Targeting ofAdenovirus via Genetic Modification of the Viral Capsid Combined with aProteinBridge
Bibliographic record
Abstract
A potential barrier to the development of genetically targeted adenovirus (Ad) vectors for cell-specific delivery of gene therapeutics lies in the fact that several types of targeting protein ligands require posttranslational modifications, such as the formation of disulfide bonds, which are not available to Ad capsid proteins due to their nuclear localization during assembly of the virion. To overcome this problem, we developed a new targeting strategy, which combines genetic modifications of the Ad capsid with a protein bridge approach, resulting in a vector-ligand targeting complex. The components of the complex associate by virtue of genetic modifications to both the Ad capsid and the targeting ligand. One component of this mechanism of association, the Fc-binding domain of Staphylococcus aureus protein A, is genetically incorporated into the Ad fiber protein. The ligand is comprised of a targeting component fused with the Fc domain of immunoglobulin, which serves as a docking moiety to bind to these genetically modified fibers during the formation of the Ad-ligand complex. The modular design of the ligand solves the problem of structural and biosynthetic compatibility with the Ad and thus facilitates targeting of the vector to a variety of cellular receptors. Our study shows that targeting ligands incorporating the Fc domain and either an anti-CD40 single-chain antibody or CD40L form stable complexes with protein A-modified Ad vectors, resulting in significant augmentation of gene delivery to CD40-positive target cells. Since this gene transfer is independent of the expression of the native Ad5 receptor by the target cells, this strategy results in the derivation of truly targeted Ad vectors suitable for tissue-specific gene therapy.
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) | 0.000 | 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) | 0.000 | 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".