The development of anti-cyclic citrullinated peptide (Anti-CCP) antibody following severe COVID-19 (preprint)

The dysregulated immune response is one of the cardinal features of severe coronavirus disease-2019 (COVID-19). This study has been conducted to clarify the occurrence of AABs associated with a systemic autoimmune rheumatic disease (SARD) in hospitalized patients with a moderate, severe, and critical form of COVID-19. The serum samples obtained from one hundred seventy-six hospitalized COVID-19 patients were enrolled in this study, including patients with moderate (N = 90), severe (N = 50), and critical (N = 36) forms of COVID-19. Serum samples collected from healthy subjects before the COVID-19 pandemic were used as control. The ANA, ds-DNA, c-ANCA, p-ANCA, aPL, and anti-CCP occurrence was evaluated using a solid-phase enzyme-linked immunosorbent assay (ELISA). The occurrence of ANA, anti-dsDNA, Anti-CCP, c-ANCA, and p-ANCA was significantly higher in the COVID-19 patients compared to serum obtained from healthy subjects (P = 0.0001, P = 0.0001, P = 0.0001, P = 0.030, and P = 0.001 respectively). The positive number of anti-CCP tests increased significantly in severe COVID-19 compared to the moderate group (P = 0.002). Our study further supports the development of autoantibodies related to systemic autoimmune rheumatologic diseases (SARD). To the best of our knowledge, this is the first study with a large sample size that reported the occurrence of anti-CCP in a severe form of COVID-19.

Immunoinformatic design of a COVID-19 subunit vaccine using entire structural immunogenic epitopes of SARS-CoV-2 (preprint)

Coronavirus disease-19 (COVID-19) is an acute resolved disease, with estimated 3.4% case fatality rate. Due to insufficient data and short onset time of the disease, researchers have to change the strategy against its associated virus, SARS-CoV-2. One of these strategies is the use of computational methods in the field of drug and vaccine design, which can greatly reduce the time and cost of the therapeutic or immunogenic development projects. In this study, we employed various immunoinformatics tools to design a multi-epitope vaccine polypeptide with the highest potential for activating the human immune system against SARS-CoV-2. The initial epitope set was extracted from the whole set of viral structural proteins. Their potential non-toxic and non-allergenic T- cell and B-cell binding and cytokine inducing epitopes were then identified through a priori immunoinformatic prediction. Selected epitopes were bonded to each other with appropriate links. A suitable adjuvant was added to the N-terminus of the vaccine polypeptide sequence to increase its immunogenicity. Molecular modelling of the 3D structure of the vaccine polypeptide, docking, molecular dynamics simulations and free energy calculations confirmed that the designed vaccine had high affinity for Toll-like receptor 3 binding, and that the vaccine-receptor complex was highly stable. Therefore, the designed polypeptide is promising for antigenicity and inducing an effective and safe immune response against SARS-CoV-2 inside the human body.

Immunoinformatic design of a COVID-19 subunit vaccine using entire structural immunogenic epitopes of SARS-CoV-2 (preprint)

One of the strategies against the lack of data and short onset time of the ongoing COVID-19 disease is the use of computational methods in the field of drug and vaccine design. Though demanding experimental validations, these methods can greatly reduce the time and cost of the immunogenic development projects. In this protocol, we describe the use of various immunoinformatics tools to design a multi-epitope vaccine polypeptide with the highest potential for activating the human immune system against SARS-CoV-2. The initial epitope set was extracted from the whole set of viral structural proteins. Their potential non-toxic and non-allergenic T-cell and B-cell binding and cytokine inducing epitopes were then identified through a priori immunoinformatic prediction. Selected epitopes were bonded to each other with appropriate links. A suitable adjuvant was added to the N-terminus of the vaccine polypeptide sequence to increase its immunogenicity. Molecular modelling of the 3D structure of the vaccine polypeptide, docking, molecular dynamics simulations and free energy calculations were used to confirm stability and receptor affinity. Time taken to complete: 43 days.

Immunoinformatic design of a COVID-19 subunit vaccine using entire structural immunogenic epitopes of SARS-CoV-2 (preprint)

Coronavirus disease-19 (COVID-19) is an acute resolved disease, with estimated 3.4% case fatality rate. Due to insufficient data and short onset time of the disease, researchers have to change the strategy against its associated virus, SARS-CoV-2. One of these strategies is the use of computational methods in the field of drug and vaccine design, which can greatly reduce the time and cost of the therapeutic or immunogenic development projects. In this study, we employed various immunoinformatics tools to design a multi-epitope vaccine polypeptide with the highest potential for activating the human immune system against SARS-CoV-2. The initial epitope set was extracted from the whole set of viral structural proteins. Their potential non-toxic and non-allergenic T-cell and B-cell binding and cytokine inducing epitopes were then identified through a priori immunoinformatic prediction. Selected epitopes were bonded to each other with appropriate links. A suitable adjuvant was added to the N-terminus of the vaccine polypeptide sequence to increase its immunogenicity. Molecular modelling of the 3D structure of the vaccine polypeptide, docking, molecular dynamics simulations and free energy calculations confirmed that the designed vaccine had high affinity for Toll-like receptor 3 binding, and that the vaccine-receptor complex was highly stable. Therefore, the designed polypeptide is promising for antigenicity and inducing an effective and safe immune response against SARS-CoV-2 inside the human body.