coli strain, K12, and the sequence of the vaccine construct showed no similarities with dog protein. Our results suggest that the vaccine construct might be useful in preventing canine parvoviral enteritis (CPE) in dogs. Further in vitro and in vivo experiments are needed for the validation of the vaccine candidate.
ABSTRACT
Candida auris is a serious health concern of the current world that possesses a serious global health threat and is emerging at a high rate. Available antifungal drugs are failing to combat this pathogen as they are growing resistant to those drugs and some strains have already shown resistance to all three available antifungal drugs in the market. Hence, finding alternative therapies is essential for saving lives from this enemy. To make the development of new treatments easier, we conducted some in silico study of this pathogen to discover possible targets for drug design and also recommended some possible metabolites to test in vivo circumstances. The complete proteome of the representative strain was retrieved, and the duplicate, non-essential, human homologous, non-metabolic, and druggable proteins were then eliminated. As a result, out of a total of 5441 C. auris proteins, we were able to isolate three proteins (XP 028890156.1, XP 028891672.1, and XP 028891858.1) that are crucial for the pathogen's survival as well as host-non-homolog, metabolic, and unrelated proteins to the human microbiome. Their subcellular locations and interactions with a large number of proteins (10 proteins) further point to them being good candidates for therapeutic targets. Following in silico docking of 29 putative antifungals of plant origin against the three proteins we chose, Caledonixanthone E, Viniferin, Glaucine, and Jatrorrhizine were discovered to be the most effective means of inhibiting those proteins since they displayed higher binding affinities (ranging from -28.97 kcal/mol to -51.99 kcal/mol) than the control fluconazole (which ranged between -28.84 kcal/mol and -41.15 kcal/mol). According to the results of MD simulations and MM-PBSA calculations, Viniferin and Caledonixanthone E are the most effective ligands for the proteins XP 028890156.1, XP 028891672.1, and XP 028891858.1. Furthermore, they were predicted to be safe and also showed proper ADME properties.
ABSTRACT
The present study aimed to predict a novel chimeric vaccine by simultaneously targeting four major structural proteins via the establishment of ancestral relationship among different strains of coronaviruses. Conserved regions from the homologous protein sets of spike glycoprotein, membrane protein, envelope protein and nucleocapsid protein were identified through multiple sequence alignment. The phylogeny analyses of whole genome stated that four proteins reflected the close ancestral relation of SARS-CoV-2 to SARS-COV-1 and bat coronavirus. Numerous immunogenic epitopes (both T cell and B cell) were generated from the common fragments which were further ranked on the basis of antigenicity, transmembrane topology, conservancy level, toxicity and allergenicity pattern and population coverage analysis. Top putative epitopes were combined with appropriate adjuvants and linkers to construct a novel multiepitope subunit vaccine against COVID-19. The designed constructs were characterized based on physicochemical properties, allergenicity, antigenicity and solubility which revealed the superiority of construct V3 in terms safety and efficacy. Essential molecular dynamics and normal mode analysis confirmed minimal deformability of the refined model at molecular level. In addition, disulfide engineering was investigated to accelerate the stability of the protein. Molecular docking study ensured high binding affinity between construct V3 and HLA cells, as well as with different host receptors. Microbial expression and translational efficacy of the constructs were checked using pET28a(+) vector of E. coli strain K12. However, the in vivo and in vitro validation of suggested vaccine molecule might be ensured with wet lab trials using model animals for the implementation of the presented data.
