LxxIxE-like Motif in Spike Protein of SARS-CoV-2 that is Known to Recruit the Host PP2A-B56 Phosphatase Mimics Artepillin C, an Immunomodulator, of Brazilian Green Propolis
Bibliographic record
Abstract
ABSTRACT SARS-CoV-2 is highly contagious and can cause acute respiratory distress syndrome (ARDS) and multiple organ failure that are largely attributed to the cytokine storm. The surface coronavirus spike (S) glycoprotein is considered as a key factor in host specificity because it mediates infection by receptor-recognition and membrane fusion. Here, the analysis of SARS-CoV-2 S protein revealed two B56-binding LxxIxE-like motifs in S1 and S2 subunits that could recruit the host protein phosphatase 2A (PP2A). The motif in S1 subunit is absent in SARS-CoV and MERS-CoV. Phosphatases and kinases are major players in the regulation of pro-inflammatory responses during pathogenic infections. Moreover, studies have shown that viruses target PP2A in order to manipulate host’s antiviral responses. Recent researches have indicated that SARS-CoV-2 is involved in sustained host inflammation. Therefore, by controlling acute inflammation, it is possible to eliminate its dangerous effects on the host. Among efforts to fight COVID-19, the interaction between LxxIxE-like motif and the PP2A-B56-binding pocket could be a target for the discovery and/or development of a bioactive ligand inhibitor for therapeutic purposes. Indeed, a small molecule called Artepillin C (ArtC), a main compound in Brazilian honeybee green propolis, mimics the side chains of LxxLxE motif. Importantly, ArtC is known, among other effects, to have anti-inflammatory activity that makes it an excellent candidate for future clinical trials in COVID-19 patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".