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Title: LCD-Composer: an intuitive, composition-centric method enabling the identification and detailed functional mapping of low-complexity domains
Abstract Low complexity domains (LCDs) in proteins are regions predominantly composed of a small subset of the possible amino acids. LCDs are involved in a variety of normal and pathological processes across all domains of life. Existing methods define LCDs using information-theoretical complexity thresholds, sequence alignment with repetitive regions, or statistical overrepresentation of amino acids relative to whole-proteome frequencies. While these methods have proven valuable, they are all indirectly quantifying amino acid composition, which is the fundamental and biologically-relevant feature related to protein sequence complexity. Here, we present a new computational tool, LCD-Composer, that directly identifies LCDs based on amino acid composition and linear amino acid dispersion. Using LCD-Composer's default parameters, we identified simple LCDs across all organisms available through UniProt and provide the resulting data in an accessible form as a resource. Furthermore, we describe large-scale differences between organisms from different domains of life and explore organisms with extreme LCD content for different LCD classes. Finally, we illustrate the versatility and specificity achievable with LCD-Composer by identifying diverse classes of LCDs using both simple and multifaceted composition criteria. We demonstrate that the ability to dissect LCDs based on these multifaceted criteria enhances the functional mapping and classification of LCDs.  more » « less
Award ID(s):
1817622
NSF-PAR ID:
10257354
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
NAR Genomics and Bioinformatics
Volume:
3
Issue:
2
ISSN:
2631-9268
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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    Low-complexity domains (LCDs) in proteins are regions enriched in a small subset of amino acids. LCDs exist in all domains of life, often have unusual biophysical behavior, and function in both normal and pathological processes. We recently developed an algorithm to identify LCDs based predominantly on amino acid composition thresholds. Here, we have integrated this algorithm with a webserver and augmented it with additional analysis options. Specifically, users can (i) search for LCDs in whole proteomes by setting minimum composition thresholds for individual or grouped amino acids, (ii) submit a known LCD sequence to search for similar LCDs, (iii) search for and plot LCDs within a single protein, (iv) statistically test for enrichment of LCDs within a user-provided protein set and (v) specifically identify proteins with multiple types of LCDs.

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