Bibliographic record
Abstract
Coronaviruses are enveloped RNA viruses that cause respiratory diseases in humans and other animals. The continued circulation of human coronaviruses and the large reservoir of non-human coronaviruses that have the potential to infect humans represent a significant health concern. Similar to other RNA viruses, coronaviruses are characterized by a high mutation rate, and evolution and adaptation has accompanied the diversification of coronaviruses. The coronavirus spike protein is a viral membrane protein involved in host receptor binding and fusion of the viral and host cell membranes. Reported here is work performed on the spike proteins of two human common cold causing coronaviruses: HCoV-229E and HCoV-OC43. Specifically, the X-ray crystal structures of the following were determined: i) the receptor binding domain (RBD) of the S-protein of HCoV-229E in complex with human aminopeptidase N (hAPN) and ii) the carbohydrate binding domain (CBD) of the S-protein of HCoV-OC43 in complex with 9-O-Acetyl-N-acetylneuraminic acid (Neu5,9Ac2). In addition, viral sequence analysis, binding studies, and comparative sequence and structural analysis among closely related coronaviruses were performed. The observation that the greatest variability shown by natural viral isolates of HCoV-229E is located in the receptor binding loops is quite surprising from a receptor binding standpoint. However, this observation suggests that the receptor binding region is changing due to viral selection. Indeed, our results indicate that the optimization of receptor binding affinity and/or immune evasion, two known determinants of viral fitness, are operative in the emergence of new viral isolates. Although less well characterized at this point, natural viral sequence variation at or near the carbohydrate binding site of HCoV-OC43 is also observed, an indication that similar selection pressures are operative. Together, our results provide mechanistic insights into coronavirus adaptation and evolution.
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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) | 0.001 | 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".