ArticlePloS one2020
Assessing the low complexity of protein sequences via the low complexity triangle.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A benchmarking framework for comparative evaluation of low-complexity region detection tools in the human proteome.Scientific reports · 2026Article
- Article
- Terminal regions of a protein are a hotspot for low complexity regions and selection.Open biology · 2024Article
- Optimizing strategy for the discovery of compositionally-biased or low-complexity regions in proteins.Scientific reports · 2024Article
- Intrinsically Disordered Compositional Bias in Proteins: Sequence Traits, Region Clustering, and Generation of Hypothetical Functional Associations.Bioinformatics and biology insights · 2024Article
- Article
- The Role of Low Complexity Regions in Protein Interaction Modes: An Illustration in Huntingtin.International journal of molecular sciences · 2021Article
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2 authors.
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Abstract
backgroundProteins with low complexity regions (LCRs) have atypical sequence and structural features. Their amino acid composition varies from the expected, determined proteome-wise, and they do not follow the rules of structural folding that prevail in globular regions. One way to characterize these regions is by assessing the repeatability of a sequence, that is, calculating the local propensity of a region to be part of a repeat.
resultsWe combine two local measures of low complexity, repeatability (using the RES algorithm) and fraction of the most frequent amino acid, to evaluate different proteomes, datasets of protein regions with specific features, and individual cases of proteins with extreme compositions. We apply a representation called 'low complexity triangle' as a proof-of-concept to represent the low complexity measured values. Results show that proteomes have distinct signatures in the low complexity triangle, and that these signatures are associated to complexity features of the sequences. We developed a web tool called LCT (http://cbdm-01.zdv.uni-mainz.de/~munoz/lct/) to allow users to calculate the low complexity triangle of a given protein or region of interest.
conclusionsThe low complexity triangle proves to be a suitable procedure to represent the general low complexity of a sequence or protein dataset. Homorepeats, direpeats, compositionally biased regions and globular regions occupy characteristic positions in the triangle. The described pipeline can be used to characterize LCRs and may help in quantifying the content of degenerated tandem repeats in proteins and proteomes.
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