Congruency in the prediction of pathogenic missense mutations: state-of-the-art web-based tools

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Deep sequencing initiatives are identified a remarkable quantity of single nucleotide polymorphisms yet only approximately half are nonsynonymous amino acid substitutions that could potentially affect protein function. A confusing array of tools are available to help identify the few gene-coding variants that actually cause or confer susceptibility to disease. In this brief, Castellana and Mazza

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Sequence variation in G-protein-coupled receptors: analysis of single nucleotide polymorphisms

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G-protein-coupled receptors (GPCRs) play an important role in many physiological processes such as signal transduction and are frequently the targets for the majority of prescription drugs such as beta-blockers and anti-histamines. Understanding the role of sequence variations such as SNPs in GPCRs has potential implications for elucidating disease pathogenesis mechanisms and drug efficacy issues. In

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Prediction of Missense Mutation Functionality Depends on Both the Algorithm and Sequence Alignment Employed

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A number of algorithms have been developed to predict the impact of missense mutations on protein structure and function using sequence and structure-based approaches, notably SIFT, PolyPhen-2, Xvar, and Align-GVGD. In this study, Hicks et al. demonstrate that accurately predicting the impact of missense mutations on protein function depends on the algorithm used, the type

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