STAG2: Computational Analysis of Missense Variants Involved in Disease
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PROVIDER: S-EPMC10816197 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:IntroductionMany missense variants in G protein-coupled receptors (GPCRs) involved in the neuroendocrine regulation of reproduction have been identified by phenotype-driven or large-scale exome sequencing. Computational functional prediction analysis is commonly performed to evaluate their impact on receptor function.MethodsTo assess the performance and outcome of functional prediction analyses for these GPCRs, we performed a statistical analysis of the prediction performance of SIFT and PolyPhen-2 for variants with documented biological function as well as variants retrieved from Ensembl. We obtained missense variants with documented biological function testing from patients with reproductive disorders from a comprehensive literature search. Missense variants from individuals with known reproductive disorders were retrieved from the Human Gene Mutation Database. Missense variants from the general population were retrieved from the Ensembl genome database.ResultsThe accuracies of SIFT and PolyPhen-2 were 83 and 85%, respectively. The performance of both prediction tools was greater in predicting loss-of-function variants (SIFT: 92%; PolyPhen-2: 95%) than in predicting variants that did not affect function (SIFT: 54%; PolyPhen-2: 57%). Concordance between SIFT and PolyPhen-2 did not improve accuracy. Surprisingly, approximately half of the variants retrieved from Ensembl were predicted as loss-of-function variants by SIFT (47%) and PolyPhen-2 (54%).ConclusionOur findings provide new guidance for interpreting the results and limitations of computational functional prediction analyses for GPCRs and will help to determine which variants require biological function testing. In addition, our findings raise important questions regarding the link between genotype and phenotype in the general population.
| S-EPMC4684493 | biostudies-literature
Project description:1 Novel Missense Variants in Patients with Primary Immunodeficiency and Immune dysregulation
| PRJEB46587 | ENA
Project description:The renal outer medullary potassium (ROMK) channel is essential for potassium transport in the kidney, and its dysfunction is associated with a salt-wasting disorder known as Bartter syndrome. Despite its physiological significance, we lack a mechanistic understanding of the molecular defects in ROMK underlying most Bartter syndrome-associated mutations. To this end, we employed a ROMK-dependent yeast growth assay and tested single amino acid variants selected by a series of computational tools representative of different approaches to predict each variants' pathogenicity. In one approach, we used in silico saturation mutagenesis, i.e. the scanning of all possible single amino acid substitutions at all sequence positions to estimate their impact on function, and then employed a new machine learning classifier known as Rhapsody. We also used two additional tools, EVmutation and Polyphen-2, which permitted us to make consensus predictions on the pathogenicity of single amino acid variants in ROMK. Experimental tests performed for selected mutants in different classes validated the vast majority of our predictions and provided insights into variants implicated in ROMK dysfunction. On a broader scope, our analysis suggests that consolidation of data from complementary computational approaches provides an improved and facile method to predict the severity of an amino acid substitution and may help accelerate the identification of disease-causing mutations in any protein.
| S-EPMC7162551 | biostudies-literature
Project description:The Snyder-Robinson syndrome is caused by missense mutations in the spermine sythase gene that encodes a protein (SMS) of 529 amino acids. Here we investigate, in silico, the molecular effect of three missense mutations, c.267G>A (p.G56S), c.496T>G (p.V132G), and c.550T>C (p.I150T) in SMS that were clinically identified to cause the disease. Single-point energy calculations, molecular dynamics simulations, and pKa calculations revealed the effects of these mutations on SMS's stability, flexibility, and interactions. It was predicted that the catalytic residue, Asp276, should be protonated prior binding the substrates. The pKa calculations indicated the p.I150T mutation causes pKa changes with respect to the wild-type SMS, which involve titratable residues interacting with the S-methyl-5'-thioadenosine (MTA) substrate. The p.I150T missense mutation was also found to decrease the stability of the C-terminal domain and to induce structural changes in the vicinity of the MTA binding site. The other two missense mutations, p.G56S and p.V132G, are away from active site and do not perturb its wild-type properties, but affect the stability of both the monomers and the dimer. Specifically, the p.G56S mutation is predicted to greatly reduce the affinity of monomers to form a dimer, and therefore should have a dramatic effect on SMS function because dimerization is essential for SMS activity.
| S-EPMC2932761 | biostudies-literature
Project description:The human transmembrane protease serine 2 (TMPRSS2) protein plays an important role in prostate cancer progression. It also facilitates viral entry into target cells by proteolytically cleaving and activating the S protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the current study, we used different available tools like SIFT, PolyPhen2.0, PROVEAN, SNAP2, PMut, MutPred2, I-Mutant Suite, MUpro, iStable, ConSurf, ModPred, SwissModel, PROCHECK, Verify3D, and TM-align to identify the most deleterious variants and to explore possible effects on the TMPRSS2 stability, structure, and function. The six missense variants tested were evaluated to have deleterious effects on the protein by SIFT, PolyPhen2.0, PROVEAN, SNAP2, and PMut. Additionally, V160M, G181R, R240C, P335L, G432A, and D435Y variants showed a decrease in stability by at least 2 servers; G181R, G432A, and D435Y are highly conserved and identified posttranslational modifications sites (PTMs) for proteolytic cleavage and ADP-ribosylation using ConSurf and ModPred servers. The 3D structure of TMPRSS2 native and mutants was generated using 7 meq as a template from the SwissModeller group, refined by ModRefiner, and validated using the Ramachandran plot. Hence, this paper can be advantageous to understand the association between these missense variants rs12329760, rs781089181, rs762108701, rs1185182900, rs570454392, and rs867186402 and susceptibility to SARS-CoV-2.
| S-EPMC8531787 | biostudies-literature
Project description:BackgroundPeriventricular nodular heterotopia (PNH) is a cell migration disorder associated with mutations in Filamin-A (FLNA) gene on chromosome X. Majority of the individuals with PNH-associated FLNA mutations are female whereas liveborn males with FLNA mutations are very rare. Fetal viability of the males seems to depend on the severity of the variant. Splicing or severe truncations presumed loss of function of the protein product, lead to male lethality and only partial-loss-of-function variants are reported in surviving males. Those variants mostly manifest milder clinical phenotypes in females and thus avoid detection of the disease in females.MethodsWe describe a novel p.Arg484Gln variant in the FLNA gene by performing whole exome analysis on the index case, his one affected brother and his healthy non-consanguineous parents. The transmission of PNH from a clinically asymptomatic mother to two sons is reported in a fully penetrant classical X-linked dominant mode. The variant was verified via Sanger sequencing. Additionally, we investigated the impact of missense mutations reported in affected males on the FLNa protein structure, dynamics and interactions by performing molecular dynamics (MD) simulations to examine the disease etiology and possible compensative mechanisms allowing survival of the males.ResultsWe observed that p.Arg484Gln disrupts the FLNa by altering its structural and dynamical properties including the flexibility of certain regions, interactions within the protein, and conformational landscape of FLNa. However, these impacts existed for only a part the MD trajectories and highly similar patterns observed in the other 12 mutations reported in the liveborn males validated this mechanism.ConclusionIt is concluded that the variants seen in the liveborn males result in transient pathogenic effects, rather than persistent impairments. By this way, the protein could retain its function occasionally and results in the survival of the males besides causing the disease.
| S-EPMC9132340 | biostudies-literature
Project description:The PAX6 gene encodes a highly-conserved transcription factor involved in eye development. Heterozygous loss-of-function variants in PAX6 can cause a range of ophthalmic disorders including aniridia. A key molecular diagnostic challenge is that many PAX6 missense changes are presently classified as variants of uncertain significance. While computational tools can be used to assess the effect of genetic alterations, the accuracy of their predictions varies. Here, we evaluated and optimised the performance of computational prediction tools in relation to PAX6 missense variants. Through inspection of publicly available resources (including HGMD, ClinVar, LOVD and gnomAD), we identified 241 PAX6 missense variants that were used for model training and evaluation. The performance of ten commonly used computational tools was assessed and a threshold optimization approach was utilized to determine optimal cut-off values. Validation studies were subsequently undertaken using PAX6 variants from a local database. AlphaMissense, SIFT4G and REVEL emerged as the best-performing predictors; the optimized thresholds of these tools were 0.967, 0.025, and 0.772, respectively. Combining the prediction from these top-three tools resulted in lower performance compared to using AlphaMissense alone. Tailoring the use of computational tools by employing optimized thresholds specific to PAX6 can enhance algorithmic performance. Our findings have implications for PAX6 variant interpretation in clinical settings.
| S-EPMC11292026 | biostudies-literature
Project description:Many variants of uncertain significance (VUS) have been identified in BRCA2 through clinical genetic testing. VUS pose a significant clinical challenge because the contribution of these variants to cancer risk has not been determined. We conducted a comprehensive assessment of VUS in the BRCA2 C-terminal DNA binding domain (DBD) by using a validated functional assay of BRCA2 homologous recombination (HR) DNA-repair activity and defined a classifier of variant pathogenicity. Among 139 variants evaluated, 54 had ?99% probability of pathogenicity, and 73 had ?95% probability of neutrality. Functional assay results were compared with predictions of variant pathogenicity from the Align-GVGD protein-sequence-based prediction algorithm, which has been used for variant classification. Relative to the HR assay, Align-GVGD significantly (p < 0.05) over-predicted pathogenic variants. We subsequently combined functional and Align-GVGD prediction results in a Bayesian hierarchical model (VarCall) to estimate the overall probability of pathogenicity for each VUS. In addition, to predict the effects of all other BRCA2 DBD variants and to prioritize variants for functional studies, we used the endoPhenotype-Optimized Sequence Ensemble (ePOSE) algorithm to train classifiers for BRCA2 variants by using data from the HR functional assay. Together, the results show that systematic functional assays in combination with in silico predictors of pathogenicity provide robust tools for clinical annotation of BRCA2 VUS.
| S-EPMC5985401 | biostudies-literature
Project description:The ATP-binding cassette transporter A1 (ABCA1) is a membrane-bound exporter protein involved in regulating serum HDL level by exporting cholesterol and phospholipids to load up in lipid-poor ApoA-I and ApoE, which allows the formation of nascent HDL. Mutations in the ABCA1 gene, when presents in both alleles, disrupt the canonical function of ABCA1, which associates with many disorders related to lipid transport. Although many studies have reported the phenotypic effects of a large number of ABCA1 variants, the pathological effect of non-synonymous polymorphisms (nsSNPs) in ABCA1 remains elusive. Therefore, aiming at exploring the structural and functional consequences of nsSNPs in ABCA1, in this study, we employed an integrated computational approach consisting of nine well-known in silico tools to identify damaging SNPs and molecular dynamics (MD) simulation to get insights into the magnitudes of the damaging effects. In silico tools revealed four nsSNPs as being most deleterious, where the two SNPs (G1050V and S1067C) are identified as the highly conserved and functional disrupting mutations located in the NBD1 domain. MD simulation suggested that both SNPs, G1050V and S1067C, changed the overall structural flexibility and dynamics of NBD1, and induced substantial alteration in the structural organization of ATP binding site. Taken together, these findings direct future studies to get more insights into the role of these variants in the loss of the ABCA1 function.
| S-EPMC7589834 | biostudies-literature
Project description:Assessing the significance of novel genetic variants revealed by DNA sequencing is a major challenge to the integration of genomic techniques with medical practice. Many variants remain difficult to classify by traditional genetic methods. Computational methods have been developed that could contribute to classifying these variants, but they have not been properly validated and are generally not considered mature enough to be used effectively in a clinical setting. We developed a computational method for predicting the effects of missense variants detected in patients with hypertrophic cardiomyopathy (HCM). We used a curated clinical data set of 74 missense variants in six genes associated with HCM to train and validate an automated predictor. The predictor is based on support vector regression and uses phylogenetic and structural features specific to genes involved in HCM. Ten-fold cross validation estimated our predictor's sensitivity at 94% (95% confidence interval: 83%-98%) and specificity at 89% (95% confidence interval: 72%-100%). This corresponds to an odds ratio of 10 for a prediction of pathogenic (95% confidence interval: 4.0-infinity), or an odds ratio of 9.9 for a prediction of benign (95% confidence interval: 4.6-21). Coverage (proportion of variants for which a prediction was made) was 57% (95% confidence interval: 49%-64%). This performance exceeds that of existing methods that are not specifically designed for HCM. The accuracy of this predictor provides support for the clinical use of automated predictions alongside family segregation and population frequency data in the interpretation of new missense variants and suggests future development of similar tools for other diseases.
| S-EPMC3035712 | biostudies-literature