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

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

Documentation

Links