COVID-19 and autoantibodies
Autoantibodies are antibodies produced by autoreactive B cells that can penetrate a wide variety of threats [104]. Autoantibodies can be produced against DNA, RNA, lipids, proteins, centromeres, chromatin and ribosomal properties [104, 105]. Loss of B cell tolerance, defective apoptosis, loss of regulatory cells and cells may cause offspring of autoantibodies [104]. Autoantibodies can be seen in IgM and IgG isotypes [104,105]. The place of autoantibodies is indispensable to recognizing and treating autoimmune clearance [106]. In organ-specific autoimmune diseases, autoantibodies are present against those with organ antigens, whereas, in systemic autoimmune diseases, no autoantibodies are present against antigens found in most tissues [104]. In autoimmune thyroiditis and Graves’ disease, which are organ-specific autoimmune diseases, autoantibodies can develop against the thyroid antigens thyroglobulin, thyroperoxidase, and thyroid stimulating hormone stores [104,107]. In myesthenia gravis, another neuro-autoimmune disease, autoantibodies against the acetylcholine receptor can be formed by B cells [107]. 107 In systemic autoimmune diseases, it consists of autoantibodies against common antigens found in most tissues [108]. For example, in systemic lupus erythematosus, anti-nuclear antibodies against nuclear material consist of anti-dsDNA against DNA and anti-histone autoantibodies against histone proteins [109]. However, auto-antibodies detected in some departments controls may not spread with autoimmune diseases [110]. Viral infections can also cause autoimmune diseases in various ways [111]. Viral infections can cause autoimmune disease by mimicry, bystander activation, by adjuvant rearrangements, and by epitope spreading [112].
Autoantibodies were detected in the COVID-19 and post-COVID-19 patients [103]. It has been shown that patients with positive autoantibodies have a more severe course of COVID-19 than other cases [113]. As a result of the study of Pascolini et al. on 33 COVID-19 patients, antinuclear antibodies, anti-cytoplasmic neutrophil antibodies (ANCA), and anti-antiphospholipid antibodies (APL) showed that these autoantibodies develop due to COVID-19 [114]. Severe and critical COVID-19 patients have a higher frequency of APL autoantibody and the presence of APL antibody positivity is associated with extremely high-level ferritin, CRP, IL-6, and pulmonary thromboembolism [115]. This explains the hypercoagulable state in severe and critical COVID-19 cases and indicates that SARS-CoV-2 can induce autoimmune responses [114,116]. COVID-19 patients have a higher risk of lupus anticoagulant positivity [117]. Lupus anticoagulant-positive patients have a higher risk of thrombosis [118]. Several case reports demonstrated autoantibodies against RBC antigens which they can contribute to hemolytic anemia and are related to the severity of anemia in COVID-19 [119,120]. Some COVID-19 patients have neurologic symptoms. These patient’s case reports have been shown to develop autoantibodies against contactin-associated protein 2 (anti-Caspr2), ganglioside GD1b (anti-GD1b), and myelin oligodendrocyte glycoprotein (anti-MOG) [121,122]. COVID-19 patients can develop the hematologic system autoimmunity [123].

Material-Method

Data Collection

Structural proteins of SARS-CoV-2 (Spike, Nucleocapsid, Membrane, Envelope) were obtained from the NCBI database. The structural proteins aminoacid sequences of SARS-CoV-2 were fragmented into 8 amino acid-long peptide fragments.

Peptide Matching

The peptide-match server is an online tool to reveal the amino acid sequence similarity between amino acid sequences and desired organism [124]. Fragmented eight amino acid length peptides uploaded peptide-match server. This server predicts similarity between 8mers and human sequences [124].

Antigenicity prediction

In order to generate immune responses based on molecular mimicry, the 8mers that we constructed from SARS-CoV-2 structural proteins must be antigenic [125]. Predicted similar epitopes assessed for antigenicity in Vaxijen v2.0 antigenicity prediction server [125].

Prediction of binding affinity of peptides to TAP

The compatibility of 8mers with the TAP protein must be met for them to be presented as epitopes. Similar epitopes were analyzed for TAP affinity. For the analysis, we use the TAPreg tool [126].

Allergenicity prediction

To elicit an autoimmune response through molecular mimicry, 8mers must not possess allergenicity as this would result in the activation of an IgE-mediated response.The predicted similar epitopes were analyzed for allergenicity. For analyses of allergenicity, we use the AllerTOP v2.0 tool [127].

Toxicity prediction

Similar epitopes were analyzed for toxicity, the toxicity prediction we use the ToxinPred tool [128].

IL-10, and IFN-gamma inducing prediction

Similar epitopes were analyzed for IL-10, and IFN-gamma induction. The prediction of IL-10 [129] inducing predicted in IL-10pred, and prediction of IFN-gamma inducing predicted in IFNepitope[130] server.

HLA docking calculation

Matched best peptide (identical, antigenic, non-allergenic, non-toxic, IL-4 inducer, and IFN-gamma inducer, non-IL-10 inducer, and high affinity to TAP) docked to Class-I and Class-II MHC molecules. Class-I HLA docking simulated in CABS-dock server [131]. Structures of HLA-I molecules were retrieved from the RCSB-PDB server (4NQV, 4UQ3, 3RL2, 1X7Q, 5HGA, 5EO1, 3SPV, 1OGT, 3LKN, 1E27, 5INC). The docked models were analyzed for ΔG (kcal mol-1) and Kd (M) at 37.0 °C values. For this analysis, the PRODIGY server was used [132,133]. The Epidock server was used for DEDDSEPV peptide docking to the MHC-II receptor.

Results

Peptide Matching

Fragmented peptides imported to the peptide match server. We found six identical amino acid sequences (VNSVLLFL, VFLLVTLA, KKDKKKKA, SRSSSRSR, RRARSVAS, DEDDSEPV) to the human proteome. Table-1 shows the UniProt codes and protein names of similar proteins with identical amino acid sequences.
Table-1
List of the identified 8mers of SARS-CoV-2 that have mimicry with human proteome.