Structural stratification of GRIN2B and GRIN2A ligand-binding domain variants reveals mechanistically distinct classes of receptor dysfunction

This working paper presents a convergent three-track structural analysis of pathogenic GRIN2B and GRIN2A variants using AlphaFold 3, applying ipSAE interface scoring, binding pocket volumetrics, and GNINA molecular docking across 525 predicted structures. The results are consistent with two structural response patterns: open-cleft stabilisation (E413G, D731N) and interface disruption (R682C, A716T). Which converge across all three independent tracks and may warrant functional characterisation for GoF/LoF classification in NMDA receptor-related neurodevelopmental disorders. This record is released as a working paper to establish scientific priority of the described findings and methodology. Primary data and analysis scripts are available upon reasonable request for validation purposes. Extended datasets and implementation protocols are available under a formal collaboration agreement. Version 2: Corrected GNINA docking statistics (R682C, A716T) and improvements to results section.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-22
DOI
https://doi.org/10.5281/zenodo.20345745
Primary Topic
Genomics and Rare Diseases
Type
article
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article

Structural stratification of GRIN2B and GRIN2A ligand-binding domain variants reveals mechanistically distinct classes of receptor dysfunction

Daniël Josephus Willem van Leeuwerden
Zenodo (CERN European Organization for Nuclear Research)
Genomics and Rare Diseases
article

Structural stratification of GRIN2B and GRIN2A ligand-binding domain variants reveals mechanistically distinct classes of receptor dysfunction

Daniël Josephus Willem van Leeuwerden
article en

Abstract

This working paper presents a convergent three-track structural analysis of pathogenic GRIN2B and GRIN2A variants using AlphaFold 3, applying ipSAE interface scoring, binding pocket volumetrics, and GNINA molecular docking across 525 predicted structures. The results are consistent with two structural response patterns: open-cleft stabilisation (E413G, D731N) and interface disruption (R682C, A716T). Which converge across all three independent tracks and may warrant functional characterisation for GoF/LoF classification in NMDA receptor-related neurodevelopmental disorders. This record is released as a working paper to establish scientific priority of the described findings and methodology. Primary data and analysis scripts are available upon reasonable request for validation purposes. Extended datasets and implementation protocols are available under a formal collaboration agreement. Version 2: Corrected GNINA docking statistics (R682C, A716T) and improvements to results section.

Zenodo (CERN European Organization for Nuclear Research)
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Genomics and Rare Diseases
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