Structure-PPi
Structure-PPi annotates cancer-related germline and somatic genetic variants on three-dimensional protein structures, emphasizing protein–protein interaction interfaces to assess variant functional and structural impact.
Key Features:
- Integration of Omics Data: Integrates NGS-derived omics data to analyze germline and somatic variants in the context of cancer.
- Utilization of Public Databases: Leverages annotations from Interactome3D, UniProtKB, InterPro, APPRIS, dbNSFP, and COSMIC to supply structural and variant-level information.
- Focus on Protein Interaction Interfaces: Annotates variants located at protein–protein interaction interfaces within three-dimensional structures.
- Functional Site Analysis: Reports variant occurrences in catalytic regions, ligand-binding domains, and posttranslational modification sites.
- Complementary Pathogenicity Insights: Provides contextual information that complements pathogenicity prediction methods and assists in distinguishing false-positive predictions.
- Mechanistic and Biological Insights: Offers mechanistic interpretations of how variants may impact protein function and interaction networks relevant to cancer.
Scientific Applications:
- Cancer variant interpretation: Mapping and interpreting structural implications of germline and somatic variants for cancer research.
- Variant prioritization and classification: Contextualizing pathogenicity predictions to refine variant classification and prioritize candidates for functional follow-up.
Methodology:
Structure-PPi extracts features and annotations from Interactome3D, UniProtKB, InterPro, APPRIS, dbNSFP, and COSMIC and maps NGS-derived variant data onto three-dimensional protein structures and annotated functional sites.
Topics
Details
- Cost:
- Free of charge
- Tool Type:
- web application
- Operating Systems:
- Mac, Linux, Windows
- Added:
- 9/1/2022
- Last Updated:
- 11/24/2024
Operations
Publications
Vazquez M, Pons T. Annotating Cancer-Related Variants at Protein–Protein Interface with Structure-PPi. Methods in Molecular Biology. 2022. doi:10.1007/978-1-0716-2293-3_20. PMID:35751824.
PMID: 35751824