mutation3D

mutation3D identifies spatial clusters of amino acid substitutions in tertiary protein structures to detect and prioritize cancer driver genes and to distinguish functional from nonfunctional mutations.

Key Features:

• 3D clustering approach: Employs a 3D clustering methodology to differentiate functional from nonfunctional mutations by grouping amino acid substitutions in protein tertiary structures.
• Structural mapping: Maps mutations onto crystal structures and homology models to evaluate the 3D arrangements of substitutions.
• Validation datasets: Validated using analyses of 8,869 known inherited disease mutations and 2,004 single nucleotide polymorphisms (SNPs) mapped to structural models.
• Cancer gene identification: Systematically analyzes whole-genome and whole-exome cancer datasets to identify established cancer genes and previously underexplored target genes.
• Somatic mutation compendium: Analyzes clusters derived from over 975,000 somatic mutations reported across 6,811 cancer sequencing studies.
• Functional implication assessment: Assesses potential functional implications of mutations by examining their spatial arrangements on protein structures.

Scientific Applications:

• Driver gene discovery: Detects spatial mutation clustering to aid identification and prioritization of cancer driver genes.
• Functional impact interpretation: Distinguishes functional versus nonfunctional mutations to inform understanding of protein function and disease mechanisms.
• Novel cancer gene identification: Reveals both known and previously underexplored cancer-associated genes to support studies of genetic underpinnings and therapeutic development.

Methodology:

Applies a 3D clustering algorithm to map amino acid substitutions onto tertiary protein structures (crystal structures and homology models) and systematically analyzes whole-genome and whole-exome cancer datasets, with validation using 8,869 inherited disease mutations, 2,004 SNPs, and analysis of over 975,000 somatic mutations from 6,811 cancer sequencing studies.