Computational prediction of functions of intrinsically disordered regions

Katuwawala, Akila; Ghadermarzi, Sina; Kurgan, Lukasz

doi:10.1016/bs.pmbts.2019.04.006

Cited by 35 publications

(24 citation statements)

References 127 publications

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“…We find that the underlying reason for this is the relatively poor ability of the current disorder predictors to identify ordered regions in the disordered protein-binding proteins, which, overall, have high amounts of disorder. The importance of this finding is motivated by the fact that disordered protein-binding proteins constitute a significant majority (66%) of the partner-annotated IDRs [94]. when compared to the set of generic disordered proteins, and by 0.04 and 0.07 when compared to the disordered nucleic-acid-binding proteins, respectively.…”

Section: Discussionmentioning

confidence: 99%

“…The six types of partners that interact with the IDRs are proteins, nucleic acids (DNA and RNAs), lipids, metals, inorganic salt and small molecules [41,108]. According to a recent analysis [94], the two most commonly annotated partners are proteins and nucleic acids. They collectively cover 84% of the partner-annotated IDRs in the DisProt resource.…”

Section: Surveys Of the Intrinsic Disorder Predictorsmentioning

confidence: 99%

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Comparative Assessment of Intrinsic Disorder Predictions with a Focus on Protein and Nucleic Acid-Binding Proteins

Katuwawala

Kurgan

2020

Biomolecules

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With over 60 disorder predictors, users need help navigating the predictor selection task. We review 28 surveys of disorder predictors, showing that only 11 include assessment of predictive performance. We identify and address a few drawbacks of these past surveys. To this end, we release a novel benchmark dataset with reduced similarity to the training sets of the considered predictors. We use this dataset to perform a first-of-its-kind comparative analysis that targets two large functional families of disordered proteins that interact with proteins and with nucleic acids. We show that limiting sequence similarity between the benchmark and the training datasets has a substantial impact on predictive performance. We also demonstrate that predictive quality is sensitive to the use of the well-annotated order and inclusion of the fully structured proteins in the benchmark datasets, both of which should be considered in future assessments. We identify three predictors that provide favorable results using the new benchmark set. While we find that VSL2B offers the most accurate and robust results overall, ESpritz-DisProt and SPOT-Disorder perform particularly well for disordered proteins. Moreover, we find that predictions for the disordered protein-binding proteins suffer low predictive quality compared to generic disordered proteins and the disordered nucleic acids-binding proteins. This can be explained by the high disorder content of the disordered protein-binding proteins, which makes it difficult for the current methods to accurately identify ordered regions in these proteins. This finding motivates the development of a new generation of methods that would target these difficult-to-predict disordered proteins. We also discuss resources that support users in collecting and identifying high-quality disorder predictions.

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Section: Discussionmentioning

confidence: 99%

Section: Surveys Of the Intrinsic Disorder Predictorsmentioning

confidence: 99%

Comparative Assessment of Intrinsic Disorder Predictions with a Focus on Protein and Nucleic Acid-Binding Proteins

Katuwawala

Kurgan

2020

Biomolecules

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“…There are over 70 disorder predictors and another 25 predictors of disorder function [28,29,[31][32][33]38]. It would be infeasible and unnecessary to develop a platform that provides access to all these tools.…”

Section: Selection Of Predictors For Inclusion Into the Depicter Websmentioning

confidence: 99%

“…Recent empirical studies have shown that some of these methods provide highly accurate predictions [34][35][36][37]. Moreover, two dozen computational tools that predict several functions of IDRs were published and released over the last decade [32,38,39]. These methods address sequence-based prediction of molecular partners that interact with IDRs, including proteins, DNA and RNAs, and a selected set of cellular functions, such as flexible linkers and moonlighting regions.…”

Section: Introductionmentioning

confidence: 99%

DEPICTER: Intrinsic Disorder and Disorder Function Prediction Server

Barik

Katuwawala

Hanson

et al. 2020

Journal of Molecular Biology

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…The peculiar sequence properties of IDPs have been exploited to predict protein disorder and have led to the development of numerous disorder predictors and/or metaservers [40][41][42][43][44]. Several databases gathering information about protein disorder have been developed in the last decade, including DisProt (the largest repository of manually curated intrinsically disordered regions-IDRs, for which disorder has been assessed experimentally) [9,45], MobiDB [46], DisBind [47], FuzDB [48], and Protein Ensemble Database [35,39].…”

Section: Introduction To Intrinsically Disordered Proteins (Idps)mentioning

confidence: 99%

Liquid–Liquid Phase Separation by Intrinsically Disordered Protein Regions of Viruses: Roles in Viral Life Cycle and Control of Virus–Host Interactions

Brocca

Grandori

Longhi

et al. 2020

IJMS

148

122

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Intrinsically disordered proteins (IDPs) are unable to adopt a unique 3D structure under physiological conditions and thus exist as highly dynamic conformational ensembles. IDPs are ubiquitous and widely spread in the protein realm. In the last decade, compelling experimental evidence has been gathered, pointing to the ability of IDPs and intrinsically disordered regions (IDRs) to undergo liquid–liquid phase separation (LLPS), a phenomenon driving the formation of membrane-less organelles (MLOs). These biological condensates play a critical role in the spatio-temporal organization of the cell, where they exert a multitude of key biological functions, ranging from transcriptional regulation and silencing to control of signal transduction networks. After introducing IDPs and LLPS, we herein survey available data on LLPS by IDPs/IDRs of viral origin and discuss their functional implications. We distinguish LLPS associated with viral replication and trafficking of viral components, from the LLPS-mediated interference of viruses with host cell functions. We discuss emerging evidence on the ability of plant virus proteins to interfere with the regulation of MLOs of the host and propose that bacteriophages can interfere with bacterial LLPS, as well. We conclude by discussing how LLPS could be targeted to treat phase separation-associated diseases, including viral infections.

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Computational prediction of functions of intrinsically disordered regions

Cited by 35 publications

References 127 publications

Comparative Assessment of Intrinsic Disorder Predictions with a Focus on Protein and Nucleic Acid-Binding Proteins

Comparative Assessment of Intrinsic Disorder Predictions with a Focus on Protein and Nucleic Acid-Binding Proteins

DEPICTER: Intrinsic Disorder and Disorder Function Prediction Server

Liquid–Liquid Phase Separation by Intrinsically Disordered Protein Regions of Viruses: Roles in Viral Life Cycle and Control of Virus–Host Interactions

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