Abstract
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 substitutions predicted to be deleterious by substitution scoring matrices in three test cases. Using SIFT 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.
Keywords
BiologyMissense mutationGeneticsPhenotypeSingle-nucleotide polymorphismAmino acid substitutionMutagenesisSubstitution (logic)SNPSequence alignmentComputational biologyMutationPeptide sequenceGeneGenotype
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Publication Info
- Year
- 2001
- Type
- article
- Volume
- 11
- Issue
- 5
- Pages
- 863-874
- Citations
- 2643
- Access
- Closed
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Cite This
Pauline C. Ng,
Steven Henikoff
(2001).
Predicting Deleterious Amino Acid Substitutions.
Genome Research
, 11
(5)
, 863-874.
https://doi.org/10.1101/gr.176601
Identifiers
- DOI
- 10.1101/gr.176601