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