Diversity within the adenovirus fiber knob hypervariable loops influences primary receptor interactions
Bibliographic record
Abstract
ABSTRACT Adenovirus based vectors are of increasing importance for wide ranging therapeutic applications. As vaccines, vectors derived from human adenovirus species D serotypes 26 and 48 (HAdV-D26/48) are demonstrating promising efficacy as protective platforms against infectious diseases. Significant clinical progress has been made, yet definitive studies underpinning mechanisms of entry, infection, and receptor usage are currently lacking. Here, we performed structural and biological analysis of the receptor binding fiber-knob protein of HAdV-D26/48, reporting crystal structures, and modelling putative interactions with two previously suggested attachment receptors, CD46 and Coxsackie and Adenovirus Receptor (CAR). We provide evidence of a low affinity interaction with CAR, with modelling suggesting affinity is attenuated through extended, semi-flexible loop structures, providing steric hindrance. Conversely, in silico and in vitro experiments are unable to provide evidence of interaction between HAdV-D26/48 fiber-knob with CD46, or with Desmoglein 2. Our findings provide new insight to the cell-virus interactions of HAdV-D26/48, with important implications for the design and engineering of optimised Ad-based therapeutics.
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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".