Real-time NMR Study of Guanine Nucleotide Exchange and Activation of RhoA by PDZ-RhoGEF
Bibliographic record
Abstract
Small guanosine triphosphatases (GTPases) become activated when GDP is replaced by GTP at the highly conserved nucleotide binding site. This process is intrinsically very slow in most GTPases but is significantly accelerated by guanine nucleotide exchange factors (GEFs). Nucleotide exchange in small GTPases has been widely studied using spectroscopy with fluorescently tagged nucleotides. However, this method suffers from effects of the bulky fluorescent moiety covalently attached to the nucleotide. Here, we have used a newly developed real-time NMR-based assay to monitor small GTPase RhoA nucleotide exchange by probing the RhoA conformation. We compared RhoA nucleotide exchange from GDP to GTP and GTP analogues in the absence and presence of the catalytic DH-PH domain of PDZ-RhoGEF (DH-PH(PRG)). Using the non-hydrolyzable analogue guanosine-5'-O-(3-thiotriphosphate), which we found to be a reliable mimic of GTP, we obtained an intrinsic nucleotide exchange rate of 5.5 x 10(-4) min(-1). This reaction is markedly accelerated to 1179 x 10(-4) min(-1) in the presence of DH-PH(PRG) at a ratio of 1:8,000 relative to RhoA. Mutagenesis studies confirmed the importance of Arg-868 near a conserved region (CR3) of the Dbl homology (DH) domain and revealed that Glu-741 in CR1 is critical for full activity of DH-PH(PRG), together suggesting that the catalytic mechanism of PDZ-RhoGEF is similar to Tiam1. Mutation of the single RhoA (E97A) residue that contacts the pleckstrin homology (PH) domain rendered the mutant 10-fold less sensitive to the activity of DH-PH(PRG). Interestingly, this mutation does not affect RhoA activation by leukemia-associated RhoGEF (LARG), indicating that the PH domains of these two homologous GEFs may play different roles.
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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".