Identification of homologous GluN subunits variants accelerates GRIN variants stratification.

The clinical spectrum of GRIN-related neurodevelopmental disorders (GRD) results from gene- and variant-dependent primary alterations of the NMDA receptor, disturbing glutamatergic neurotransmission. Despite GRIN gene variants' functional annotations being dually critical for stratification and precision medicine design, genetically diagnosed pathogenic GRIN 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 GRIN structural algorithm that predicts functional changes in the equivalent structural positions in other GluN subunits. GRIN structural algorithm was computationally evaluated to the full GRIN 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 in silico 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 GRIN variants, resulting in the duplication of pathogenic GRIN variants assignment, reduction by 30% of GRIN variants with uncertain significance, and increase by 70% of functionally annotated GRIN variants. Finally, GRIN structural algorithm has been implemented into GRIN variants Database (http://lmc.uab.es/grindb), providing a computational tool that accelerates GRIN missense variants stratification, contributing to clinical therapeutic decisions for this neurodevelopmental disorder.

Correction to 'TMSNP: a web server to predict pathogenesis of missense mutations in the transmembrane region of membrane proteins'.

[This corrects the article DOI: 10.1093/nar/lqab008.].

TMSNP: a web server to predict pathogenesis of missense mutations in the transmembrane region of membrane proteins.

The massive amount of data generated from genome sequencing brings tons of newly identified mutations, whose pathogenic/non-pathogenic effects need to be evaluated. This has given rise to several mutation predictor tools that, in general, do not consider the specificities of the various protein groups. We aimed to develop a predictor tool dedicated to membrane proteins, under the premise that their specific structural features and environment would give different responses to mutations compared to globular proteins. For this purpose, we created TMSNP, a database that currently contains information from 2624 pathogenic and 196 705 non-pathogenic reported mutations located in the transmembrane region of membrane proteins. By computing various conservation parameters on these mutations in combination with annotations, we trained a machine-learning model able to classify mutations as pathogenic or not. TMSNP (freely available at http://lmc.uab.es/tmsnp/) improves considerably the prediction power of commonly used mutation predictors trained with globular proteins.

The mutational landscape of human olfactory G protein-coupled receptors.

BACKGROUND: Olfactory receptors (ORs) constitute a large family of sensory proteins that enable us to recognize a wide range of chemical volatiles in the environment. By contrast to the extensive information about human olfactory thresholds for thousands of odorants, studies of the genetic influence on olfaction are limited to a few examples. To annotate on a broad scale the impact of mutations at the structural level, here we analyzed a compendium of 119,069 natural variants in human ORs collected from the public domain. RESULTS: OR mutations were categorized depending on their genomic and protein contexts, as well as their frequency of occurrence in several human populations. Functional interpretation of the natural changes was estimated from the increasing knowledge of the structure and function of the G protein-coupled receptor (GPCR) family, to which ORs belong. Our analysis reveals an extraordinary diversity of natural variations in the olfactory gene repertoire between individuals and populations, with a significant number of changes occurring at the structurally conserved regions. A particular attention is paid to mutations in positions linked to the conserved GPCR activation mechanism that could imply phenotypic variation in the olfactory perception. An interactive web application (hORMdb, Human Olfactory Receptor Mutation Database) was developed for the management and visualization of this mutational dataset. CONCLUSION: We performed topological annotations and population analysis of natural variants of human olfactory receptors and provide an interactive application to explore human OR mutation data. We envisage that the utility of this information will increase as the amount of available pharmacological data for these receptors grow. This effort, together with ongoing research in the study of genetic changes in other sensory receptors could shape an emerging sensegenomics field of knowledge, which should be considered by food and cosmetic consumer product manufacturers for the benefit of the general population.

GRIN database: A unified and manually curated repertoire of GRIN variants.

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.

Disease-associated GRIN protein truncating variants trigger NMDA receptor loss-of-function.

De novo GRIN variants, encoding for the ionotropic glutamate NMDA receptor subunits, have been recently associated with GRIN-related disorders, a group of rare paediatric encephalopathies. Current investigational and clinical efforts are focused to functionally stratify GRIN variants, towards precision therapies of this primary disturbance of glutamatergic transmission that affects neuronal function and brain. In the present study, we aimed to comprehensively delineate the functional outcomes and clinical phenotypes of GRIN protein truncating variants (PTVs)-accounting for ~20% of disease-associated GRIN variants-hypothetically provoking NMDAR hypofunctionality. To tackle this question, we created a comprehensive GRIN PTVs variants database compiling a cohort of nine individuals harbouring GRIN PTVs, together with previously identified variants, to build-up an extensive GRIN PTVs repertoire composed of 293 unique variants. Genotype-phenotype correlation studies were conducted, followed by cell-based assays of selected paradigmatic GRIN PTVs and their functional annotation. Genetic and clinical phenotypes meta-analysis revealed that heterozygous GRIN1, GRIN2C, GRIN2D, GRIN3A and GRIN3B PTVs are non-pathogenic. In contrast, heterozygous GRIN2A and GRIN2B PTVs are associated with specific neurological clinical phenotypes in a subunit- and domain-dependent manner. Mechanistically, cell-based assays showed that paradigmatic pathogenic GRIN2A and GRIN2B PTVs result on a decrease of NMDAR surface expression and NMDAR-mediated currents, ultimately leading to NMDAR functional haploinsufficiency. Overall, these findings contribute to delineate GRIN PTVs genotype-phenotype association and GRIN variants stratification. Functional studies showed that GRIN2A and GRIN2B pathogenic PTVs trigger NMDAR hypofunctionality, and thus accelerate therapeutic decisions for this neurodevelopmental condition.

HomolWat: a web server tool to incorporate 'homologous' water molecules into GPCR structures.

Internal water molecules play an essential role in the structure and function of membrane proteins including G protein-coupled receptors (GPCRs). However, technical limitations severely influence the number and certainty of observed water molecules in 3D structures. This may compromise the accuracy of further structural studies such as docking calculations or molecular dynamics simulations. Here we present HomolWat, a web application for incorporating water molecules into GPCR structures by using template-based modelling of homologous water molecules obtained from high-resolution structures. While there are various tools available to predict the positions of internal waters using energy-based methods, the approach of borrowing lacking water molecules from homologous GPCR structures makes HomolWat unique. The tool can incorporate water molecules into a protein structure in about a minute with around 85% of water recovery. The web server is freely available at http://lmc.uab.es/homolwat.

DIMERBOW: exploring possible GPCR dimer interfaces.

MOTIVATION: G protein-coupled receptors (GPCRs) can form homo-, heterodimers and larger order oligomers that exert different functions than monomers. The pharmacological potential of such complexes is hampered by the limited information available on the type of complex formed and its quaternary structure. Several GPCR structures in the Protein Data Bank display crystallographic interfaces potentially compatible with physiological interactions. RESULTS: Here, we present DIMERBOW, a database and web application aimed to visually browse the complete repertoire of potential GPCR dimers present in solved structures. The tool is suited to help finding the best possible structural template to model GPCR homomers. AVAILABILITY AND IMPLEMENTATION: DIMERBOW is available at http://lmc.uab.es/dimerbow/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.