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Record W2748248568 · doi:10.1016/j.neuron.2017.07.040

Structural Mechanism for Modulation of Synaptic Neuroligin-Neurexin Signaling by MDGA Proteins

2017· article· en· W2748248568 on OpenAlexafffund
Jonathan Elegheert, Vedrana Cvetkovska, Amber J. Clayton, Christina Heroven, Kristel M. Vennekens, Samuel N. Smukowski, Michael C. Regan, Wanyi Jia, Alexandra Smith, Hiro Furukawa, Jeffrey N. Savas, Joris de Wit, Jo Begbie, Ann Marie Craig, A.R. Aricescu

Bibliographic record

VenueNeuron · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Neurological Disorders and StrokeDiamond Light SourceNational Institute of General Medical SciencesNational Institute of Mental HealthMedical Research CouncilCanadian Institutes of Health ResearchNational Institute on Deafness and Other Communication DisordersWellcome TrustEuropean Synchrotron Radiation FacilityMichael Smith Health Research BCNational Institutes of HealthCancer Research UK
KeywordsNeurexinNeuroliginNeuroscienceAlternative splicingRNA splicingGene isoformNeurotransmissionBiologySynapseExcitatory postsynaptic potentialCell biologyInhibitory postsynaptic potentialGeneGeneticsReceptor

Abstract

fetched live from OpenAlex

Neuroligin-neurexin (NL-NRX) complexes are fundamental synaptic organizers in the central nervous system. An accurate spatial and temporal control of NL-NRX signaling is crucial to balance excitatory and inhibitory neurotransmission, and perturbations are linked with neurodevelopmental and psychiatric disorders. MDGA proteins bind NLs and control their function and interaction with NRXs via unknown mechanisms. Here, we report crystal structures of MDGA1, the NL1-MDGA1 complex, and a spliced NL1 isoform. Two large, multi-domain MDGA molecules fold into rigid triangular structures, cradling a dimeric NL to prevent NRX binding. Structural analyses guided the discovery of a broad, splicing-modulated interaction network between MDGA and NL family members and helped rationalize the impact of autism-linked mutations. We demonstrate that expression levels largely determine whether MDGAs act selectively or suppress the synapse organizing function of multiple NLs. These results illustrate a potentially brain-wide regulatory mechanism for NL-NRX signaling modulation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.235
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations82
Published2017
Admission routes2
Has abstractyes

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