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There are no specific drugs or vaccines for Nipah virus (NiV), which is a new Paramyxovirus that infects swine and humans. This study was conducted to investigate B-cell epitope mapping of the NiV attachment glycoprotein and to construct peptide-based vaccine candidates using the reverse vaccinology approach. To generate the linear B-cell epitope, the NiV isolates were extractad from GenBank, NCBI, using the IEDB web server; peptide modeling was conducted using PEP-FOLD3; docking was conducted using PatchDock and FireDock; and in silico cloning was designed using SnapGene. Various peptides were successfully identified from the NiV attachment glycoprotein based on B-cell epitope prediction, allergenicity prediction, similarity prediction, and toxicity prediction. An in silico cloning design of the pET plasmic was also developed. The peptide "RFENTTSDKGKIPSKVIKSYYGTMDIKKINEGLLD" (1G peptide) is predicted to be a potential candidate for the NiV vaccine as it has several good vaccine characteristics. It increases the immune response of B cells through activation, differentiation into plasma cells, the formation of memory cells, and it may increase IgM/IgG antibody titres for viral neutralization. However, the results of this study should be further verified through in vivo and in vitro analyses. [ABSTRACT FROM AUTHOR]

Ebola virus (EBOV) is a type of RNA virus from the family of Filoviridae. The 2014-2016 Ebola outbreak in African countries Guinea, Liberia, and Sierra Leone has a total of 28,616 cases and 11,310 deaths. Death from Ebola is mainly caused by multi-organ failure due to internal bleeding and fluid loss. Another Ebola outbreak spiked this February 2021, suggesting the low effectiveness of the previous vaccines used. Zaire Ebola virus (EBOV) is known to be the species highly involved in the recent outbreak with a high mortality rate. This study is carried out to design a Bcell epitope Ebola vaccine based on the conserved region of Zaire EBOV glycoprotein. Reverse vaccinology and immunoinformatics approaches are used in this study. Samples of Zaire EBOV glycoprotein sequences were retrieved from GenBank, NCBI. The 3D modeling was done using the SWISSMODEL web server and PyMol software. Phylogenetic tree analysis was also done using MEGA X. B-cell epitope prediction was done by BepiPred 2.0 and Emini Surface Accessibility using the IEDB web server. Epitopes were selected based on their conservancy by comparing the sequences with the MEGA X alignment result. Antigenicity, allergenicity, and toxicity properties of the peptides were predicted using VaxiJen 2.0, AllerTOP 2.0, and ToxinPred web servers. In silico cloning was done as the final step using the pET-24a(+) expression vector. This study revealed that peptides “LEIKKPD,” “TGFGTNETEYLF,” “PYFGPAA,” “PYFGPA,” and “KLSSTNQL” are the best candidate for the B-cell epitope vaccine. Phylogenetic tree and 3D modeling successfully showed the genetic and structural differences of Zaire EBOV GP originating from various countries. In silico cloning was also done using the pET28a(+) expression vector to design a clone vector map for the next vaccine development phase. [ABSTRACT FROM AUTHOR]

Dengue is a major public health threat worldwide, affecting approximately 3 billion people. More than 100 countries in the world located in tropical and subtropical areas, there are at least 100 to 400 million people infected with the dengue virus which causes dengue hemorrhagic fever (DHF). Soluble Non Structural Protein (sNS1) DENV is a soluble NS1 protein that is secreted and found in the serum of patients during acute infection. Because of its presence early in infection, sNS1 is used as a diagnostic indicator of acute dengue infection. NS1 can directly activate platelets through TLR4 and can further increase platelet aggregation, endothelial cell adhesion, and phagocytosis by macrophages that can cause thrombocytopenia so that high sNS1 levels are associated with disease severity. From the results of the study showed p <0.05. This indicates that there is a correlation between the presence of NS1 and the severity of dengue infection. [ABSTRACT FROM AUTHOR]

Algal biomass synthesised nanocomposites have a higher surface area and reusability advantages. This study aimed to synthesise and characterise ZnMgO and silica-supported graphene with ZnMgO (G-ZnMgO) nanocomposites from Kappaphycusalvarezii and evaluate their potential in the application of photocatalysis to remove Rhodamine-B (RhB) and methylene blue (MB) dyes from their aqueous medium by maximising the percentage removal using response surface methodology (RSM) modelling. Nanocomposites were synthesised and characterised by biogenic and instrumental (Powder X-ray diffraction (P-XRD), electron microscopic analysis (SEM and TEM), Fourier transform infrared spectroscopy (FTIR), Energy dispersive analysis of X-rays (EDAX). and UV-visible diffuse reflectance spectroscopy (UV-DRS)) methods, respectively; modelling predicted the optimal conditions to be photocatalyst dosage and contact time of 1 g/L and 90 min, respectively, to obtain maximum MB dye removal of 80% using G-ZnMgO. The results showed the best fit between experimental and RSM predicted values. Thus, the obtained results conclude that the algal biomass synthesised nanocomposites were found to be one of the potential photocatalysts for the removal of RhB and MB dyes from their aqueous solution. [ABSTRACT FROM AUTHOR]