Functional Analysis of Human Hub Proteins and Their Interactors Involved in the Intrinsic Disorder-Enriched Interactions

Hu, Gang; Wu, Zhonghua; Uversky, Vladimir N.; Kurgan, Lukasz

doi:10.3390/ijms18122761

Cited by 87 publications

(62 citation statements)

References 284 publications

(406 reference statements)

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“…85,86 In conjunction, proteins with the most disorder are associated with hub positions in cancer-associated protein-protein interaction networks. 19,46 The combination of these two IDR aspects may explain why mucins can bind with and activate a great number of surface receptors, 87 signaling molecules, 3 and transcription factors. 88,89 It is known that protein-protein interactions involving IDPs are influenced by molecular recognition features (MoRFs).…”

Section: Discussionmentioning

confidence: 99%

“…In addition to splice events, numerous structural modifications of mucins drive protein-protein interactions which serve as a key to their oncogenic role in cancer progression. 97 The flexibility of IDRs facilitates access to enzymes involved in PTM 19 and the ability of an IDR to interact with target proteins is dramatically altered by the presence of these PTMs. 94 Our findings show a high degree of overlap between the PhosphoSitePlus curated phosphorylation sites found in D 2 P 2 and IDRs, throughout the mucin protein family.…”

Section: Discussionmentioning

confidence: 99%

“…16 However, it is now well established that intrinsically disordered proteins (IDPs) and regions (IDRs) are complete proteins (or segments of proteins) that lack a traditional globular secondary or tertiary structure, yet are fully functional. [17][18][19][20][21][22] Disordered regions generally are sequences of low complexity with a low proportion of hydrophobic residues and a high number of repeating residues with a preponderance of polar and charged residues. 23,24 This lack of bulky hydrophobic amino acids prevents the formation of an ordered core that comprises a traditional structured domain.…”

Section: Intrinsically Disordered Proteinsmentioning

confidence: 99%

“…A study estimated that 30% of all proteins harbor some degree of disorder with a majority of these proteins containing disorder ranging between 20% and 40% of their total sequence. [25][26][27] IDPs/IDRs have wide-ranging implications in various physiological and biological processes such as transcription, splicing, translation, signaling, 20,28-31 scaffolding, 32,33 cell cycle regulation, [34][35][36] protein-protein interactions (PPIs), 19,[37][38][39][40][41] chaperoning, 17 and phenotypic plasticity 42,43 (that is the ability to switch phenotypes). Further, IDP/IDR-mediated modulations are implicated in the pathogenesis of various diseases such as cancer, diabetes, cardiovascular defects, amyloidosis, and neurodegeneration.…”

Section: Intrinsically Disordered Proteinsmentioning

confidence: 99%

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Presence and structure‐activity relationship of intrinsically disordered regions across mucins

et al. 2020

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Abbreviations: AMOP, adhesion-associated domain in MUC4 and other proteins domain; CH, charge hydropathy; D 2 P 2 , database of disordered protein predictions; ECM, extracellular matrix; EGF, epidermal growth factor-like domain; IDP, intrinsically disordered protein; IDR, intrinsically disordered region; MoRF, molecular recognition feature; NIDO, nidogen-like domain; PPI, protein-protein interaction; PTM, posttranslational modification; PTS sequence, proline, threonine and serine sequence; SEA, sea-urchin sperm protein enterokinase and agrin module; TM, transmembrane; VNTR, variable number of tandem repeat domain; vWD, von Willebrand factor D domain. AbstractMany members of the mucin family are evolutionarily conserved and are often aberrantly expressed and glycosylated in various benign and malignant pathologies leading to tumor invasion, metastasis, and immune evasion. The large size and extensive glycosylation present challenges to study the mucin structure using traditional methods, including crystallography. We offer the hypothesis that the functional versatility of mucins may be attributed to the presence of intrinsically disordered regions (IDRs) that provide dynamism and flexibility and that the IDRs offer potential therapeutic targets. Herein, we examined the links between the mucin structure and function based on IDRs, posttranslational modifications (PTMs), and potential impact on their interactome. Using sequence-based bioinformatics tools, we observed that mucins are predicted to be moderately (20%-40%) to highly (>40%) disordered and many conserved mucin domains could be disordered. Phosphorylation sites overlap with IDRs throughout the mucin sequences. Additionally, the majority of predicted O-and N-glycosylation sites in the tandem repeat regions occur within IDRs and these IDRs contain a large number of functional motifs, that is, molecular recognition features (MoRFs), which directly influence protein-protein interactions (PPIs).This investigation provides a novel perspective and offers an insight into the complexity and dynamic nature of mucins. K E Y W O R D Sintrinsically disordered protein, glycoprotein, protein-protein interaction, protein structure 1940 | CARMICHEAL Et AL.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Intrinsically Disordered Proteinsmentioning

confidence: 99%

Section: Intrinsically Disordered Proteinsmentioning

confidence: 99%

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Presence and structure‐activity relationship of intrinsically disordered regions across mucins

et al. 2020

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“…According to some estimates around 20% of residues in Eukaryotic proteins are disordered and about half of human proteins have at least one long (>30 consecutives residues) IDR . Proteins with IDRs carry out numerous functions that rely on protein–protein and protein–nucleic acids interactions (eg, translation, transcription, and chromosome condensation), are involved in a variety of signaling functions, and facilitate regulation of protein functions via posttranslational modifications . Substantial efforts have been made to predict and computationally characterize IDRs .…”

Section: Introductionmentioning

confidence: 99%

High‐throughput prediction of disordered moonlighting regions in protein sequences

Meng

Kurgan

2018

Proteins

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Intrinsically disordered regions lack stable structure in their native conformation but are nevertheless functional and highly abundant, particularly in Eukaryotes. Disordered moonlighting regions (DMRs) are intrinsically disordered regions that carry out multiple functions. DMRs are different from moonlighting proteins that could be structured and that are annotated at the whole-protein level. DMRs cannot be identified by current predictors of functions of disorder that focus on specific functions rather than multifunctional regions. We conceptualized, designed and empirically assessed first-of-its-kind sequence-based predictor of DMRs, DMRpred. This computational tool outputs propensity for being in a DMR for each residue in an input protein sequence. We developed novel amino acid indices that quantify propensities for functions relevant to DMRs and used evolutionary conservation, putative solvent accessibility and intrinsic disorder derived from the input sequence to build a rich profile that is suitable to accurately predict DMRs. We processed this profile to derive innovative features that we input into a Random Forest model to generate the predictions. Empirical assessment shows that DMRpred generates accurate predictions with area under receiver operating characteristic curve = 0.86 and accuracy = 82%. These results are significantly better than the closest alternative approaches that rely on sequence alignment, evolutionary conservation and putative disorder and disorder functions. Analysis of abundance of putative DMRs in the human proteome reveals that as many as 25% of proteins may have long >30 residues) DMRs. A webserver implementation of DMRpred is available at http://biomine.cs.vcu.edu/servers/DMRpred/.

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Overview Update: Computational Prediction of Intrinsic Disorder in Proteins

Uversky

Kurgan

2023

Current Protocols

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There are over 100 computational predictors of intrinsic disorder. These methods predict amino acid-level propensities for disorder directly from protein sequences. The propensities can be used to annotate putative disordered residues and regions. This unit provides a practical and holistic introduction to the sequence-based intrinsic disorder prediction. We define intrinsic disorder, explain the format of computational prediction of disorder, and identify and describe several accurate predictors. We also introduce recently released databases of intrinsic disorder predictions and use an illustrative example to provide insights into how predictions should be interpreted and combined. Lastly, we summarize key experimental methods that can be used to validate computational predictions.

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Functional Analysis of Human Hub Proteins and Their Interactors Involved in the Intrinsic Disorder-Enriched Interactions

Cited by 87 publications

References 284 publications

Presence and structure‐activity relationship of intrinsically disordered regions across mucins

Presence and structure‐activity relationship of intrinsically disordered regions across mucins

High‐throughput prediction of disordered moonlighting regions in protein sequences

Overview Update: Computational Prediction of Intrinsic Disorder in Proteins

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