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The clinical spectrum of -related neurodevelopmental disorders (GRD) results from gene- and variant-dependent primary alterations of the NMDA receptor, disturbing glutamatergic neurotransmission. Despite gene variants' functional annotations being dually critical for stratification and precision medicine design, genetically diagnosed pathogenic variants currently outnumber their relative functional annotations. Based on high-resolution crystal 3D models and topological domains conservation between GluN1, GluN2A, and GluN2B subunits of the NMDAR, we have generated GluN1-GluN2A-GluN2B subunits structural superimposition model to find equivalent positions between GluN subunits. We have developed a structural algorithm that predicts functional changes in the equivalent structural positions in other GluN subunits. GRIN structural algorithm was computationally evaluated to the full missense variants repertoire, consisting of 4,525 variants. The analysis of this structure-based model revealed an absolute predictive power for GluN1, GluN2A, and GluN2B subunits, both in terms of pathogenicity-association (benign vs. pathogenic variants) and functional impact (loss-of-function, benign, gain-of-function). Further, we validated this computational algorithm experimentally, using an library of GluN2B-equivalent GluN2A artificial variants, designed from pathogenic GluN2B variants. Thus, the implementation of the GRIN structural algorithm allows to computationally predict the pathogenicity and functional annotations of variants, resulting in the duplication of pathogenic variants assignment, reduction by 30% of variants with uncertain significance, and increase by 70% of functionally annotated variants. Finally, GRIN structural algorithm has been implemented into variants Database (http://lmc.uab.es/grindb), providing a computational tool that accelerates missense variants stratification, contributing to clinical therapeutic decisions for this neurodevelopmental disorder.

Glutamatergic neurotransmission is crucial for brain development, wiring neuronal function, and synaptic plasticity mechanisms. Recent genetic studies showed the existence of autosomal dominant de novo GRIN gene variants associated with GRIN-related disorders (GRDs), a rare pediatric neurological disorder caused by N-methyl- d-aspartate receptor (NMDAR) dysfunction. Notwithstanding, GRIN variants identification is exponentially growing and their clinical, genetic, and functional annotations remain highly fragmented, representing a bottleneck in GRD patient's stratification. To shorten the gap between GRIN variant identification and patient stratification, we present the GRIN database (GRINdb), a publicly available, nonredundant, updated, and curated database gathering all available genetic, functional, and clinical data from more than 4000 GRIN variants. The manually curated GRINdb outputs on a web server, allowing query and retrieval of reported GRIN variants, and thus representing a fast and reliable bioinformatics resource for molecular clinical advice. Furthermore, the comprehensive mapping of GRIN variants' genetic and clinical information along NMDAR structure revealed important differences in GRIN variants' pathogenicity and clinical phenotypes, shedding light on GRIN-specific fingerprints. Overall, the GRINdb and web server is a resource for molecular stratification of GRIN variants, delivering clinical and investigational insights into GRDs. GRINdb is accessible at http://lmc.uab.es/grindb.