FABP7 Binds to Fatty Acid Micelles: Implications for Lipid Transport
Bibliographic record
Abstract
Abstract The transport of hydrophobic molecules, including long-chain fatty acids, within cells is highly dynamic. Hydrophobic molecules are unable to freely diffuse through the aqueous cytoplasm without a transporter. Fatty acid binding proteins (FABP) transport these molecules to different cellular compartments. As part of their transport, FABPs often associate with cell membranes to acquire and deliver their bound cargo. Understanding the nature of this transport is becoming increasingly important because lipid signaling functions are associated with metabolic pathways impacting disease pathologies such as carcinomas, autism and schizophrenia. Herein, we focus on Brain fatty acid binding protein (FABP7), which demonstrates localization to the cytoplasm and nucleus, influencing transcription and fatty acid metabolism. We use a combined biophysical approach to elucidate the interaction between FABP7 and model membranes. Specifically, we use microscale thermophoresis to show that FABP7 can bind oleic acid (OA) and docosahexaenoic acid (DHA) micelles, while differential scanning fluorimetry experiments show binding lowers the melting temperature of FABP7. Structural data from NMR and multiscale molecular dynamics simulations reveals that the interaction between FABP7 and micelles is through FABP7’s portal region residues. Our simulations also capture binding events where fatty acids dissociate from the model membrane and bind to FABP7. Overall, our data reveals a novel interaction between FABP7 and OA or DHA micelles and provides key structural insight into the transport of hydrophobic molecules. Significance This study examines how FABP7 binds to fatty acids at low and high fatty acid concentrations. Our binding assays, including microscale thermophoresis (MST) and Nile red fluorescence establish that FABP7 binds to both free fatty acids in solution and fatty acid micelles. NMR and computational experiments show that FABP7 specifically interacts with micelles through the portal region of the protein, thereby mediating ligand transfer into the binding cavity.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".