Bioimpacts. 2019;9(3): 131-144.
doi: 10.15171/bi.2019.18
PMID: 31508329
PMCID: PMC6726745
Scopus ID: 85071191509
WOSID: 000483926500003
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Original Research

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

Mohammad Mostafa Pourseif 1,2, Mitra Yousefpour 1 * , Mohammad Aminianfar 2, Gholamali Moghaddam 3, Ahmad Nematollahi 4 ORCID logo

1 Department of Physiology, Faculty of Medicine, AJA University of Medical Sciences, Tehran, Iran
2 Infectious Diseases and Tropical Medicine Research Center (IDTMRC), Department of Aerospace and Subaquatic Medicine, AJA University of Medical Sciences, Tehran, Iran
3 Department of Animal Sciences, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
4 Department of Pathobiology, Veterinary College, University of Tabriz, Tabriz, Iran


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.
Keywords: Echinococcus granulosus, Enolase, In silico vaccinology, Molecular docking, Epitope
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Submitted: 29 Oct 2018
Revision: 27 Nov 2018
Accepted: 04 Dec 2018
ePublished: 08 Mar 2019
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