CryoEM Structures of the Human HIV-1 Restriction Factor SERINC3 and Function as a Lipid Transporter
Bibliographic record
Abstract
Abstract The host proteins SERINC3 and SERINC5 are HIV-1 restriction factors that reduce infectivity when incorporated into the viral envelope. The HIV-1 accessory protein Nef abrogates incorporation of SERINCs via binding to intracellular loop 4 (ICL4). CryoEM maps of full-length human SERINC3 and an ICL4 deletion construct reveal that hSERINC3 is comprised of two α - helical bundles connected by a ∼40-residue, tilted, “crossmember” helix. The design resembles non-ATP-dependent lipid transporters. Consistently, purified hSERINCs reconstituted into proteoliposomes flip phosphatidylserine (PS), phosphatidylethanolamine and phosphatidylcholine. SERINC3 and SERINC5 reduce infectivity and expose PS on the surface of HIV-1 and also MLV, which is counteracted by Nef and GlycoGag, respectively. Antiviral activities by SERINCs and the scramblase TMEM16F correlate with the exposure of PS and with altered conformation of the envelope glycoprotein. We conclude that SERINCs are lipid transporters, and we demonstrate that lipid flipping is directly correlated with loss of infectivity. One Sentence Summary The HIV-1 restriction factor SERINC3 has a molecular design similar to non-ATP dependent lipid transporters, a function supported by the observation of flipping activity in proteoliposomes and exposure of phosphatidylserine on HIV-1 and MLV particles, which is correlated with loss of infectivity.
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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".