Immunoinformatics for Novel Multi-Epitope Vaccine Development in Canine Parvovirus Infections.

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.

Immunogenic multi-epitope-based vaccine development to combat cyclosporiasis of immunocompromised patients applying computational biology method.

Cyclospora cayetanensis infections, also known as cyclosporiasis, persist to be the prevalent emerging protozoan parasite and an opportunist that causes digestive illness in immunocompromised individuals. In contrast, this causal agent can affect people of all ages, with children and foreigners being the most susceptible populations. For most immunocompetent patients, the disease is self-limiting; in extreme circumstances, this illness can manifest as severe or persistent diarrhea as well as colonize on secondary digestive organs leading to death. According to recent reports, worldwide 3.55% of people are infected by this pathogen, with Asia and Africa being more prevalent. For the treatment, trimethoprim-sulfamethoxazole is the only licensed drug and does not appear to work as well in some patient populations. Therefore, the much more effective strategy to avoid this illness is immunization through the vaccine. This present study uses immunoinformatics for identifying a computational multi-epitope-based peptide vaccine candidate for Cyclospora cayetanensis. Following the review of the literature, a highly efficient, secure, and vaccine complex based on multi-epitopes was designed by utilizing the identified proteins. These selected proteins were then used to predict non-toxic and antigenic HTL-epitopes, B-cell-epitopes, and CTL-epitopes. Ultimately, both a few linkers and an adjuvant were combined to create a vaccine candidate with superior immunological epitopes. Then, to establish the vaccine-TLR complex binding constancy, the TLR receptor and vaccine candidates were placed into the FireDock, PatchDock, and ClusPro servers for molecular docking and iMODS server for molecular-dynamic simulation. Finally, this selected vaccine construct was cloned into Escherichia coli strain-K12; thus, the constructed vaccines against Cyclospora cayetanensiscould improve the host immune response and can be produced experimentally.

Insight into the first multi-epitope-based peptide subunit vaccine against avian influenza A virus (H5N6): An immunoinformatics approach.

The rampant spread of highly pathogenic avian influenza A (H5N6) virus has drawn additional concerns along with ongoing Covid-19 pandemic. Due to its migration-related diffusion, the situation is deteriorating. Without an existing effective therapy and vaccines, it will be baffling to take control measures. In this regard, we propose a revers vaccinology approach for prediction and design of a multi-epitope peptide based vaccine. The induction of humoral and cell-mediated immunity seems to be the paramount concern for a peptide vaccine candidate; thus, antigenic B and T cell epitopes were screened from the surface, membrane and envelope proteins of the avian influenza A (H5N6) virus, and passed through several immunological filters to determine the best possible one. Following that, the selected antigenic with immunogenic epitopes and adjuvant were linked to finalize the multi-epitope-based peptide vaccine by appropriate linkers. For the prediction of an effective binding, molecular docking was carried out between the vaccine and immunological receptors (TLR8). Strong binding affinity and good docking scores clarified the stringency of the vaccines. Furthermore, molecular dynamics simulation was performed within the highest binding affinity complex to observe the stability, and minimize the designed vaccine's high mobility region to order to increase its stability. Then, Codon optimization and other physicochemical properties were performed to reveal that the vaccine would be suitable for a higher expression at cloning level and satisfactory thermostability condition. In conclusion, predicting the overall in silico assessment, we anticipated that our designed vaccine would be a plausible prevention against avian influenza A (H5N6) virus.

Global prevalence of zoonotic pathogens from pigeon birds: A systematic review and meta-analysis.

Pigeons have been considered the most preferred companion for human civilizations since prehistoric times. Despite the fact that pigeons offer the most palatable and nutritious food and provide pleasure to humans, they can pose a health risk because of carrying infectious and zoonotic organisms. Moreover, the scanty of systematic reports on the occurrence of zoonotic pathogens in pigeon makes the situations worst. Hence, the current study conducted a systematic review and meta-analysis to evaluate the global prevalence of zoonotic pathogens among the pigeon population from existing segregated literatures. Four internationally recognized databases including Google Scholar, Scopus, PubMed, and Science Direct were used to search the published studies from January 2000 to October 2021. Analyzing the total 18,589 samples, mean prevalence estimates of pigeon pathogens worldwide were found to be 17% (95% CI:13-21) whereas serological and molecular prevalence were reported as 18% (95% CI:12-23) and 17% (95% CI:10-23). Meanwhile, virus, bacteria, and protozoal pathogens were found to be 21% (10-32%), 17% (12-23%), and 14% (10-19%), respectively. Moreover, continent wise analysis of all zoonotic pigeon pathogens has revealed the highest prevalence rate in Asia 20% (95% CI: 14-26%), followed by Europe 16% (95% CI: 08-24%), Africa 16% (95% CI: 07-24%), and America (North and South) 10% (95% CI: 03-17%). Furthermore, the highest number of studies were reported from Iran showed the prevalence rate of 20%, China 13%, Bangladesh 37%, and Poland 15%. Therefore, this prevalence of data would be helpful to the policymakers to develop appropriate intervention strategies to prevent and control diseases in their respective locations.

Seawater fungi-derived compound screening to identify novel small molecules against dengue virus NS5 methyltransferase and NS2B/NS3 protease.

Dengue fever is a virus spread by mosquitoes that has no effective treatment or vaccination. Several dengue cases combined with the current COVID-19 pandemic, exacerbates this problem. Two proteins, NS5 methyltransferase and NS2B/NS3 primary protease complexes, are crucial for dengue viral replication and are the target sites for antiviral development. Thus, this study screened published literature and identified 162 marine fungus-derived compounds with active bioavailability. Following Lipinski's rules and antiviral property prediction, 41 compounds were selected for docking with NS5 methyltransferase and NS2B/NS3 protease (PDB ID: 6IZZ and 2FOM) to evaluate compounds that could stop the action of dengue viral protein complexes. To find the best candidates, computational ADME, toxicity, and drug target prediction were performed to estimate the potential of the multi-targeting fungal-derived natural compounds. Analyzing the result from 41 compounds, Chevalone E (-13.5 kcal/mol), Sterolic acid (-10.3 kcal/mol) showed higher binding energy against dengue NS2B/NS3 protease; meanwhile, Chevalone E (-12.0 kcal/mol), Brevione K (-7.4 kcal/mol), had greater binding affinity against NS5 methyltransferase. Consequently, this study suggests that Chevalone E is an effective inhibitor of NS5 methyltransferase and NS2B/NS3 protease. Ligand-based virtual screening from DrugBank was utilized to predict biologically active small compounds against dengue virus NS2B/NS3 major protease and NS5 methyltransferase. Both licensed medications, estramustine (DB01196) and quinestrol (DB04575), were found to be similar to Chevalone E, with prediction scores of 0.818 and 0.856, respectively. In addition, cholic acid (DB02659), acitretin (DB00459), and mupirocin (DB00410) are similar to Sterolic acid, zidovudine (DB00495), imipenem (DB01598), and nadolol (DB01203) are similar to Brocazine A, and budesonide (DB01222) and colchicine (DB01394) are related to Brevione K. These findings suggest that these could be feasible dengue virus treatment options, meaning that more research is needed.

Inhibitory Potentiality of Secondary Metabolites Extracted from Marine Fungus Target on Avian Influenza Virus-A Subtype H5N8 (Neuraminidase) and H5N1 (Nucleoprotein): A Rational Virtual Screening.

Highly contagious avian influenza virus' (AIV) subtypes, including H5N1 and H5N8 are considered as serious threats for poultry industry. Despite its severity, treatment and mitigation attempts are fall into baffling. Though a few approved anti-influenza medications are available, the M2 channel blockers amantadine and rimantadine, as well as the neuraminidase inhibitor oseltamivir are being less effective due to widespread drug resistance. To cope up with these circumstances, scientists have found nucleoprotein as a novice drug targeting site for H5N1. Hence, the current study used a rational screening method to find the best candidates for nucleoprotein inhibitors of H5N1 subtype and neuraminidase inhibitors for H5N8 subtype against pathogenic AIV. Finding the best candidates, molecular docking method and computational pharmacokinetics and pharmacology was developed to estimate the potential of the multi-targeting fungal-derived natural compounds for the development of drug. Chevalone E compound was found as the best inhibitor for both nucleoprotein and neuraminidase of H5N1 and H5N8 subtypes respectively, whereas, Brevione F and Brocazine-A for nucleoprotein with Penilactone-A and Aspergifuranone for neuraminidase. In case of drug prediction, the study recommends Estramustine and Iloprost against both nucleoprotein and neuraminidase. Besides these, Butorphanol, Desvenlafaxine, Zidovudine and Nadolol are the best drug candidates for nucleoprotein inhibitors, meanwhile, Sitaxentan, Ergoloid mesylate, Capecitabine and Fenoterol act as speculated candidates against neuraminidase.

A systematic review and meta-analysis on prevalence and epidemiological risk factors of zoonotic Fascioliasis infection among the ruminants in Bangladesh.

The parasitic Fascioliasis is a zoonotic and economically significant disease for livestock and humans, creating public health concerns around the world, including in Bangladesh. Populations of Bangladesh are more vulnerable to this parasitic infestation for their intimate interactions. To tackles the adverse effects on humans from food animals, it is exigency to know the exact prevalence and associated risk factors of zoonotic Fascioliasis among ruminants. Therefore, the aim of this systematic review and meta-analysis was to determine the authentic knowledge of potential risk factors and prevalence among livestock populations. Four globally recognized databases, including Web of Science, Scopus, PubMed, and Google Scholar, along with local databases, were used to search the related studies since 2000. A total of 38 studies were selected for the meta-analysis, and the pooled prevalence of Fascioliasis was found at 20% (95 % CI: 15-25). A subgroup analysis was also performed for: species, age, sex, study duration, and sample size. The prevalence rate was found highest in cattle and sheep at 21% (95 % CI: 15-27), female individuals at 26% (95 % CI: 16-35), aged animals at 26% (95 % CI: 15-36), and rainy season at 25% (95 % CI: 16-34). This is the first systematic review and meta-analysis in Bangladesh that offers a comprehensive picture of the prevalence of Fascioliasis in ruminants and possible risk factors. Thus, this study will assist the government, policymakers, and veterinarians in implementing effective control measures by providing more detailed information about outbreak patterns.

Multi-epitope based subunit vaccine construction against Banna virus targeting on two outer proteins (VP4 and VP9): A computational approach.

Recently, RNA viruses have gained a mammoth concern for causing various outbreaks, and due to pandemics, they are acquiring additional attention throughout the world. An emerging RNA as well as vector-borne Banna Virus (BAV) is a human pathogen resulting in encephalitis, fever, headache, muscle aches, and severe coma. Besides human, pathogenic BAV was also detected from pigs, cattle, ticks, midges, and mosquitoes in Indonesia, China, and Vietnam. Due to high mutation tendency and dearth of a species barrier, this virus will consider as a significant threat in the near future throughout the planet, particularly in Africa. Despite of severe human case fatalities in several countries, there are no specific therapeutics, available vaccines, and other preventive measures against BAV. Thus, to find out the effective therapeutics and preventive strategies are crying exigency. In the present study, a unique multi-epitope-based peptide vaccine candidate is constructed using bioinformatics' tools that efficiently instigate immune cells for generating BAV antibodies. The potential vaccine candidates were developed using both T and B -cell epitopes. UniprotKB database was used to retrieve of two outer proteins (VP9 and VP4), and homologous sequences of BAV taxid: 7763, 649,604, 77,763, and 8453 were searched by NCBI BLAST. These serotypes are the most closely associated with the disease. Then combining the best-selected epitopes in various combinations with different adjuvants, three distinct vaccine candidates were formed. The validity tests were performed for the screened vaccine candidate regarding stability, allergenicity, and antigenicity parameters. Moreover, molecular dynamic simulations of the selected vaccine with TLR-8 immune receptor confirmed the stability of the binding pose and showed a significant response to immune cells. Thus, the results established that the designed chimeric peptide vaccine could enhance the immune response against BAV.