Designer molecules of the synaptic organizer MDGA1 reveal 3D conformational control of biological function
Bibliographic record
Abstract
MDGAs (MAM domain-containing glycosylphosphatidylinositol anchors) are synaptic cell surface molecules that regulate the formation of trans-synaptic bridges between neurexins (NRXNs) and neuroligins (NLGNs), which promote synaptic development. Mutations in MDGAs are implicated in various neuropsychiatric diseases. MDGAs bind NLGNs in cis on the postsynaptic membrane and physically block NLGNs from binding to NRXNs. In crystal structures, the six immunoglobulin (Ig) and single fibronectin III domains of MDGA1 reveal a striking compact, triangular shape, both alone and in complex with NLGNs. Whether this unusual domain arrangement is required for biological function or other arrangements occur with different functional outcomes is unknown. Here, we show that WT MDGA1 can adopt both compact and extended 3D conformations that bind NLGN2. Designer mutants targeting strategic molecular elbows in MDGA1 alter the distribution of 3D conformations while leaving the binding affinity between soluble ectodomains of MDGA1 and NLGN2 intact. In contrast, in a cellular context, these mutants result in unique combinations of functional consequences, including altered binding to NLGN2, decreased capacity to conceal NLGN2 from NRXN1β, and/or suppressed NLGN2-mediated inhibitory presynaptic differentiation, despite the mutations being located far from the MDGA1-NLGN2 interaction site. Thus, the 3D conformation of the entire MDGA1 ectodomain appears critical for its function, and its NLGN-binding site on Ig1-Ig2 is not independent of the rest of the molecule. As a result, global 3D conformational changes to the MDGA1 ectodomain via strategic elbows may form a molecular mechanism to regulate MDGA1 action within the synaptic cleft.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".