Targeted Delivery of Antigen Processing Inhibitors to Antigen Presenting Cells <i>via</i> Mannose Receptors
Bibliographic record
Abstract
Improved chemical inhibitors are required to dissect the role of specific antigen processing enzymes and to complement genetic models. In this study we explore the in vitro and in vivo properties of a novel class of targeted inhibitor of aspartic proteinases, in which pepstatin is coupled to mannosylated albumin (MPC6), creating an inhibitor with improved solubility and the potential for selective cell tropism. Using these compounds, we have demonstrated that MPC6 is taken up via mannose receptor facilitated endocytosis, leading to a slow but continuous accumulation of inhibitor within large endocytic vesicles within dendritic cells and a parallel inhibition of intracellular aspartic proteinase activity. Inhibition of intracellular proteinase activity is associated with reduction in antigen processing activity, but this is epitope-specific, preferentially inhibiting processing of T cell epitopes buried within compact proteinase-resistant protein domains. Unexpectedly, we have also demonstrated, using quenched fluorescent substrates, that little or no cleavage of the disulfide linker takes place within dendritic cells. This does not appear to affect the activity of MPC6 as an inhibitor of cathepsins D and E in vitro and in vivo. Finally, we have shown that MPC6 selectively targets dendritic cells and macrophages in spleen in vivo. Preliminary results suggest that access to nonlymphoid tissues is very limited in the steady state but is strongly enhanced at local sites of inflammation. The strategy adopted for MPC6 synthesis may therefore represent a more general way to deliver chemical inhibitors to cells of the innate immune system, especially at sites of inflammation.
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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) | 0.000 | 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 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".