Human rElafin Inhibits HIV-1 Replication in Its Natural Target Cells
Bibliographic record
Abstract
Trappin-2/elafin is a novel innate immune factor that belongs to the serine protease inhibitor family and has known antibacterial, antifungal, and antiviral properties. In this study, we further investigated the anti-HIV activity of elafin using different cellular models and both X4- and R5-HIV-1 laboratory strains. We compared the antiviral activity of human recombinant elafin (rElafin) with three well-known antiretroviral drugs, AZT, tenofovir, and enfuvirtide. We have found that when the virus is pre-incubated with rElafin prior to the infection of the cells, HIV-1 replication is significantly inhibited. In target T cells and human peripheral blood mononuclear cells, maximal inhibition was achieved using submicromolar concentrations, and rElafin was found to be as potent as enfuvirtide, showing its potential for therapeutic application. We also show data on the mechanism of the antiviral activity of rElafin. We have demonstrated that rElafin neither binds to CD4, CXCR4, or CCR5 host cell receptors, nor to the viral glycoproteins gp120 and gp41. Furthermore, in our cell-to-cell fusion assays, in contrast to enfuvirtide, rElafin failed to block cell fusion. Altogether our results indicate that rElafin interferes with HIV replication at the early steps of its cycle but with a different mechanism of action than enfuvirtide. This study provides the first experimental evidence that elafin inhibits HIV replication in its natural target cells; therefore, elafin might have potential for its development as a new anti-HIV drug or microbicide.
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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".