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DOI 10.1016/j.meegid.2021.104985

Медицинская библиотека · Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2021

In silico analysis and prediction of immunogenic epitopes for pre-erythrocytic proteins of the deadly Plasmodium falciparum.

Asghari Ali, Nourmohammadi Hassan, Majidiani Hamidreza, Shariatzadeh Seyyed Ali, Shams Morteza, Montazeri Fattaneh

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Аннотация

Malaria is the deadliest parasitic disease in tropical and subtropical areas around the world, with considerable morbidity and mortality, particularly due to the life-threatening Plasmodium falciparum. The present in silico investigation was performed to reveal the biophysical characteristics and immunogenic epitopes of the six pre-erythrocytic proteins of the P. falciparum using comprehensive immunoinformatics approaches. For this aim, different web servers were employed to predict subcellular localization, antigenicity, allergenicity, solubility, physico-chemical properties, post-translational modification sites (PTMs), the presence of signal peptide and transmembrane domains. Moreover, the secondary and tertiary structures of the proteins were revealed followed by refinement and validations. Finally, NetCTL server was used to predict cytotoxic T-lymphocyte (CTL) epitopes, followed by subsequent screening in terms of antigenicity and immunogenicity. Also, IEDB server was utilized to predict helper T-lymphocyte (HTL) epitopes, followed by screening regarding interferon gamma induction and population coverage. These proteins showed appropriate antigenicity, abundant PTMs as well as many CTL and HTL epitopes, which could be directed for future vaccination studies in the context of multi-epitope vaccine design.

Для цитирования: Asghari Ali, Nourmohammadi Hassan, Majidiani Hamidreza, Shariatzadeh Seyyed Ali, Shams Morteza, Montazeri Fattaneh. In silico analysis and prediction of immunogenic epitopes for pre-erythrocytic proteins of the deadly Plasmodium falciparum.. Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases. 2021. DOI: 10.1016/j.meegid.2021.104985.

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