Predicting Deleterious Amino Acid Substitutions
Author(s) -
Pauline C. Ng,
Steven Henikoff
Publication year - 2001
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.176601
Subject(s) - biology , missense mutation , genetics , phenotype , single nucleotide polymorphism , amino acid substitution , mutagenesis , substitution (logic) , snp , sequence alignment , computational biology , mutation , peptide sequence , gene , genotype , computer science , programming language
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.
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