Abstract 2235 Identifying the CowN-MoFeP Interaction Site Utilizing Protein Cross-linking
Bibliographic record
Abstract
Nitrogenase is a bacterial enzyme that catalyzes the conversion of nitrogen gas into ammonia, a key plant nutrient. Nitrogenase is a protein complex consisting of a homodimeric reductase (Fe-protein) and a catalytic subunit (MoFeP), which is a dimer of dimers. Carbon monoxide (CO) inhibits nitrogenase by acting as a mixed inhibitor. To protect nitrogenase from CO, many nitrogen fixing organisms express a small protein, CowN, which interacts with MoFeP to weaken carbon monoxide inhibition. The goal of this research was to determine the interaction site between Gluconacetobacter diazotrophicus CowN and MoFeP. To do so, a cross-linking approach was utilized. A series of cross-linkers were tested to capture the MoFeP-CowN interaction, including EDC, BS3 and SIAB. The lysine-cysteine reactive cross-linker SIAB formed a cross-linked complex between CowN and MoFeP, suggesting that the cross-linking interface contains a lysine and a cysteine residue. Next, a variant of CowN, C90A-CowN, was created that eliminated all cysteine reactivity on CowN. SIAB cross-linking still occurred with C90A-CowN, indicating that the SIAB cross linker most likely reacts with a lysine on CowN and a cysteine on MoFeP. Further analysis of the cross-linked complex by mass spectrometry demonstrated that CowN interacted with both subunits of MoFeP. The sequence coverage for the complex was very high, however, no characteristic peptides indicative of a CowN-MoFeP complex were found. Further experiments using different mass spectrometry approaches and MoFeP mutants are currently underway to determine the CowN-MoFeP interaction site. I would like to thank the past nitrogenase team, especially Joshuah Arellano, Dr. Owens, Chapman University, for making the nitrogenase project progress so much. I would also like to give a big thank you to the NSF for funding the research at Chapman University in Schmid College of Science and Technology.
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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) | 0.002 | 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".