PONDR-FIT: A meta-predictor of intrinsically disordered amino acids

Xue, Bin; Dunbrack, Roland L.; Williams, Robert W.; Dunker, A. Keith; Uversky, Vladimir N.

doi:10.1016/j.bbapap.2010.01.011

Cited by 1,058 publications

(1,035 citation statements)

References 90 publications

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“…Several programs for identification of intrinsically disordered regions in IDPs are available on the web. The H.8 epitope of Laz was predicted to be intrinsically disordered by all the typical programs, PONDR-FIT, 30 DISOPRED 2,31 and DisEMBL 32 (Figs. 1 and 6).…”

Section: Discussionmentioning

confidence: 99%

Structural studies on Laz, a promiscuous anticancer Neisserial protein

et al. 2015

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Azurin and Laz (lipidated azurin) are 2 bacterial proteins with anticancer, anti-viral and anti-parasitic activities. Azurin, isolated from the bacterium Pseudomonas aeruginosa, termed Paz, demonstrates anticancer activity against a range of cancers but not against brain tumors. In contrast, Laz is produced by members of Gonococci/Meningococci, including Neisseria meningitides which can cross the blood-brain barrier to infect brain meninges. It has been previously reported that Laz has an additional 39 amino acid moiety, called an H.8 epitope, in the N-terminal part of the azurin moiety that allows Laz to cross the entry barrier to brain tumors such as glioblastomas. Exactly, how the H.8 epitope helps the azurin moiety of Laz to cross the entry barriers to attack glioblastoma cells is unknown. In this paper, we describe the structural features of the H.8 moiety in Laz using X-ray crystallography and demonstrate that while the azurin moiety of Laz adopts a b-sandwich fold with 2 b-sheets arranged in the Greek key motif, the H.8 epitope was present as a disordered structure outside the Greek key motif. Structures of Paz and H.8 epitope-deficient Laz are well superimposed. The structural flexibility of the H.8 motif in Laz explains the extracellular location of Laz in Neisseria where it can bind the key components of brain tumor cells to disrupt their tight junctions and allow entry of Laz inside the tumors to exert cytotoxicity.

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Section: Discussionmentioning

confidence: 99%

Structural studies on Laz, a promiscuous anticancer Neisserial protein

et al. 2015

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“…Additional protein motifs relevant for protein function described in the literature but not included in these databases were also identified. The putative presence of intrinsically disordered regions across the D. melanogaster proteins was analyzed with the PONDR-FIT predictor (Xue et al, 2010) available at http://www.disprot.org.…”

Section: Divergence Analysismentioning

confidence: 99%

Adaptive selection and coevolution at the proteins of the Polycomb repressive complexes in Drosophila

et al. 2015

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JM Calvo-Martín, P Librado, M Aguadé, M Papaceit and C Segarra Polycomb group (PcG) proteins are important epigenetic regulatory proteins that modulate the chromatin state through posttranslational histone modifications. These interacting proteins form multimeric complexes that repress gene expression. Thus, PcG proteins are expected to evolve coordinately, which might be reflected in their phylogenetic trees by concordant episodes of positive selection and by a correlation in evolutionary rates. In order to detect these signals of coevolution, the molecular evolution of 17 genes encoding the subunits of five Polycomb repressive complexes has been analyzed in the Drosophila genus. The observed distribution of divergence differs substantially among and along proteins. Indeed, CAF1 is uniformly conserved, whereas only the established protein domains are conserved in other proteins, such as PHO, PHOL, PSC, PH-P and ASX. Moreover, regions with a low divergence not yet described as protein domains are present, for instance, in SFMBT and SU(Z)12. Maximum likelihood methods indicate an acceleration in the nonsynonymous substitution rate at the lineage ancestral to the obscura group species in most genes encoding subunits of the Pcl-PRC2 complex and in genes Sfmbt, Psc and Kdm2. These methods also allow inferring the action of positive selection in this lineage at genes E(z) and Sfmbt. Finally, the protein interaction network predicted from the complete proteomes of 12 Drosophila species using a coevolutionary approach shows two tight PcG clusters. These clusters include well-established binary interactions among PcG proteins as well as new putative interactions.

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“…Prediction of different features of protein structure like secondary structures (Jones, 1999;Madera et al, 2010;Pollastri et al, 2002), protein disorder (Madera et al, 2010;Xue et al, 2010), transmembrane regions (Illergard et al, 2010;Pylouster et al, 2010), phosphorylation sites (Biswas et al, 2010), protein flexibility (Bornot et al, 2011) or the generation of structural models (de Brevern, 2010;Kelley and Sternberg, 2009), are mainly based on machine learning algorithms (Brylinski and Skolnick, 2008;Rangwala et al, 2009;Xu et al, 2008). Protein structure analyses and prediction methods derive information from non-redundant databanks that represent the state-of-the-art of available data (i.e., solved protein structures).…”

Section: Introductionmentioning

confidence: 99%

Species specific amino acid sequence–protein local structure relationships: An analysis in the light of a structural alphabet

Brevern

Joseph

2011

Journal of Theoretical Biology

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To cite this version:Alexandre De Brevern, Agnel Praveen Joseph. Species specific amino acid sequence-protein local structure relationships: An analysis in the light of a structural alphabet.: species sequence -structure relationship. Journal of Theoretical Biology, Elsevier, 2011, 276 (1) AbstractProtein structure analysis and prediction methods are based on non-redundant data extracted from the available protein structures, regardless of the species from which the protein originates. Hence, these datasets represent the global knowledge on protein folds, which constitutes a generic distribution of amino acid sequence -protein structure (AAS-PS) relationships. In this study, we try to elucidate whether the AAS-PS relationship could possess specificities depending on the specie.For this purpose, we have chosen three different species: Saccharomyces cerevisiae, Plasmodium falciparum and Arabidopsis thaliana. We analyzed the AAS-PS behaviors of the proteins from these three species and compared it to the "expected" distribution of a classical non-redundant databank. With the classical secondary structure description, only slight differences in amino acid preferences could be observed. With a more precise description of local protein structures (Protein Blocks), significant changes could be highlighted.Saccharomyces cerevisiae's AAS-PS relationship is close to the general distribution, while striking differences are observed in the case of Arabidopsis thaliana. Plasmodium falciparum is the most distant one.This study presents some interesting view-points on AAS-PS relationship. Certain species exhibit unique preferences for amino acids to be associated with protein local structural elements. Thus, AAS-PS relationships are species dependant. These results can give useful insights for improving prediction methodologies which take the species specific information into account.

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PONDR-FIT: A meta-predictor of intrinsically disordered amino acids

Cited by 1,058 publications

References 90 publications

Structural studies on Laz, a promiscuous anticancer Neisserial protein

Structural studies on Laz, a promiscuous anticancer Neisserial protein

Adaptive selection and coevolution at the proteins of the Polycomb repressive complexes in Drosophila

Species specific amino acid sequence–protein local structure relationships: An analysis in the light of a structural alphabet

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