SIFT

SIFT predicts the impact of amino acid substitutions on protein function by using sequence homology to classify missense variants as tolerated or deleterious.

Key Features:

• Sequence homology comparison: Compares the sequence of interest to a database of homologous sequences to assess whether amino acid changes are likely to affect protein function.
• Substitution classification: Classifies each amino acid substitution as tolerated or deleterious based on its predicted effect on protein functionality.
• Genome-wide prediction: Provides genome-wide prediction capabilities for coding variants.
• Indel analysis: Includes insertion/deletion (indel) analysis features for coding variants.
• Comparative accuracy: Demonstrates improved accuracy relative to traditional substitution scoring matrices in identifying substitutions that affect phenotypes.
• Variant prioritization: Prioritizes missense variants and SNPs for downstream functional studies to reduce experimental validation burden.

Scientific Applications:

• Missense variant interpretation: Predicting functional consequences of missense mutations in proteins.
• SNP prioritization and disease candidate identification: Prioritizing single nucleotide polymorphisms that cause missense substitutions as plausible disease candidates.
• Large-scale random mutagenesis analysis: Identifying deleterious substitutions in large-scale random mutagenesis projects.
• Genome-wide coding variant annotation: Annotating coding variants across genomes for research and variant interpretation.

Methodology:

Compares the sequence of interest to a database of homologous sequences to determine whether an amino acid change is likely to affect protein function. Classifies each substitution as tolerated or deleterious based on that comparison.