Identification of Interactions between Abscisic Acid and Ribulose-1,5-Bisphosphate Carboxylase/Oxygenase
Bibliographic record
Abstract
Abscisic acid ((+)-ABA) is a phytohormone involved in the modulation of developmental processes and stress responses in plants. A chemical proteomics approach using an ABA mimetic probe was combined with in vitro assays, isothermal titration calorimetry (ITC), x-ray crystallography and in silico modelling to identify putative (+)-ABA binding-proteins in crude extracts of Arabidopsis thaliana. Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) was identified as a putative ABA-binding protein. Radiolabelled-binding assays yielded a Kd of 47 nM for (+)-ABA binding to spinach Rubisco, which was validated by ITC, and found to be similar to reported and experimentally derived values for the native ribulose-1,5-bisphosphate (RuBP) substrate. Functionally, (+)-ABA caused only weak inhibition of Rubisco catalytic activity (Ki of 2.1 mM), but more potent inhibition of Rubisco activation (Ki of ~ 130 μM). Comparative structural analysis of Rubisco in the presence of (+)-ABA with RuBP in the active site revealed only a putative low occupancy (+)-ABA binding site on the surface of the large subunit at a location distal from the active site. However, subtle distortions in electron density in the binding pocket and in silico docking support the possibility of a higher affinity (+)-ABA binding site in the RuBP binding pocket. Overall we conclude that (+)-ABA interacts with Rubisco. While the low occupancy (+)-ABA binding site and weak non-competitive inhibition of catalysis may not be relevant, the high affinity site may allow ABA to act as a negative effector of Rubisco activation.
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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".