Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm

Kumar, Prateek; Henikoff, Steven; Ng, Pauline C

doi:10.1038/nprot.2009.86

Cited by 6,521Genomics and Rare DiseasesGenomics and Phylogenetic StudiesGenetic Associations and Epidemiology

Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm

Kumar, Prateek, Henikoff, Steven, Ng, Pauline C·2009·Nature Protocols

DOI 10.1038/nprot.2009.86

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Abstract

The effect of genetic mutation on phenotype is of significant interest in genetics. The type of genetic mutation that causes a single amino acid substitution (AAS) in a protein sequence is called a non-synonymous single nucleotide polymorphism (nsSNP). An nsSNP could potentially affect the function of the protein, subsequently altering the carrier's phenotype. This protocol describes the use of the 'Sorting Tolerant From Intolerant' (SIFT) algorithm in predicting whether an AAS affects protein function. To assess the effect of a substitution, SIFT assumes that important positions in a protein sequence have been conserved throughout evolution and therefore substitutions at these positions may affect protein function. Thus, by using sequence homology, SIFT predicts the effects of all possible substitutions at each position in the protein sequence. The protocol typically takes 5-20 min, depending on the input. SIFT is available as an online tool (http://sift.jcvi.org).

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Some of the more commonly used in-silico tools for missense variant interpretation in clinical laboratories include PolyPhen2, SIFT and MutationTaster.
“Some of the more commonly used in-silico tools for missense variant interpretation in clinical laboratories include PolyPhen2 19 , SIFT 20 and MutationTaster 21 .”
From Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (2015) · cites this paper as [20]

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Authors: Kumar, P., Henikoff, S., & Ng, P. C.
Affiliations: J. Craig Venter Institute (US)
Howard Hughes Medical Institute (US)
Corresponding author: Ng, Pauline C
ORCID: Henikoff, Steven
Ng, Pauline C
Venue: Nature Protocols
Publisher: Springer Science and Business Media LLC
Published: 2009-06-25
Volume: 4
Issue: 7
Pages: 1073-1081
ISSN: 1750-2799 (ISSN-L)
1754-2189
DOI: 10.1038/nprot.2009.86
OpenAlex: W1980740976
Cited by: 6,521
References: 1
Citations by year: 2026: 116 · 2025: 172 · 2024: 275 · 2023: 260 · 2022: 353 · 2021: 415 · 2020: 471 · 2019: 555 · 2018: 636 · 2017: 606 · 2016: 638 · 2015: 612 · 2014: 495 · 2013: 428 · 2012: 279
FWCI: 94.57
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
www.springer.com/tdm (vor)
Locations: Nature Protocols (publishedVersion)
PubMed (publishedVersion)
Funders: Menzies School of Health Research
National Human Genome Research Institute (R01HG004701)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords: SIFT algorithm, non-synonymous single nucleotide polymorphisms, amino acid substitutions, protein function prediction, sequence conservation, sequence homology, genetic mutations
MeSH terms: Algorithms, Amino Acid Sequence, Computer Simulation, Molecular Sequence Data, Phenotype, Proteins, Software, Amino Acid Substitution, Internet

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Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm

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