Structural biology of <scp>DOCK‐family</scp> guanine nucleotide exchange factors
Bibliographic record
Abstract
DOCK proteins are a family of multi‐domain guanine nucleotide exchange factors (GEFs) that activate the RHO GTPases CDC42 and RAC1, thereby regulating several RHO GTPase‐dependent cellular processes. DOCK proteins are characterized by the catalytic DHR2 domain (DOCKDHR2), and a phosphatidylinositol(3,4,5)P3‐binding DHR1 domain (DOCKDHR1) that targets DOCK proteins to plasma membranes. DOCK‐family GEFs are divided into four subfamilies (A to D) differing in their specificities for CDC42 and RAC1, and the composition of accessory signalling domains. Additionally, the DOCK‐A and DOCK‐B subfamilies are constitutively associated with ELMO proteins that auto‐inhibit DOCK GEF activity. We review structural studies that have provided mechanistic insights into DOCK‐protein functions. These studies revealed how a conserved nucleotide sensor in DOCKDHR2 catalyses nucleotide exchange, the basis for how different DOCK proteins activate specifically CDC42 and RAC1, and sometimes both, and how up‐stream regulators relieve the ELMO‐mediated auto‐inhibition. We conclude by presenting a model for full‐length DOCK9 of the DOCK‐D subfamily. The involvement of DOCK GEFs in a range of diseases highlights the importance of gaining structural insights into these proteins to better understand and specifically target them.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".