Intrinsic Structural Disorder in Adenovirus E1A: a Viral Molecular Hub Linking Multiple Diverse Processes
Bibliographic record
Abstract
Viruses are obligate intracellular parasites. Their genomes are not large enough to encode all the functions required to independently produce progeny; hence, viruses are absolutely dependent on host cell functions. Mechanistically, these host cell processes in eukaryotes are founded on an exquisitely complex series of molecular interactions. In particular, the execution of complex biological processes requires the precise interaction and regulation of thousands of proteins. The definition of cellular interactomes by systematic analysis of protein-protein interactions has revealed complex molecular networks (39, 82, 111, 122). Most cellular proteins interact with only one or two other proteins, making only one or two connections. However, the minority of proteins interact with tens, or even hundreds, of other proteins to form network hubs. Hub proteins play key roles in regulating and orchestrating the activity of the proteins they interact with, effectively creating functional modules within the cellular interactome (35, 48, 62). The central role served by cellular hub proteins in regulating cell functions makes them ideal targets during a viral infection. By targeting a single cellular hub, a viral regulatory protein can effectively gain control over an entire module, potentially comprised of hundreds of proteins. By targeting multiple cellular hubs, a virally encoded hub can transform the architecture of the cellular protein interaction network, reprogramming virtually all aspects of cell function and behavior. The viral oncogenes of the small DNA tumor viruses encode some of the most versatile and potent viral hub proteins. Among these, adenovirus E1A is one of the best characterized and is the subject of this review.
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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".