Tyrosine Regulates β‑Sheet Structure Formation in Amyloid‑β₄₂: A New Clustering Algorithm for Disordered Proteins

Our recent studies show that the single Tyr residue in the sequence of amyloid-β₄₂ (Aβ₄₂) is reactive toward various ligands, including metals and adenosine trisphospate (see: Coskuner, O. J. Biol. Inorg. Chem. 2016 21, 957–973 and Coskuner, O.; Murray, I. V. J. J. Alzheimer’s Dis. 2014 41, 561–574). However, the exact role of Tyr in the structures of Aβ₄₂ remains unknown. To fill this gap, here we analyzed the role of Tyr and the impact of the Tyr10Ala mutation on the structural ensemble of Aβ₄₂. β-Sheet formation in the structural ensemble of Aβ₄₂ is directly associated with the reactivity of this peptide toward ligand–receptor interactions, including self-assembly. On the basis of our findings, Tyr plays a crucial role in β-sheet emergence in the structures of Aβ₄₂, and the Tyr10Ala mutation greatly suppresses or diminishes β-sheet formation in the overall structures of monomeric Aβ₄₂. A new strategy for predicting the degree of stability and an “order in disorder” algorithm using secondary structure properties and thermodynamics were developed and applied for the Tyr10Ala mutant and wild-type Aβ₄₂ analysis. This new clustering algorithm may help in selecting disordered protein structure ensembles for drug design studies. Tyr10Ala mutation results in less stable and less compact structures, a conclusion based on our varying thermodynamic studies using harmonic and quasi-harmonic methods. Furthermore, the use of various intrinsic disorder predictors suggests that the Tyr10Ala mutation impacts the Aβ₄₂ propensity for disorder, whereas the application of several computational tools for aggregation prediction suggests that this mutation decreases the Aβ₄₂ aggregation propensity. The mid-domain interactions with the N- and C-terminal regions weaken or disappear upon Tyr10Ala mutation. In addition, the N- and C-terminal interactions are weaker or diminished upon the introduction of the Tyr10Ala mutation to the structures of the Aβ₄₂ peptide in solution

Multiparametric Analysis of Intrinsically Disordered Proteins: Looking at Intrinsic Disorder through Compound Eyes

Multiparametric Analysis of Intrinsically Disordered Proteins: Looking at Intrinsic Disorder through Compound Eye

Orderly order in protein intrinsic disorder distribution: disorder in 3500 proteomes from viruses and the three domains of life

<div><p>Intrinsically disordered proteins and intrinsically disordered protein regions are highly abundant in nature. However, the quantitative and qualitative measures of protein intrinsic disorder in species with known genomes are still not available. Furthermore, although the correlation between high fraction of disordered residues and advanced species has been reported, the details of this correlation and the connection between the disorder content and proteome complexity have not been reported as of yet. To fill this gap, we analysed entire proteomes of 3484 species from three domains of life (archaea, bacteria and eukaryotes) and from viruses. Our analysis revealed that the evolution process is characterized by distinctive patterns of changes in the protein intrinsic disorder content. We are showing here that viruses are characterized by the widest spread of the proteome disorder content (the percentage of disordered residues ranges from 7.3% in human coronavirus NL63 to 77.3% in <i>Avian carcinoma virus</i>). For several organisms, a clear correlation is seen between their disorder contents and habitats. In multicellular eukaryotes, there is a weak correlation between the complexity of an organism (evaluated as a number of different cell types) and its overall disorder content. For both the prokaryotes and eukaryotes, the disorder content is generally independent of the proteome size. However, disorder shows a sharp increase associated with the transition from prokaryotic to eukaryotic cells. This suggests that the increased disorder content in eukaryotic proteomes might be used by nature to deal with the increased cell complexity due to the appearance of the various cellular compartments.</p> </div

Potential functions of LEA proteins from the brine shrimp <i>Artemia franciscana</i> – anhydrobiosis meets bioinformatics

<p>Late embryogenesis abundant (LEA) proteins are a large group of anhydrobiosis-associated intrinsically disordered proteins, which are commonly found in plants and some animals. The brine shrimp <i>Artemia franciscana</i> is the only known animal that expresses LEA proteins from three, and not only one, different groups in its anhydrobiotic life stage. The reason for the higher complexity in the <i>A. franciscana</i> LEA proteome (LEAome), compared with other anhydrobiotic animals, remains mostly unknown. To address this issue, we have employed a suite of bioinformatics tools to evaluate the disorder status of the <i>Artemia</i> LEAome and to analyze the roles of intrinsic disorder in functioning of brine shrimp LEA proteins. We show here that <i>A. franciscana</i> LEA proteins from different groups are more similar to each other than one originally expected, while functional differences among members of group three are possibly larger than commonly anticipated. Our data show that although these proteins are characterized by a large variety of forms and possible functions, as a general strategy, <i>A. franciscana</i> utilizes glassy matrix forming LEAs concurrently with proteins that more readily interact with binding partners. It is likely that the function(s) of both types, the matrix-forming and partner-binding LEA proteins, are regulated by changing water availability during desiccation.</p

Virucidal activity of cell-penetrating peptides of viral origin

Virucidal activity of cell-penetrating peptides of viral origi

<i>In silico</i> evaluation of the resistance of the T790M variant of epidermal growth factor receptor kinase to cancer drug Erlotinib

<p>Epidermal growth factor receptor kinase is implicated in cancer development due to either overexpression or activation variants in its functional intracellular kinase domain. Threonine to methionine (Thr 790 Met) is one such variant observed commonly in patients showing resistance to kinase inhibitor drug Erlotinib. Two mechanisms for resistance have been proposed (1) steric hindrance and (2) enhanced binding to ATP. In this study, we employed molecular dynamics simulations and studied both the mechanisms. Extensive simulations and free energy of binding analyses has shown that steric hindrance does not explain appropriately the mechanism for resistance against Erlotinib therapy for this variant. It has been observed that conformational switching from an intermediate intrinsically disordered C-helix conformation is required for completion of the kinase’s catalytic cycle. Our study substantiates that T790M variant has greater tendency for early transition to this intrinsically disordered C-helix intermediate state. We propose that enhanced catalytic efficiency in addition to enhanced ATP binding explains mechanism of T790M resistance to drug Erlotinib.</p

Effect of human heat shock protein HspB6 on the solvent features of water in aqueous solutions

Effect of human heat shock protein HspB6 on the solvent features of water in aqueous solution

Intrinsic disorder according to transmembrane protein classes and topology.

<p>(A) Organization of the different protein dataset depending on the transmembrane protein classes and the presence or not of IDRs. B) Percent of IDRs localized in the cytoplasm or the extracellular domain of single-pass and multi-pass proteins. (C) Prediction of MoRFs in the proteins from the fully folded protein (FOP) and IDP datasets. Mann-Whitney Significance test ***: p value < 0.0001. (D) Percentage of MoRFs localized either on the cytoplasmic or extracellular part of transmembrane proteins. (E) BMPR2 (UniProtID: Q13873) is a single-pass transmembrane protein with a long predicted IDR in the cytoplasmic side. The red boxes show the position of the MoRFs detected in BMPR2. (F) zDHHC8 (UniProtID: Q9ULC8) is a multi-pass transmembrane protein with a long predicted IDR in the cytoplasmic side. For (C) and (D), the blue dots represent the average disorder score using PONDR-FIT, IUPRED and DISOPRED2 prediction tools and the error bars the standard error. The blue lane shows the position of the transmembrane domain and the grey area the cytoplasmic C-terminal part of the protein.</p

Topology prediction of a multi-pass transmembrane protein according to the localization of its IDRs.

<p>(A) Topology prediction of TMEM117 (UniProtID: Q9H0C3) according to the localization of its C-terminal IDRs, with the IN label describing the cytoplasmic part of the protein and the OUT labels the extracellular part. The blue dots represent the average disorder score using PONDR-FIT, IUPRED and DISOPRED2, and the error bars the standard error. The blue lanes show the position of the transmembrane domains. (B) Immunofluorescence of HeLa transiently expressing TMEM117-V5. Cells were fixed, permeabilized and stained for TMEM117-V5 and CLIMP63 (UniProtID: Q07065) for Endoplasmic Reticulum visualization. (C) Surface biotinylation of HeLa transiently expressing TMEM117-V5. Plasma membrane proteins were labelled with biotin, immunoprecipitated by streptavidin conjugated beads and probed by western blot against V5, transferrin receptor and GAPDH. The total cell extract (TCE) represents 10% of the immunoprecipitation volume. (D) TMEM117-V5 was immunoprecipitated with an anti V5 antibody from extracts of HeLa transiently expressing the protein. The precipitate was then left untreated or treated with N-Glycosidase F or EndoH and the effect of the treatment analyzed by SDS-PAGE and western blotting against the V5 tag. * aspecific band. (E) Expression of TMEM117 glycosylation mutants in HeLa. Cells were transfected for 48h and the wild-type and mutant proteins were immunoprecipitated using a mouse anti V5 monoclonal antibody and subsequently analyzed by SDS-PAGE and western blotting using a rabbit anti V5 antibody. (F) Immunofluorescence on HeLa transiently expressing TMEM117-GFP (green signal). Cells were fixed in 4% PFA and left non permeabilized or permeabilized with 0.1% Triton X100. Cells were then stained with a mouse anti-GFP primary antibody coupled to an Alexa 568 anti-mouse secondary antibody (red signal) and Hoechst for the nuclei staining in both conditions. (G) Cartoon representing the experimentally observed topology of TMEM117, the localization of the two N-Glycosylation sites and the GFP or V5 tags. For (C, D and E) n.t. = mock transfected controls.</p

Cellular localizations and functions of IDPs.

<p>(A) Cellular localizations of fully folded proteins and IDPs according to their UniProt annotations. The bar graph represent the percentage of fully folded proteins or IDPs associated with a particular GOTERM compared to the total number of proteins from our dataset associated with this GOTERM. The number within the bars show the number of proteins annotated with the GOTERM (B) Protein families enriched in fully folded proteins or IDPs. The enrichment is calculated with the number of proteins in the ordered or disordered dataset compared to the total amount of proteins known to be in this family. (C) Enrichment of GOTERM from the molecular function ontology for IDPs and fully folded proteins. The enrichment score was calculated by DAVID, an online tool for gene ontology. <b>(</b>D) Disorder prediction of Synaptotagmin 1 (UniProtID: P21579), a calcium binding protein involved in synaptic vesicles fusion. (E) Disorder prediction of UDP-glucuronosyltranferase 1–3 (UniProtID: P35503), an enzyme involved in the addition of glucoronic acid moieties to various compounds and important in detoxification. For (D and E) the blue dots represent the average disorder score using PONDR-FIT, IUPRED and DISOPRED2 prediction tools, and the errors bar the standard error. The blue lanes show the position of the transmembrane domains.</p