EpiCurator: an immunoinformatic workflow to predict and prioritize SARS-CoV-2 epitopes

Abstract

The ongoing coronavirus 2019 (COVID-19) pandemic, triggered by the emerging SARS-CoV-2 virus, represents a global public health challenge. Therefore, the development of effective vaccines is an urgent need to prevent and control virus spread. One of the vaccine production strategies uses the in silico epitope prediction from the virus genome by immunoinformatic approaches, which assist in selecting candidate epitopes for in vitro and clinical trials research. This study introduces the EpiCurator workflow to predict and prioritize epitopes from SARS-CoV-2 genomes by combining a series of computational filtering tools. To validate the workflow effectiveness, SARS-CoV-2 genomes retrieved from the GISAID database were analyzed. We identified 11 epitopes in the receptor-binding domain (RBD) of Spike glycoprotein, an important antigenic determinant, not previously described in the literature or published on the Immune Epitope Database (IEDB). Interestingly, these epitopes have a combination of important properties: recognized in sequences of the current variants of concern, present high antigenicity, conservancy, and broad population coverage. The RBD epitopes were the source for a multi-epitope design to in silico validation of their immunogenic potential. The multi-epitope overall quality was computationally validated, endorsing its efficiency to trigger an effective immune response since it has stability, high antigenicity and strong interactions with Toll-Like Receptors (TLR). Taken together, the findings in the current study demonstrated the efficacy of the workflow for epitopes discovery, providing target candidates for immunogen development.

Peptide microarray analysis of in-silico predicted B-cell epitopes in SARS-CoV-2 sero-positive healthcare workers in Bulawayo, Zimbabwe

“…The study population consisted of forty-nine health care workers [14.3% ( Ludolf et al, 2022 May 1 ) males and 85.7% ( Ceraolo and Giorgi, 2020 May 1 ) females] within the age range of 20-64 years (median age: 38.9; IQR: 29-23) from Bulawayo. The cohort of health workers were of two different health settings [87.8% ( Carmona et al, 2012 Dec 14 ) hospital and 12.2% ( West and Kobokovich, 2020 ) clinic] and comprised of 53.1% ( Jena et al, 2021 Jan 23 ) nurses, 2% ( Ferreira et al, 2021 Nov 30 ) doctor, 16.3% ( Javadi Mamaghani et al, 2021 Dec 1 ) nurse aides, 16.3% ( Javadi Mamaghani et al, 2021 Dec 1 ) student nurses, 8.2% ( Ong et al, 2021 Jul 1 ) general and 4.1% ( Musicò et al, 2021 Jan 11 ) clerks. Four workers who did not have demographic data were also included in the study.…”

“…Diagnostic methods are crucial for the control of the ongoing coronavirus diseases of 2019 (COVID-19) pandemic, triggered by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ( Ferreira et al, 2021 Nov 30 , Musicò et al, 2021 Jan 11 ). Though real-time reverse-transcriptase polymerase chain reaction (RT-PCR) is the most established method in detecting active or current SARS-CoV-2 infections ( Rai et al, 2021 Jan 1 ) serological tests (or equivalently, serology, or antibody testing) are useful in resource-limited settings ( Ong et al, 2021 Jul 1 , Lagatie et al, 2017 Dec 1 ).…”

VOE: automated analysis of variant epitopes of SARS-CoV-2 for the development of diagnostic tests or vaccines for COVID-19

“…Immunoinformatics has been used predict peptide-MHC complexes, and comparative molecular docking analyses have led to the identification of potential peptides for peptide vaccine development ( Waqas et al, 2020 ). The predicted epitopes RVQPTES, APGQTGK, DSKVGGNYN, and LKPFERD ( Ferreira et al, 2021 ) were highly antigenic for the development of an epitope-based peptide. The predicted epitopes KLNDLCFTNV and ITLCFTLKRK ( Can et al, 2020 ) were ideal antigens for the development of an epitope-based peptide, and GGDGKMKD ( Can et al, 2020 ) was ideal for a serodiagnostic assay.…”