A multi-method and structure-based in silico vaccine designing against Echinococcus granulosus through investigating enolase protein

Introduction: Hydatid disease is a ubiquitous parasitic zoonotic disease, which causes different medical, economic and serious public health problems in some parts of the world. The causal organism is a multi-stage parasite named Echinococcus granulosus whose life cycle is dependent on two types of mammalian hosts viz definitive and intermediate hosts. Methods: In this study, enolase, as a key functional enzyme in the metabolism of E. granulosus (EgEnolase), was targeted through a comprehensive in silico modeling analysis and designing a host-specific multi-epitope vaccine. Three-dimensional (3D) structure of enolase was modeled using MODELLER v9.18 software. The B-cell epitopes (BEs) were predicted based on the multi-method approach and via some authentic online predictors. ClusPro v2.0 server was used for docking-based T-helper epitope prediction. The 3D structure of the vaccine was modeled using the RaptorX server. The designed vaccine was evaluated for its immunogenicity, physicochemical properties, and allergenicity. The codon optimization of the vaccine sequence was performed based on the codon usage table of E. coli K12. Finally, the energy minimization and molecular docking were implemented for simulating the vaccine binding affinity to the TLR-2 and TLR-4 and the complex stability. Results: The designed multi-epitope vaccine was found to induce anti-EgEnolase immunity which may have the potential to prevent the survival and proliferation of E. granulosus into the definitive host. Conclusion: Based on the results, this step-by-step immunoinformatics approach could be considered as a rational platform for designing vaccines against such multi-stage parasites. Furthermore, it is proposed that this multi-epitope vaccine is served as a promising preventive anti-echinococcosis agent

A novel B- and helper T-cell epitopes-based prophylactic vaccine against Echinococcus granulosus

Introduction: In this study, we targeted the worm stage of Echinococcus granulosus to design a novel multi-epitope B- and helper T-cell based vaccine construct for immunization of dogs against this multi-host parasite. Methods: The vaccine was designed based on the local Eg14-3-3 antigen (Ag). DNA samples were extracted from the protoscoleces of the infected sheep’s liver, and then subjected to the polymerase chain reaction (PCR) with 14-3-3 specific forward and reverse primers. For the vaccine designing, several in silico steps were undertaken. Three-dimensional (3D) structure of the local Eg14-3-3 Ag was modeled by EasyModeller software. The protein modeling accuracy was then analyzed via various validation assays. Potential transmembrane helix, signal peptide, post-translational modifications and allergenicity of Eg14-3-3 were evaluated as the preliminary measures of B-cell epitopes (BEs) prediction. Having used many web-servers, a well-designed process was carried out for improved prediction of BEs. High ranked linear and conformational BEs were utilized for engineering the final vaccine construct. Possible T-helper epitopes (TEs) were identified by the molecular docking between 13-mer fragments of the Eg14-3-3 Ag and two high frequent dog class II MHC alleles (i.e., DLA-DRB1*01101 and DRB1*01501). The epitopes coverage was evaluated by Shannon’s variability plot. Results: The final designed construct was analyzed based on different physicochemical properties, which was then codon optimized for high-level expression in Escherichia coli k12. This minigene construct is the first dog-specific epitopic vaccine construct that is established based on TEs with high-binding affinity to canine MHC alleles. Conclusion: This in silico study is the first part of a multi-antigenic vaccine designing work that represents as a novel dog-specific vaccine against E. granulosus. Here, we present key data on the step-by-step methodologies used for designing this de novo vaccine, which is under comprehensive in vivo investigations

A multi-method and structure-based in silico vaccine designing against Echinococcus granulosus through investigating enolase protein

Introduction: Hydatid disease is a ubiquitous parasitic zoonotic disease, which causes different medical, economic and serious public health problems in some parts of the world. The causal organism is a multi-stage parasite named Echinococcus granulosus whose life cycle is dependent on two types of mammalian hosts viz definitive and intermediate hosts. Methods: In this study, enolase, as a key functional enzyme in the metabolism of E. granulosus (EgEnolase), was targeted through a comprehensive in silico modeling analysis and designing a host-specific multi-epitope vaccine. Three-dimensional (3D) structure of enolase was modeled using MODELLER v9.18 software. The B-cell epitopes (BEs) were predicted based on the multi-method approach and via some authentic online predictors. ClusPro v2.0 server was used for docking-based T-helper epitope prediction. The 3D structure of the vaccine was modeled using the RaptorX server. The designed vaccine was evaluated for its immunogenicity, physicochemical properties, and allergenicity. The codon optimization of the vaccine sequence was performed based on the codon usage table of E. coli K12. Finally, the energy minimization and molecular docking were implemented for simulating the vaccine binding affinity to the TLR-2 and TLR-4 and the complex stability. Results: The designed multi-epitope vaccine was found to induce anti-EgEnolase immunity which may have the potential to prevent the survival and proliferation of E. granulosus into the definitive host. Conclusion: Based on the results, this step-by-step immunoinformatics approach could be considered as a rational platform for designing vaccines against such multi-stage parasites. Furthermore, it is proposed that this multi-epitope vaccine is served as a promising preventive anti-echinococcosis agent.</jats:p

Prophylactic domain-based vaccine against SARS-CoV-2, causative agent of COVID-19 pandemic

Abstract Coronavirus disease 2019 (COVID-19) is undoubtedly the most challenging pandemic in the current century with more than 253,381 deaths worldwide since its emergence in late 2019 (updated May 6th, 2020). COVID-19 is caused by a novel emerged coronavirus named as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Today, the world needs crucially to develop a prophylactic vaccine scheme for such emerged and emerging infectious pathogens. In this study, we have targeted spike (S) glycoprotein, as an important surface antigen of SARS-CoV-2, to identify its immunodominant B- and T-cell epitopes. We have conducted a multi-method B-cell epitope (BCE) prediction approach using different predictor algorithms to discover most potential BCEs. Besides, we sought among a pool of MHC class I and II-associated peptide binders provided by the IEDB server through the strict cut-off values. To design a broad-coverage vaccine, we carried out a population coverage analysis for a set of candidate T-cell epitopes and based on the HLA allele frequency in the top most-affected countries by COVID-19 (update 02 April 2020). The final determined B- and T-cell epitopes were mapped on the S glycoprotein sequence, and three potential hub regions covering the largest number of overlapping epitopes were identified for the vaccine designing (I531–N711; T717–C877; and V883–E973). Here, we have designed two domain-based constructs to be produced and delivered through the recombinant protein- and gene-based approaches, including (i) an adjuvanted domain-based protein vaccine construct (DPVC), and (ii) a self-amplifying mRNA vaccine (SAMV) construct. The safety, stability, and immunogenicity of the DPVC were validated using the integrated sequential (i.e. allergenicity, autoimmunity, and physicochemical features) and structural (i.e. molecular docking between the vaccine and human Toll-like receptors (TLRs) 4 and 5) analysis. The stability of the docked complexes was evaluated using the molecular dynamics (MD) simulations. These rigorous in silico validations supported the potential of the DPVC and SAMV to promote both innate and specific immune responses in the animal studies.</jats:p