Inter-proteomic posttranslational modifications of the SARS-CoV-2 and the host proteins ‒ A new frontier
Bibliographic record
Abstract
Posttranslational modification of proteins, which include both the enzymatic alterations of protein side chains and main-chain peptide bond connectivity, is a fundamental regulatory process that is crucial for almost every aspects of cell biology, including the virus-host cell interaction and the SARS-CoV-2 infection. The posttranslational modification of proteins has primarily been studied in cells and tissues in an intra-proteomic context (where both substrates and enzymes are part of the same species). However, the inter-proteomic posttranslational modifications of most of the SARS-CoV-2 proteins by the host enzymes and vice versa are largely unexplored in virus pathogenesis and in the host immune response. It is now known that the structural spike (S) protein of the SARS-CoV-2 undergoes proteolytic priming by the host serine proteases for entry into the host cells, and N- and O-glycosylation by the host cell enzymes during virion packaging, which enable the virus to spread. New evidence suggests that both SARS-CoV-2 and the host proteins undergo inter-proteomic posttranslational modifications, which play roles in virus pathogenesis and infection-induced immune response by hijacking the host cell signaling. The purpose of this minireview is to bring attention of the scientific community to recent cutting-edge discoveries in this understudied area. It is likely that a better insight into the molecular mechanisms involved may open new research directions, and thereby contribute to novel therapeutic modality development against the SARS-CoV-2. Here we briefly discuss the rationale and touch upon some unanswered questions in this context, especially those that require attention from the scientific community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".