Predicting deleterious amino acid substitutions

PC Ng, S Henikoff - Genome research, 2001 - genome.cshlp.org
PC Ng, S Henikoff
Genome research, 2001genome.cshlp.org
Many missense substitutions are identified in single nucleotide polymorphism (SNP) data
and large-scale random mutagenesis projects. Each amino acid substitution potentially
affects protein function. We have constructed a tool that uses sequence homology to predict
whether a substitution affects protein function. SIFT, which s orts i ntolerant f rom t olerant
substitutions, classifies substitutions as tolerated or deleterious. A higher proportion of
substitutions predicted to be deleterious by SIFT gives an affected phenotype than …
Many missense substitutions are identified in single nucleotide polymorphism (SNP) data and large-scale random mutagenesis projects. Each amino acid substitution potentially affects protein function. We have constructed a tool that uses sequence homology to predict whether a substitution affects protein function. SIFT, whichsorts intolerant fromtolerant substitutions, classifies substitutions as tolerated or deleterious. A higher proportion of substitutions predicted to be deleterious by SIFT gives an affected phenotype than substitutions predicted to be deleterious by substitution scoring matrices in three test cases. UsingSIFT before mutagenesis studies could reduce the number of functional assays required and yield a higher proportion of affected phenotypes. SIFT may be used to identify plausible disease candidates among the SNPs that cause missense substitutions.
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