The HB-19 Pseudopeptide 5[Kpsi(CH <sub>2</sub> N)PR]-TASP Inhibits Attachment of T Lymphocyte- and Macrophage-Tropic HIV to Permissive Cells
Bibliographic record
Abstract
The HB-19 pseudopeptide 5[Kpsi(CH2N)PR]-TASP[psi(CH2N) indicating a reduced peptide bond], which binds the cell surface-expressed nucleolin, is a potent inhibitor of HIV infection. Here, by using primary T lymphocyte cultures and an experimental cell model to monitor HIV entry, we show that HB-19 inhibits in a dose-dependent manner both T lymphocyte- and macrophage-tropic HIV isolates. Similar positively charged control pseudopeptides have no effect on HIV infection even at high concentrations. These observations, and the fact that HB-19 has no effect on SIV-mac and HIV-1 pseudotyped with VSV envelope glycoproteins, confirm the specific nature of this inhibitor against the entry process mediated by the HIV envelope glycoproteins. Finally, association of low doses of HB-19 with beta-chemokines or AZT results in an increased inhibitory effect on HIV infection. HB-19 has no inhibitory effect when added to cells a few hours after HIV entry. On the other hand, in HB-19-pretreated cells, the inhibitory effect persists for several hours, even after washing cells to remove away the unbound pseudopeptide. Under such conditions, the attachment of HIV particles to cells is inhibited as efficiently as by neutralizing monoclonal antibodies directed against the V3 loop. In view of its specific mode of action on various HIV isolates, HB-19 represents a potential anti-HIV drug.
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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".