GlobPlot: exploring protein sequences for globularity and disorder

Linding, Rune; Russell, Robert B.; Neduva, Victor; Gibson, Toby J.

doi:10.1093/nar/gkg519

Cited by 917 publications

(822 citation statements)

References 35 publications

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“…FoldIndex and GlobPlot2.3 were used to assess the propensity to form secondary and tertiary structures (55,56). The default parameter for window size in FoldIndex was changed to 10 residues, to be comparable with GlobPlot2.3.…”

Section: Structure Assessmentmentioning

confidence: 99%

Modelling the structure of full-length Epstein–Barr virus nuclear antigen 1

2014

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Abstract:Epstein-Barr virus (EBV) is a clinically important human virus associated with several cancers and is the etiologic agent of infectious mononucleosis. The viral nuclear antigen-1 (EBNA1) is central to the replication and propagation of the viral genome and likely contributes to tumourigenesis. We have compared EBNA1 homologues from other primate lymphocryptoviruses (LCV) and found that the central glycine/alanine repeat (GAr) domain, as well as predicted cellular protein (USP7 and CK2) binding sites are present in homologues in the Old World primates, but not the marmoset; suggesting that these motifs may have co-evolved. Using the resolved structure of the C-terminal one third of EBNA1 (homodimerisation and DNA binding domain), we have gone on to develop monomeric and dimeric models in silico of the full length protein.The C-terminal domain is predicted to be structurally highly similar between homologues, indicating conserved function. Zinc could be stably incorporated into the model, bonding with two N-terminal cysteines predicted to facilitate multimerisation. The GAr contains secondary structural elements in the models, while the protein binding regions are unstructured, irrespective of the prediction approach used and sequence origin. These intrinsically disordered regions may facilitate the diversity observed in partner interactions. We hypothsise that the structured GAr could mask the disordered regions, thereby protecting the protein from default degradation. In the dimer conformation, the C-terminal tails of each monomer wrap around a proline-rich protruding loop of the partner monomer, providing dimer stability, a feature which could be exploited in therapeutic design. Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation EBV-B95-8 hu-EBNA1CyEBV-TsBB6 cy-EBNA1 CeHV15 rh-EBNA1CeHV12 ba-EBNA1 CalHV3 ma EBNA1Modelling the structure of full length Epstein-Barr Virus Nuclear Antigen Figure S2. EBNA1 model comparison.The EBV B95-8 EBNA1 sequence was input to I-TASSER, which selected the EBNA1 C-terminal domain crystal structure (1B3T) and several fragment templates comprising: yeast fatty acid synthetase (2PFF), a-L-fucosidase (2Z8X), photosynthetic reaction centre (1C51), type A collagen (1YOF) and dimeric 6-phosphoglucouronate dehydrogenase (2ZYD). The 1B3T template was also used to generate models in MOE. EBNA1 models constructed using I-TASSER and MOE (and the composite of these two generated in Modeller9v8 (shown above), were assessed for structural plausibility using Molprobity and QMEAN score servers (table S1). Models were superimposed over the template (1B3T) and RMSD was estimated for each. The qualitative model energy analysis, normalised (QMEANnorm) score of a protein structural model provides a composite scoring function based on several geometrical aspects, both global (for the entire structure) and local (per residue), enabling the discrimination of good and bad models. The human and other primate LCV EBNA1 protein structure models (as indicated) were ...

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Section: Structure Assessmentmentioning

confidence: 99%

Modelling the structure of full-length Epstein–Barr virus nuclear antigen 1

2014

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“…Assignment of the best repeats and registers, compilation of amino acid occupancies and charge pairs were performed with Perl scripts, coupled with manual intervention for the identification of register-shifts. We used the JNet secondary structure prediction method (Cuff et al, 1998), via the JPred web server, and the GLOBPLOT (Linding et al, 2003) tool for predicting disordered regions. Amino acid composition of domains was calculated with the COMPSEQ program of EMBOSS.…”

Section: Sequence Analysis Feature Predictions and Statisticsmentioning

confidence: 99%

A novel coiled-coil repeat variant in a class of bacterial cytoskeletal proteins

Walshaw

Gillespie

Kelemen

2010

Journal of Structural Biology

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a b s t r a c tIn recent years, a number of bacterial coiled-coil proteins have been characterised which have roles in cell growth and morphology. Several have been shown to have a cytoskeletal function and some have been proposed to have an IF-like character in particular. We recently demonstrated in Streptomyces coelicolor a cytoskeletal role of Scy, a large protein implicated in filamentous growth, whose sequence is dominated by an unusual coiled-coil repeat. We present a detailed analysis of this 51-residue repeat and conclude that it is likely to form a parallel dimeric non-canonical coiled coil based on hendecads but with regions of local underwinding reflecting highly periodic modifications in the sequence. We also demonstrate that traditional sequence similarity searching is insufficient to identify all but the close orthologues of such repeat-dominated proteins, but that by an analysis of repeat periodicity and composition, remote homologues can be found. One clear candidate, despite a great size discrepancy and unremarkable sequence identity, is the known filament-former FilP in the same species. Both proteins appear distinct from the archetypal bacterial IF-like protein; they therefore may constitute a new class of bacterial filamentous protein. The similar sequence characteristics of both suggest their likely oligomer state and a possible mechanism for higher-order assembly into filaments. Another remote homologue in Actinomyces was highlighted by this method. Further, a known coiled-coil protein, DivIVA, appears to share some of these sequence characteristics.

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“…Low complexity sequences were shown to be absent from globular regions of structured proteins in the Protein Data Bank (PDB) 18,23 . More recently, several other groups have developed predictors of disordered or similar regions [24][25][26][27] each of which has particular advantages.…”

Section: Introductionmentioning

confidence: 99%

“…As mentioned above, we combine both collapsed-disorder (molten globule-like) and extended-disorder (random coil-like) into a single disorder category, while others regard molten globules as partially folded and not in the natively unfolded category. Predictors of coil regions with high B-factors, called hot-loops, have also been developed 26,27 . Our studies showed that the amino acid compositions of high B-factor regions are distinct from those of disordered regions, and these distinctions were used to develop a predictor of high B -factor regions 28 .…”

Section: Introductionmentioning

confidence: 99%

Optimizing Long Intrinsic Disorder Predictors With Protein Evolutionary Information

Peng

Vučetić

Radivojac

et al. 2005

J. Bioinform. Comput. Biol.

468

428

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Protein existing as an ensemble of structures, called intrinsically disordered, has been shown to be res ponsible for a wide variety of biological functions and to be common in nature. Here we focus on improving sequence-based predictions of long (> 30 amino acid residues) regions lacking specific 3-D structure by means of four new neural -network-based Predictors Of Natural Disordered Regions (PONDRs): VL3, VL3H, VL3P, and VL3E. PONDR VL3 used several features from a previously introduced PONDR VL2, but benefitted from optimized predictor models and a slightly larger (152 versus 145) set of disordered proteins that were cleaned of mislabeling errors found in the smaller set. PONDR VL3H utilized homologues of the disordered proteins in the training stage, while PONDR VL3P used attributes derived from sequence profiles obtained by PSI-BLAST searches. The measure of accuracy was the average between accuracies on disordered and ordered protein regions. By this measure, the 30-fold cross-validation accuracies of VL3, VL3H, and VL3P were, respectively, 83.6±1.4%, 85.3±1.4%, and 85.2±1.5%. By combining VL3H and VL3P, t he resulting PONDR VL3E achieved an accuracy of 86.7±1.4%. This is a significant improvement over our previous PONDRs VLXT (71.6±1.3%) and VL2 (80.9±1.4% ). The new disorder predictors with the corresponding datasets are freely accessible through the web server at www.ist.temple.edu/disprot.

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GlobPlot: exploring protein sequences for globularity and disorder

Cited by 917 publications

References 35 publications

Modelling the structure of full-length Epstein–Barr virus nuclear antigen 1

Modelling the structure of full-length Epstein–Barr virus nuclear antigen 1

A novel coiled-coil repeat variant in a class of bacterial cytoskeletal proteins

Optimizing Long Intrinsic Disorder Predictors With Protein Evolutionary Information

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