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Predicting the Effects of Amino Acid Substitutions on Protein Function

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TLDR
An overview of amino acid substitution (AAS) prediction methods, which use sequence and/or structure to predict the effect of an AAS on protein function, and the utility of AAS prediction methods for Mendelian and complex diseases as well as their broader applications for understanding protein function.
Abstract
Nonsynonymous single nucleotide polymorphisms (nsSNPs) are coding variants that introduce amino acid changes in their corresponding proteins. Because nsSNPs can affect protein function, they are believed to have the largest impact on human health compared with SNPs in other regions of the genome. Therefore, it is important to distinguish those nsSNPs that affect protein function from those that are functionally neutral. Here we provide an overview of amino acid substitution (AAS) prediction methods, which use sequence and/or structure to predict the effect of an AAS on protein function. Most methods predict approximately 25–30% of human nsSNPs to negatively affect protein function, and such nsSNPs tend to be rare in the population. We discuss the utility of AAS prediction methods for Mendelian and complex diseases as well as their broader applications for understanding protein function.

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Journal ArticleDOI

Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm.

TL;DR: This protocol describes the use of the 'Sorting Tolerant From Intolerant' (SIFT) algorithm in predicting whether an AAS affects protein function.
Journal ArticleDOI

Predicting the Functional Effect of Amino Acid Substitutions and Indels

TL;DR: A new algorithm, PROVEAN (Protein Variation Effect Analyzer), is developed, which provides a generalized approach to predict the functional effects of protein sequence variations including single or multiple amino acid substitutions, and in-frame insertions and deletions.
Journal ArticleDOI

PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels

TL;DR: A web server to predict the functional effect of single or multiple amino acid substitutions, insertions and deletions using the prediction tool PROVEAN, which provides rapid analysis of protein variants from any organisms, and also supports high-throughput analysis for human and mouse variants at both the genomic and protein levels.
Journal ArticleDOI

Predicting the functional impact of protein mutations: application to cancer genomics

TL;DR: A new functional impact score (FIS) for amino acid residue changes using evolutionary conservation patterns is introduced, estimating that at least 5% of cancer-relevant mutations involve switch of function, rather than simply loss or gain of function.
Journal ArticleDOI

Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models.

TL;DR: The Functional Analysis Through Hidden Markov Models (FATHMM) software and server is described: a species‐independent method with optional species‐specific weightings for the prediction of the functional effects of protein missense variants, demonstrating that FATHMM can be efficiently applied to high‐throughput/large‐scale human and nonhuman genome sequencing projects with the added benefit of phenotypic outcome associations.
References
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Journal ArticleDOI

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Journal ArticleDOI

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Journal ArticleDOI

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