Influence of Membrane Surface Charge and Post-Translational Modifications to Myelin Basic Protein on Its Ability To Tether the Fyn-SH3 Domain to a Membrane in Vitro
Bibliographic record
Abstract
Myelin basic protein (MBP) is a highly post-translationally modified, multifunctional structural component of central nervous system myelin, adhering to phospholipid membranes and assembling cytoskeletal proteins, and has previously been shown to bind SH3 domains in vitro and tether them to a membrane surface [Polverini, E., et al. (2008) Biochemistry 47, 267-282]. Since molecular modeling shows that the Fyn-SH3 domain has a negative surface charge density even after binding the MBP ligand, we have investigated the influence of negative membrane surface charge and the effects of post-translational modifications to MBP on the interaction of the Fyn-SH3 domain with membrane-associated MBP. Using a sedimentation assay with multilamellar vesicles consisting of neutral phosphatidylcholine (PC) and negatively charged phosphatidylinositol (PI), we demonstrate that increasing the negative surface charge of the membrane by increasing the proportion of PI reduces the amount of Fyn-SH3 domain that binds to membrane-associated MBP, due to electrostatic repulsion. When one of the phosphoinositides, PI(4)P or PI(4,5)P(2) was substituted for PI in equal proportion, none of the Fyn-SH3 domain bound to MBP under the conditions that were used. Post-translational modifications of MBP which reduced its net positive charge, i.e., phosphorylation or arginine deimination, increased the degree of repulsion of Fyn-SH3 from the membrane surface, an effect further modulated by the lipid charge. This study suggests that changes in membrane negative surface charge due to protein or lipid modifications, which could occur during cell signaling, can regulate the binding of the Fyn-SH3 domain to membrane-associated MBP and thus could regulate the activity of Fyn at the oligodendrocyte membrane surface.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".