Predicting deleterious amino acid substitutions

Genome Res. 2001 May;11(5):863-74. doi: 10.1101/gr.176601.


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.

Publication types

  • Comparative Study
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Amino Acid Sequence
  • Amino Acid Substitution / genetics*
  • Bacterial Proteins / classification
  • Bacterial Proteins / genetics
  • Bacterial Proteins / metabolism
  • Bacteriophage T4 / enzymology
  • Bacteriophage T4 / genetics
  • Computational Biology / methods*
  • Conserved Sequence
  • Escherichia coli Proteins*
  • Genetic Diseases, Inborn / genetics
  • HIV Protease / genetics
  • HIV-1 / enzymology
  • HIV-1 / genetics
  • Humans
  • Lac Repressors
  • Lactose / antagonists & inhibitors
  • Molecular Sequence Data
  • Muramidase
  • Mutation, Missense / genetics
  • Phenotype
  • Probability
  • Repressor Proteins / classification
  • Repressor Proteins / genetics
  • Repressor Proteins / metabolism
  • Sequence Alignment
  • Software


  • Bacterial Proteins
  • Escherichia coli Proteins
  • Lac Repressors
  • Repressor Proteins
  • Muramidase
  • HIV Protease
  • Lactose