LIST-S2

LIST-S2 predicts the deleteriousness of amino acid (missense) mutations in protein sequences from any organism by leveraging taxonomy distances and local sequence identity to assess evolutionary conservation.

Key Features:

• Taxonomy-Based Approach: Calculates taxonomy distances to weight conservation signals according to evolutionary relationships across taxa.
• Local Sequence Identity: Incorporates local sequence identity to quantify conservation around mutation sites.
• Cross-Species Applicability: Applies to protein sequences from diverse organisms rather than being limited to human sequences.
• Visualization Capabilities: Computes and provides visualizations of predicted deleteriousness for missense mutations in protein sequences.

Scientific Applications:

• Variant interpretation: Distinguishes deleterious from benign missense mutations to support variant pathogenicity assessment.
• Evolutionary and comparative genomics: Analyzes conservation patterns across taxa to inform evolutionary studies and comparative genomics.
• Personalized medicine: Prioritizes variants in clinical and research datasets to aid personalized medicine and genetic diagnosis.
• Disease mechanism and therapy development: Informs studies of disease mechanisms and selection of candidate variants for functional follow-up and targeted therapy research.

Methodology:

Calculates taxonomy distances and local sequence identity to assess protein sequence conservation and predict missense mutation deleteriousness.