List of software to detect low complexity regions in proteins

Computational methods can study protein sequences to identify regions with low complexity, which can have particular properties regarding their function and structure.

NameLast updateUsageDescriptionOpen source?ReferenceSAPS1992downloadable / webIt describes several protein sequence statistics for the evaluation of distinctive characteristics of residue content and arrangement in primary structures.yesSEG1993downloadableIt is a two pass algorithm: first, identifies the LCR, and then performs local optimization by masking with Xs the LCRsyesfLPS2017downloadable / webIt can readily handle very large protein data sets, such as might come from metagenomics projects. It is useful in searching for proteins with similar CBRs and for making functional inferences about CBRs for a protein of interestyesCAST2000 downloadable (as geneCAST) webIt identifies LCRs using iterative steps of local dynamic programming search and masking against a database of homopolymeric protein sequences.yes SIMPLE2002 downloadable webIt facilitates the quantification of the amount of simple sequence in proteins and determines the type of short motifs that show clustering above a certain threshold.yesOj.py2001on requestA tool for demarcating low complexity protein domains.noDSR2003on requestIt calculates complexity using reciprocal complexity.noScanCom2003on requestCalculates the compositional complexity using the linguistic complexity measure.noCARD2005on requestBased on the complexity analysis of subsequences delimited by pairs of identical, repeating subsequences.noBIAS2006downloadable / webIt uses discrete scan statistics that provide a highly accurate multiple test correction to compute analytical estimates of the significance of each compositionally biased segment.yesGBA2006on requestA graph-based algorithm that constructs a graph of the sequence.noSubSeqer2008webA graph-based approach for the detection and identification of repetitive elements in low–complexity sequences.noANNIE2009webThis method creates an automation of the sequence analytic process.noLPS-annotate2011on requestThis algorithm defines compositional bias through a thorough search for lowest-probability subsequences (LPSs; Low Probability Sequences) and serves as workbench of tools now available to molecular biologists to generate hypotheses and inferences about the proteins that they are investigating.noLCReXXXplorer2015webA web platform to search, visualize and share data for low complexity regions in protein sequences. LCR-eXXXplorer offers tools for displaying LCRs from the UniProt/SwissProt knowledgebase, in combination with other relevant protein features, predicted or experimentally verified. Also, users may perform queries against a custom designed sequence/LCR-centric database.noXNU1993downloadableIt uses the PAM120 scoring matrix for the calculation of complexity.yesAlcoR2022downloadableA compression-based and alignment-free tool for detecting low-complexity regions in biological data (see: )yes

For a comprehensive review on the various methods and tools, see.

In addition, a web meta-server named PLAtform of TOols for LOw COmplexity (PlaToLoCo) has been developed, for visualization and annotation of low complexity regions in proteins. PlaToLoCo integrates and collects the output of five different state-of-the-art tools for discovering LCRs and provides functional annotations such as domain detection, transmembrane segment prediction, and calculation of amino acid frequencies. Furthermore, the union or intersection of the results of the search on a query sequence can be obtained.

A Neural Network webserver, named LCR-hound has been developed to predict the function of prokaryotic and eukaryotic LCRs, based on their amino acid or di-amino acid (bigram) content.

References