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.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816381PMC
http://dx.doi.org/10.3389/fncel.2022.998719DOI Listing

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