Interaction of Lipid-Bound Myelin Basic Protein with Actin Filaments and Calmodulin
Bibliographic record
Abstract
Myelin basic protein (MBP) binds to negatively charged lipids on the cytosolic surface of oligodendrocytes (OLs) and is believed to be responsible for adhesion of these surfaces in the multilayered myelin sheath. MBP in solution has been shown by others to bind to both G- and F-actin, to bundle F-actin filaments, and to induce polymerization of G-actin. Here we show that MBP bound to acidic lipids can also bind to both G- and F-actin and cause their sedimentation together with MBP-lipid vesicles. Thus it can simultaneously utilize some of its basic residues to bind to the lipid bilayer and some to bind to actin. The amount of actin bound to the MBP-lipid vesicles decreased with increasing net negative surface charge of the lipid vesicles. It was also less for vesicles containing the lipid composition predicted for the cytosolic surface of myelin than for PC vesicles containing a similar amount of an acidic lipid. Calmodulin caused dissociation of actin from MBP and of the MBP-actin complex from the vesicles. However, it did not cause dissociation of bundles of actin filaments once these had formed as long as some MBP was still present. These results suggest that MBP could be a membrane actin-binding protein in OLs/myelin and its actin binding can be regulated by calmodulin and by the lipid composition of the membrane. Actin binding to MBP decreased the labeling of MBP by the hydrophobic photolabel 3-(trifluoromethyl)-3-(m-[(125)I]iodophenyl)diazirine (TID), indicating that it decreased the hydrophobic interactions of MBP with the bilayer. This change in interaction of MBP with the bilayer could then create a cytosol to membrane signal caused by changes in interaction of the cytoskeleton with the membrane.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".