Candidate antigenic epitopes for vaccination and diagnosis strategies of Toxoplasma gondii infection: A review

Mamaghani, Amirreza Javadi; Fathollahi, Anwar; Spotin, Adel; Ranjbar, Malek Mohammad; Barati, Meisam; Aghamolaie, Somayeh; Karimi, Maryam; Taghipour, Niloofar; Ashrafi, Mohammad; Tabaei, Seyyed Javad Seyyed

doi:10.1016/j.micpath.2019.103788

Cited by 16 publications

(9 citation statements)

References 56 publications

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“…The application of bioinformatics methods is very helpful in predicting protein structure, their functions, biological features, specific immune response, avidity of antigen-antibody binding in vaccine design, and serologic diagnosis (Ebrahimi et al 2019;Mamaghani et al 2019;Habibi et al 2020;Karimi et al 2020). The epitope prediction servers based on the artificial intelligence have higher accuracy and sensitivity than those that perform epitope prediction based on physicochemical properties.…”

Section: Discussionmentioning

confidence: 99%

In-silico design of a multi-epitope for developing sero-diagnosis detection of SARS-CoV-2 using spike glycoprotein and nucleocapsid antigens

Mamaghani

Arab-Mazar

Heidarzadeh

et al. 2021

Netw Model Anal Health Inform Bioinforma

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COVID-19 is a pandemic disease caused by novel corona virus, SARS-CoV-2, initially originated from China. In response to this serious life-threatening disease, designing and developing more accurate and sensitive tests are crucial. The aim of this study is designing a multi-epitope of spike and nucleocapsid antigens of COVID-19 virus by bioinformatics methods. The sequences of nucleotides obtained from the NCBI Nucleotide Database. Transmembrane structures of proteins were predicted by TMHMM Server and the prediction of signal peptide of proteins was performed by Signal P Server. B-cell epitopes' prediction was performed by the online prediction server of IEDB server. Beta turn structure of linear epitopes was also performed using the IEDB server. Conformational epitope prediction was performed using the CBTOPE and eventually, eight antigenic epitopes with high physicochemical properties were selected, and then, all eight epitopes were blasted using the NCBI website. The analyses revealed that α-helices, extended strands, β-turns, and random coils were 28.59%, 23.25%, 3.38%, and 44.78% for S protein, 21.24%, 16.71%, 6.92%, and 55.13% for N Protein, respectively. The S and N protein three-dimensional structure was predicted using the prediction I-TASSER server. In the current study, bioinformatics tools were used to design a multi-epitope peptide based on the type of antigen and its physiochemical properties and SVM method (Machine Learning) to design multi-epitopes that have a high avidity against SARS-CoV-2 antibodies to detect infections by COVID-19.

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Section: Discussionmentioning

confidence: 99%

In-silico design of a multi-epitope for developing sero-diagnosis detection of SARS-CoV-2 using spike glycoprotein and nucleocapsid antigens

Mamaghani

Arab-Mazar

Heidarzadeh

et al. 2021

Netw Model Anal Health Inform Bioinforma

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“…There are several successful examples of the application of immunoinformatics in the identification/development of new diagnostic targets as described with COVID-19 [ 185 , 186 , 187 ], Schistosoma mansoni [ 188 ], Toxoplasma gondii [ 189 ] Fasciola hepatica [ 190 ], helminth [ 191 ] human brucellosis [ 192 ] and Leishmania [ 193 ]. In the context of systemic mycosis, the number of works is substantially limited, and this approach has been used combined with immunoproteomic analyses as described to Paracoccidioides complex [ 43 , 172 ], Sporothrix schenckii complex [ 159 ] and Cryptococcus gattii [ 158 ].…”

Section: Approaches Used To Search For New Diagnostic Candidatesmentioning

confidence: 99%

Challenges in Serologic Diagnostics of Neglected Human Systemic Mycoses: An Overview on Characterization of New Targets

et al. 2022

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Systemic mycoses have been viewed as neglected diseases and they are responsible for deaths and disabilities around the world. Rapid, low-cost, simple, highly-specific and sensitive diagnostic tests are critical components of patient care, disease control and active surveillance. However, the diagnosis of fungal infections represents a great challenge because of the decline in the expertise needed for identifying fungi, and a reduced number of instruments and assays specific to fungal identification. Unfortunately, time of diagnosis is one of the most important risk factors for mortality rates from many of the systemic mycoses. In addition, phenotypic and biochemical identification methods are often time-consuming, which has created an increasing demand for new methods of fungal identification. In this review, we discuss the current context of the diagnosis of the main systemic mycoses and propose alternative approaches for the identification of new targets for fungal pathogens, which can help in the development of new diagnostic tests.

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“…A detailed description of Eukpaths is included in Supplementary Table S1. In addition, we also obtained 371 experimentally determined peptide sequences for host CD8 + T cells that are described in the latest Review articles, in which have gave a detailed list regarding peptide sequences in three important parasites [i.e., Plasmodium falciparum (Heide et al, 2019), Toxoplasma gondii (Javadi Mamaghani et al, 2019), and Trypanosoma cruzi (Ferragut et al, 2021)] and, eventually, a total of 1,180 TCEs were reorganized as the positive dataset.…”

Section: Dataset Preparationmentioning

confidence: 99%

CD8TCEI-EukPath: A Novel Predictor to Rapidly Identify CD8+ T-Cell Epitopes of Eukaryotic Pathogens Using a Hybrid Feature Selection Approach

Wu²,

Zhang³

et al. 2022

Front. Genet.

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Computational prediction to screen potential vaccine candidates has been proven to be a reliable way to provide guarantees for vaccine discovery in infectious diseases. As an important class of organisms causing infectious diseases, pathogenic eukaryotes (such as parasitic protozoans) have evolved the ability to colonize a wide range of hosts, including humans and animals; meanwhile, protective vaccines are urgently needed. Inspired by the immunological idea that pathogen-derived epitopes are able to mediate the CD8+ T-cell-related host adaptive immune response and with the available positive and negative CD8+ T-cell epitopes (TCEs), we proposed a novel predictor called CD8TCEI-EukPath to detect CD8+ TCEs of eukaryotic pathogens. Our method integrated multiple amino acid sequence-based hybrid features, employed a well-established feature selection technique, and eventually built an efficient machine learning classifier to differentiate CD8+ TCEs from non-CD8+ TCEs. Based on the feature selection results, 520 optimal hybrid features were used for modeling by utilizing the LightGBM algorithm. CD8TCEI-EukPath achieved impressive performance, with an accuracy of 79.255% in ten-fold cross-validation and an accuracy of 78.169% in the independent test. Collectively, CD8TCEI-EukPath will contribute to rapidly screening epitope-based vaccine candidates, particularly from large peptide-coding datasets. To conduct the prediction of CD8+ TCEs conveniently, an online web server is freely accessible (http://lab.malab.cn/∼hrs/CD8TCEI-EukPath/).

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Candidate antigenic epitopes for vaccination and diagnosis strategies of Toxoplasma gondii infection: A review

Cited by 16 publications

References 56 publications

In-silico design of a multi-epitope for developing sero-diagnosis detection of SARS-CoV-2 using spike glycoprotein and nucleocapsid antigens

In-silico design of a multi-epitope for developing sero-diagnosis detection of SARS-CoV-2 using spike glycoprotein and nucleocapsid antigens

Challenges in Serologic Diagnostics of Neglected Human Systemic Mycoses: An Overview on Characterization of New Targets

CD8TCEI-EukPath: A Novel Predictor to Rapidly Identify CD8+ T-Cell Epitopes of Eukaryotic Pathogens Using a Hybrid Feature Selection Approach

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