Jamestown Canyon virus (JCV) is a deadly viral infection transmitted by various mosquito species. This mosquito-borne virus belongs to Bunyaviridae family, posing a high public health threat in the in tropical regions of the United States causing encephalitis in humans. Common symptoms of JCV include fever, headache, stiff neck, photophobia, nausea, vomiting, and seizures. Despite the availability of resources, there is currently no vaccine or drug available to combat JCV. The purpose of this study was to develop an epitope-based vaccine using immunoinformatics approaches. The vaccine aimed to be secure, efficient, bio-compatible, and capable of stimulating both innate and adaptive immune responses. In this study, the protein sequence of JCV was obtained from the NCBI database. Various bioinformatics methods, including toxicity evaluation, antigenicity testing, conservancy analysis, and allergenicity assessment were utilized to identify the most promising epitopes. Suitable linkers and adjuvant sequences were used in the design of vaccine construct. 50s ribosomal protein sequence was used as an adjuvant at the N-terminus of the construct. A total of 5 CTL, 5 HTL, and 5 linear B cell epitopes were selected based on non-allergenicity, immunological potential, and antigenicity scores to design a highly immunogenic multi-peptide vaccine construct. Strong interactions between the proposed vaccine and human immune receptors, i.e., TLR-2 and TLR-4, were revealed in a docking study using ClusPro software, suggesting their possible relevance in the immunological response to the vaccine. Immunological and physicochemical properties assessment ensured that the proposed vaccine demonstrated high immunogenicity, solubility and thermostability. Molecular dynamics simulations confirmed the strong binding affinities, as well as dynamic and structural stability of the proposed vaccine. Immune simulation suggest that the vaccine has the potential to effectively stimulate cellular and humoral immune responses to combat JCV infection. Experimental and clinical assays are required to validate the results of this study.
This research work seeks to evaluate the impact of selected enzyme complexes on the optimised release of phenolics from leaves of Pongamia pinnata. After preliminary solvent extraction, the P. pinnata leaf extract was subjected to enzymatic treatment, using enzyme cocktails such as kemzyme dry-plus, natuzyme, and zympex-014. It was noticed that zympex-014 had a greater extract yield (28.0%) than kemzyme dry-plus (17.0%) and natuzyme (18.0%). Based on the better outcomes, zympex-014-based extract values were subsequently applied to several RSM parameters. The selected model is suggested to be significant by the F value (12.50) and R2 value (0.9669). The applicability of the ANN model was shown by how closely the projected values from the ANN were to the experimental values. In terms of total phenolic contents (18.61 mg GAE/g), total flavonoid contents (12.56 mg CE/g), and DPPH test (IC50) (6.5 g/mL), antioxidant activities also shown significant findings. SEM analysis also revealed that the cell walls were damaged during enzymatic hydrolysis, as opposed to non-hydrolysed material. Using GC-MS, five potent phenolic compounds were identified in P. pinnata extract. According to the findings of this study, the recovery of phenolic bioactives and subsequent increase in the antioxidant capacity of P. pinnata leaf extract were both positively impacted by the optimisation approaches suggested, including the use of zympex-014.