Enhanced Binding of TonB to a Ligand-loaded Outer Membrane Receptor
Bibliographic record
Abstract
The ferric hydroxymate uptake (FhuA) receptor from Escherichia coli facilitates transport of siderophores ferricrocin and ferrichrome and siderophore-antibiotic conjugates such as albomycin and rifamycin CGP 4832. FhuA is also the receptor for phages T5, T1, Phi80, UC-1, for colicin M and for the antimicrobial peptide microcin MccJ21. Energy for transport is provided by the cytoplasmic membrane complex TonB.ExbB.ExbD, which uses the proton motive force of the cytoplasmic membrane to transduce energy to the outer membrane. To accomplish energy transfer, TonB contacts outer membrane receptors. However, the stoichiometry of TonB. receptor complexes and their sites of interaction remain uncertain. In this study, analyses of FhuA interactions with two recombinant TonB proteins by analytical ultracentrifugation revealed that TonB forms a 2:1 complex with FhuA. The presence of the FhuA-specific ligand ferricrocin enhanced the amounts of complex but is not essential for its formation. Surface plasmon resonance experiments demonstrated that FhuA.TonB interactions are multiple and have apparent affinities in the nanomolar range. TonB also possesses two distinct binding regions: one in the C terminus of the protein, for which binding to FhuA is ferricrocin-independent, and a higher affinity region outside the C terminus, for which ferricrocin enhances interactions with FhuA. Together these experiments establish that FhuA.TonB interactions are more intricate than originally predicted, that the TonB.FhuA stoichiometry is 2:1, and that ferricrocin modulates binding of FhuA to TonB at regions outside the C-terminal domain of TonB.
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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 | 0.000 |
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".