Virus-Derived Peptides for Hepatic Enzyme Delivery
Bibliographic record
Abstract
Recently, a lipopeptide derived from the hepatitis B virus (HBV) large surface protein has been developed as an HBV entry inhibitor. This lipopeptide, called MyrcludexB (MyrB), selectively binds to the sodium taurocholate cotransporting polypeptide (NTCP) on the basolateral membrane of hepatocytes. Here, the feasibility of coupling therapeutic enzymes to MyrB was investigated for the development of enzyme delivery strategies. Hepatotropic targeting shall enable enzyme prodrug therapies and detoxification procedures. Here, horseradish peroxidase (HRP) was conjugated to MyrB via maleimide chemistry, and coupling was validated by SDS-PAGE and reversed-phase HPLC. The specificity of the target recognition of HRP-MyrB could be shown in an NTCP-overexpressing liver parenchymal cell line, as demonstrated by competitive inhibition with an excess of free MyrB and displayed a strong linear dependency on the applied HRP-MyrB concentration. In vivo studies in zebrafish embryos revealed a dominating interaction of HRP-MyrB with scavenger endothelial cells vs xenografted NTCP expressing mammalian cells. In mice, radiolabeled 125 I-HRP-MyrBy, as well as the non-NTCP targeted control HRP-peptide-construct ( 125 I-HRP-alaMyrBy) demonstrated a strong liver accumulation confirming the nonspecific interaction with scavenger cells. Still, MyrB conjugation to HRP resulted in an increased and NTCP-mediated hepatotropism, as revealed by competitive inhibition. In conclusion, the model enzyme HRP was successfully conjugated to MyrB to achieve NTCP-specific targeting in vitro with the potential for ex vivo diagnostic applications. In vivo, target specificity was reduced by non-NTCP-mediated interactions. Nonetheless, tissue distribution experiments in zebrafish embryos provide mechanistic insight into underlying scavenging processes indicating partial involvement of stabilin receptors.
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 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".