PAT
PAT identifies structured units within protein sequences to define optimized domain boundaries and detect putative non-domain folded regions for biochemical studies and synthetic antibody target selection.
Key Features:
- Domain Identification: Locates structural domains within protein sequences and optimizes their boundaries for improved accuracy.
- Non-Domain Structured Units: Detects putative structured units that do not conform to traditional domain definitions.
- Structural Property Analysis: Analyzes structural properties and evaluates folding stability to characterize potential secondary and tertiary structures.
- Performance Superiority: Defines reliable domain boundaries and characterizes structurally well-defined regions with higher accuracy than existing methods.
Scientific Applications:
- Antibody Target Identification: Identifies soluble and well-defined secondary and tertiary structures as candidate targets for synthetic antibody generation.
- Experimental Validation: Has identified experimentally confirmed antibody targets, supporting its applicability in experimental workflows.
Methodology:
Integrates analytical approaches to assess structural properties and folding stability and provides pre-calculated results for 20,210 human proteins.
Topics
Details
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Python
- Added:
- 8/3/2017
- Last Updated:
- 12/10/2018
Operations
Data Inputs & Outputs
Protein structure prediction
Inputs
Outputs
Publications
Jeon J, et al. PAT: predictor for structured units and its application for the optimization of target molecules for the generation of synthetic antibodies. BMC Bioinformatics. 2016; 17:150. doi: 10.1186/s12859-016-1001-1
PMID: 27039071