High Resolution Structure of an Alternate Form of the Ferric Ion Binding Protein from Haemophilus influenzae
Bibliographic record
Abstract
The periplasmic iron binding protein of pathogenic Gram-negative bacteria performs an essential role in iron acquisition from transferrin and other iron sources. Structural analysis of this protein from Haemophilus influenzae identified four amino acids that ligand the bound iron: His(9), Glu(57), Tyr(195), and Tyr(196). A phosphate provides an additional ligand, and the presence of a water molecule is required to complete the octahedral geometry for stable iron binding. We report the 1.14-A resolution crystal structure of the iron-loaded form of the H. influenzae periplasmic ferric ion binding protein (FbpA) mutant H9Q. This protein was produced in the periplasm of Escherichia coli and, after purification and conversion to the apo form, was iron-loaded. H9Q is able to bind ferric iron in an open conformation. A surprising finding in the present high resolution structure is the presence of EDTA located at the previously determined anion ternary binding site, where phosphate is located in the wild type holo and apo structures. EDTA contributes four of the six coordinating ligands for iron, with two Tyr residues, 195 and 196, completing the coordination. This is the first example of a metal binding protein with a bound metal.EDTA complex. The results suggest that FbpA may have the ability to bind and transport iron bound to biological chelators, in addition to bare ferric iron.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".