LCD-Composer

LCD-Composer identifies and analyzes low-complexity domains (LCDs) in protein sequences to characterize amino-acid-enriched regions and support studies of their biophysical properties and biological roles.


Key Features:

  • Algorithm-Based Identification: An algorithm identifies LCDs primarily by assessing amino acid composition against defined thresholds.
  • Proteome-Wide Search: Searches entire proteomes using minimum composition thresholds for individual amino acids or groups of amino acids.
  • Sequence Similarity Search: Accepts known LCD sequences to find similar domains across different proteins.
  • Intramolecular Plotting: Searches for and visualizes LCDs within single protein structures.
  • Statistical Enrichment Testing: Tests for enrichment of LCDs within a user-provided set of proteins using statistical comparisons.
  • Multi-Type Identification: Identifies proteins that contain multiple distinct types of LCDs.

Scientific Applications:

  • Protein structure–function analysis: Characterizes how LCDs influence protein biophysical properties and functional behavior.
  • Evolutionary biology: Surveys LCD prevalence and composition across proteomes to support evolutionary and comparative studies.
  • Disease and pathology studies: Identifies LCDs potentially involved in pathological conditions for targeted investigation.

Methodology:

Algorithmic assessment of amino acid composition using user-defined minimum composition thresholds for individual amino acids or groups to identify LCDs.

Topics

Details

License:
GPL-3.0
Cost:
Free of charge
Tool Type:
command-line tool, web application
Operating Systems:
Mac, Linux, Windows
Programming Languages:
Python
Added:
12/27/2022
Last Updated:
11/24/2024

Operations

Publications

Cascarina SM, Ross ED. The LCD-Composer webserver: high-specificity identification and functional analysis of low-complexity domains in proteins. Bioinformatics. 2022;38(24):5446-5448. doi:10.1093/bioinformatics/btac699. PMID:36282522. PMCID:PMC9750097.

PMID: 36282522
PMCID: PMC9750097
Funding: - National Institute of General Medical Sciences: R35GM130352 - National Science Foundation: MCB-1817622

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