Small Molecule Inhibition of HIV-1–Induced MHC-I Down-Regulation Identifies a Temporally Regulated Switch in Nef Action
Bibliographic record
Abstract
HIV-1 Nef triggers down-regulation of cell-surface MHC-I by assembling a Src family kinase (SFK)-ZAP-70/Syk-PI3K cascade. Here, we report that chemical disruption of the Nef-SFK interaction with the small molecule inhibitor 2c blocks assembly of the multi-kinase complex and represses HIV-1-mediated MHC-I down-regulation in primary CD4(+) T-cells. 2c did not interfere with the PACS-2-dependent trafficking of Nef required for the Nef-SFK interaction or the AP-1 and PACS-1-dependent sequestering of internalized MHC-I, suggesting the inhibitor specifically interfered with the Nef-SFK interaction required for triggering MHC-I down-regulation. Transport studies revealed Nef directs a highly regulated program to down-regulate MHC-I in primary CD4(+) T-cells. During the first two days after infection, Nef assembles the 2c-sensitive multi-kinase complex to trigger down-regulation of cell-surface MHC-I. By three days postinfection Nef switches to a stoichiometric mode that prevents surface delivery of newly synthesized MHC-I. Pharmacologic inhibition of the multi-kinase cascade prevents the Nef-dependent block in MHC-I transport, suggesting the signaling and stoichiometric modes are causally linked. Together, these studies resolve the seemingly controversial models that describe Nef-induced MHC-I down-regulation and provide new insights into the mechanism of Nef action.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".