Sadic
Sadic calculates atom depth values for each atom in protein structures to characterize three-dimensional protein core composition and support studies of protein folding and stability.
Key Features:
- Atom depth calculation: Computes atom depth values for each atom within a protein structure to quantify burial and proximity to the molecular surface.
- Residue core/outer assignment: Establishes unambiguous criteria based on atom depth to assign amino acid residues to core or outer regions of proteins.
- Quantitative core characterization: Provides quantitative descriptions of protein cores in relation to structure and dynamics.
- Amino acid composition pattern definition: Defines specific patterns of amino acid composition within protein cores across different architectures.
- CATH database analysis: Analyzes solved protein structures from the CATH database to derive core composition patterns across folds.
- Amino acid network identification: Identifies unique amino acid networks that contribute to structural stability in various protein folds.
Scientific Applications:
- Protein folding studies: Supports investigation of protein folding mechanisms by providing atom-level core composition metrics.
- Protein engineering: Informs protein engineering efforts by quantifying core composition and residue burial to guide stability modifications.
- Structural stability analysis: Enables identification of amino acid networks and composition patterns that correlate with structural stability across folds.
- Comparative fold analysis: Facilitates comparison of core architectures and amino acid compositions across protein architectures from CATH.
- Structure–function relationships: Assists exploration of relationships between amino acid composition and protein architecture relevant to function and dynamics.
Methodology:
Calculates atom depth values per atom, applies atom-depth-based criteria to assign residues to core or outer regions, and analyzes solved protein structures from the CATH database to define amino acid composition patterns and identify stabilizing amino acid networks.
Topics
Details
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Python, C
- Added:
- 8/3/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Bottini S, Bernini A, De Chiara M, Garlaschelli D, Spiga O, Dioguardi M, Vannuccini E, Tramontano A, Niccolai N. ProCoCoA: A quantitative approach for analyzing protein core composition. Computational Biology and Chemistry. 2013;43:29-34. doi:10.1016/j.compbiolchem.2012.12.007. PMID:23333734.