xProtCAS
xProtCAS identifies conserved accessible surfaces on protein structures to pinpoint interaction interfaces and infer functional and regulatory sites, including post-translational modification loci and regions affected by disease-associated mutations.
Key Features:
- Integration with AlphaFold2 Models: Uses structural models predicted by AlphaFold2 to analyze protein structures.
- Autonomous Structural Module Definition: Defines autonomous structural modules within predicted structures for localized analysis.
- Graph Representation of Modules: Transforms structural modules into graph representations that encode residue topology, accessibility, and conservation.
- Eigenvector Centrality-Based Approach: Applies an eigenvector centrality metric on module graphs to extract conserved surfaces and discriminate functional versus structural conservation constraints.
Scientific Applications:
- Protein Function Analysis: Identifies conserved accessible surfaces to support interpretation of protein function and regulation, including potential post-translational modification sites.
- Disease Mutation Impact Assessment: Highlights conserved surface regions that overlap disease-associated mutations to aid assessment of mutation impact.
- Proteome-wide Discovery: Enables application to the human proteome to reveal previously uncharacterized conserved surfaces, some containing clinically significant mutations.
Methodology:
Defines structural modules from AlphaFold2 models, converts modules into graphs encoding residue topology, accessibility, and conservation, and applies an eigenvector centrality-based method to identify conserved accessible surfaces and distinguish functional from structural conservation.
Topics
Details
- License:
- MIT
- Cost:
- Free of charge
- Tool Type:
- web application
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Python
- Added:
- 2/23/2024
- Last Updated:
- 11/24/2024
Operations
Publications
Kotb HM, Davey NE. xProtCAS: A Toolkit for Extracting Conserved Accessible Surfaces from Protein Structures. Biomolecules. 2023;13(6):906. doi:10.3390/biom13060906. PMID:37371487. PMCID:PMC10296640.