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Disentangling the complexity of low complexity proteins.

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cris.lastimport.scopus2024-02-12T20:44:33Z
dc.abstract.enThere are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, and more generally the overlaps between different properties related to LCRs, using examples. We argue that statistical measures alone cannot capture all structural aspects of LCRs and recommend the combined usage of a variety of predictive tools and measurements. While the methodologies available to study LCRs are already very advanced, we foresee that a more comprehensive annotation of sequences in the databases will enable the improvement of predictions and a better understanding of the evolution and the connection between structure and function of LCRs. This will require the use of standards for the generation and exchange of data describing all aspects of LCRs.
dc.affiliationUniwersytet Warszawski
dc.contributor.authorGruca, Aleksandra
dc.contributor.authorGrynberg, Marcin
dc.contributor.authorPlewczyński, Dariusz
dc.contributor.authorOuzounis, Christos A.
dc.contributor.authorPromponas, Vasilis J.
dc.contributor.authorKajava, Andrey V.
dc.contributor.authorAndrade-Navarro, Miguel A.
dc.contributor.authorMier, Pablo
dc.contributor.authorPaladin, Lisanna
dc.contributor.authorTamana, Stella
dc.contributor.authorPetrosian, Sophia
dc.contributor.authorHajdu-Soltész, Borbála
dc.contributor.authorUrbanek, Annika
dc.contributor.authorBernadó, Pau
dc.contributor.authorGáspári, Zoltán
dc.contributor.authorHancock, John M.
dc.contributor.authorTosatto, Silvio C. E.
dc.contributor.authorDosztanyi, Zsuzsanna
dc.date.accessioned2024-01-24T21:55:09Z
dc.date.available2024-01-24T21:55:09Z
dc.date.copyright2019-01-30
dc.date.issued2019
dc.description.accesstimeBEFORE_PUBLICATION
dc.description.financeNie dotyczy
dc.description.number2
dc.description.versionFINAL_PUBLISHED
dc.description.volume21
dc.identifier.doi10.1093/BIB/BBZ007
dc.identifier.issn1467-5463
dc.identifier.urihttps://repozytorium.uw.edu.pl//handle/item/104999
dc.identifier.weblinkhttps://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbz007/5299744
dc.languageeng
dc.pbn.affiliationbiological sciences
dc.relation.ispartofBriefings in Bioinformatics
dc.relation.pages458-472
dc.rightsCC-BY-NC
dc.sciencecloudnosend
dc.subject.enlow complexity regions
dc.subject.encomposition bias
dc.subject.enstructure
dc.subject.endisorder
dc.titleDisentangling the complexity of low complexity proteins.
dc.typeJournalArticle
dspace.entity.typePublication