The Recognition Unit of FIBCD1 Organizes into a Noncovalently Linked Tetrameric Structure and Uses a Hydrophobic Funnel (S1) for Acetyl Group Recognition
Bibliographic record
Abstract
We have recently identified FIBCD1 (Fibrinogen C domain containing 1) as a type II transmembrane endocytic receptor located primarily in the intestinal brush border. The ectodomain of FIBCD1 comprises a coiled coil, a polycationic region, and a C-terminal FReD (fibrinogen-related domain) that assembles into disulfide-linked homotetramers. The FIBCD1-FReD binds Ca(2+) dependently to acetylated structures like chitin, N-acetylated carbohydrates, and amino acids. FReDs are present in diverse innate immune pattern recognition proteins including the ficolins and horseshoe crab TL5A. Here, we use chemical cross-linking, combined with analytical ultracentrifugation and electron microscopy of the negatively stained recombinant FIBCD1-FReD to show that it assembles into noncovalent tetramers in the absence of the coiled coil. We use surface plasmon resonance, carbohydrate binding, and pulldown assays combined with site-directed mutagenesis to define the binding site involved in the interaction of FIBCD1 with acetylated structures. We show that mutations of central residues (A432V and H415G) in the hydrophobic funnel (S1) abolish the binding of FIBCD1 to acetylated bovine serum albumin and chitin. The double mutations (D393N/D395A) at the putative calcium-binding site reduce the ability of FIBCD1 to bind ligands. We conclude that the FReDs of FIBCD1 forms noncovalent tetramers and that the acetyl-binding site of FReDs of FIBCD1 is homologous to that of tachylectin 5A and M-ficolin but not to the FReD of L-ficolin. We suggest that the spatial organization of the FIBCD1-FReDs determine the molecular pattern recognition specificity and subsequent biological functions.
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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 | 0.001 |
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".