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Predicting Deleterious Amino Acid Substitutions

Genome Research · 2001 · Vol. 11(5) · pp. 863–874
Pauline C. NgSteven Henikoff

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 sorts intolerant from tolerant 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. may be used to identify plausible disease candidates among the SNPs that cause missense substitutions.

RNA and protein synthesis mechanismsGenomics and Phylogenetic StudiesBacterial Genetics and BiotechnologyBiologyMissense mutationGeneticsPhenotypeSingle-nucleotide polymorphismAmino acid substitutionMutagenesisSubstitution (logic)SNPSequence alignment

MeSH terms

Amino Acid SequenceBacterial ProteinsHumansLactoseMolecular Sequence DataMuramidasePhenotypeProbabilityRepressor ProteinsSoftwareHIV-1HIV ProteaseSequence AlignmentBacteriophage T4Conserved Sequence

Funding

  • National Science Foundation
  • U.S. Department of Energy
  • National Institutes of Health
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