Unstructural biology of the dengue virus proteins
Bibliographic record
Abstract
In this study, we used a wide spectrum of bioinformatics techniques to evaluate the extent of intrinsic disorder in the complete proteomes of genotypes of four human dengue virus (DENV), to analyze the peculiarities of disorder distribution within individual DENV proteins, and to establish potential roles for the structural disorder with respect to their functions. We show that several proteins (ER, E, 1, 2A and 4A) are predicted to be mostly ordered, whereas four proteins (C, 2k, NS3 and NS5) are expected to have high disorder levels. The profiles of disorder propensities are similar across the four genotypes, except for the NS5 protein. Cleavage sites are depleted in polymorphic sites, and have a high propensity for disorder, especially relative to neighboring residues. Disordered regions are highly polymorphic in type 1 DENV but have a relatively low number of polymorphic sites in the type 4 virus. There is a high density of polymorphisms in proteins 2A and 4A, which are depleted in disorder. Thus, a high density of polymorphism is not unique to disordered regions. Analysis of disorder/function association showed that the predominant function of the disordered regions in the DENV proteins is protein-protein interaction and binding of nucleic acids, metals and other small molecules. These regions are also associated with phosphorylation, which may regulate their function.
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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 | 0.001 | 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".