Structural Determinants of IFNα Distinguish Antiviral and Potentially Toxic Functions. (39.7)
Bibliographic record
Abstract
Abstract Interferon alpha (IFNα), a cytokine with multiple functions in innate and adaptive immunity and a potent inhibitor of human immunodeficiency virus (HIV), exerts antiviral activity, in part, by enhancing apolipoprotein B mRNA-editing enzyme-catalytic polypeptide-like 3(APOBEC3) family members. Although IFNα therapy is associated with reduced viral burden, this cytokine also mediates immune dysfunction and toxicities. Through detailed mapping of IFNα receptor binding sites, we generated IFNα hybrids and mutants and determined that structural changes in the C-loop influencing receptor interactions alter IFN’s ability to limit retroviral replication. Selective IFNα constructs differentially block HIV replication and their directional magnitude of inhibition correlates with elevated APOBEC3 levels with less significant changes in transcription of other antiviral molecules such as TRIM22 and PKR. Besides participation of the JAK-STAT pathway, we uncover previously unappreciated roles for NFκB, CAMK and PI3K signaling pathways in induction of APOBEC3 by the IFN constructs. Importantly, certain mutants exhibited reduced toxicity as reflected by induced indoleamine 2,3-dioxygenase and TNFα compared with intact IFN, suggesting discreet and shared intracellular signaling pathways. Defining IFN structure and function relative to APOBEC and other antiviral genes may enable the design of novel IFN-related molecules preserving beneficial antiviral roles while minimizing negative effects.
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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) | 0.004 | 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".