Domains and Functions of Spike Protein in SARS-Cov-2 in the Context of Vaccine Design
Bibliographic record
Abstract
The spike protein in SARS-CoV-2 (SARS-2-S) interacts with the human ACE2 receptor to gain entry into a cell to initiate infection. Both Pfizer/BioNTech's BNT162b2 and Moderna's mRNA-1273 vaccine candidates are based on stabilized mRNA encoding prefusion SARS-2-S that can be produced after the mRNA is delivered into the human cell and translated. SARS-2-S is cleaved into S1 and S2 subunits, with S1 serving the function of receptor-binding and S2 serving the function of membrane fusion. Here, I dissect in detail the various domains of SARS-2-S and their functions discovered through a variety of different experimental and theoretical approaches to build a foundation for a comprehensive mechanistic understanding of how SARS-2-S works to achieve its function of mediating cell entry and subsequent cell-to-cell transmission. The integration of structure and function of SARS-2-S in this review should enhance our understanding of the dynamic processes involving receptor binding, multiple cleavage events, membrane fusion, viral entry, as well as the emergence of new viral variants. I highlighted the relevance of structural domains and dynamics to vaccine development, and discussed reasons for the spike protein to be frequently featured in the conspiracy theory claiming that SARS-CoV-2 is artificially created.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".