Juxtamembrane Protein Segments that Contribute to Recruitment of Cholesterol into Domains
Bibliographic record
Abstract
We investigated the properties of several peptides with sequences related to LWYIK, a segment found in the gp41 protein of HIV and believed to play a role in sequestering this protein to a cholesterol-rich domain in the membrane. This segment fulfills the requirements to be classified as a CRAC motif that has been suggested to predict those proteins that will partition into cholesterol-rich regions of the membrane. All of the peptides were studied with the terminal amino and carboxyl groups blocked, i.e., as N-acetyl-peptide-amides. Effects of cholesterol on the intensity of W emission generally parallel DSC evidence of sequestration of cholesterol. Modeling studies indicate that all of these peptides tend to partition with their mass center at the membrane interface at the level of the hydroxyl of cholesterol. Interaction with cholesterol is dual: van der Waals interactions between mainly hydrophobic surfaces and electrostatic stabilization of the cholesterol OH group. Thus, both experiments and modeling studies indicate that the preference of CRAC motifs for cholesterol-rich domains might be related to a membrane interfacial preference of the motif, to a capacity to wrap and block the cholesterol polar OH group by H-bond interactions, and to a capacity for peptide aromatic side chains to stack with cholesterol. These results were supported by studies of single mutations in the gp41 protein of HIV-1, in which L(679) is replaced with I. Despite the similarity of the properties of these amino acid residues, this single substitution resulted in a marked attenuation of the ability of JC53-BL HeLa-based HIV-1 indicator cells to form syncytia.
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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) | 0.001 | 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".