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ABSTRACT: The number of protein-peptide interactions in a cell is so large that experimental determination of all these complex structures would be a daunting task. Although homology modeling and refinement protocols have vastly improved the number and quality of predicted structural models, ab initio methods are still challenged by both the large number of possible docking sites and the conformational space accessible to flexible peptides. We present a method that addresses these challenges by sampling the entire accessible surface of a protein with a reduced conformational space of interacting backbone fragment pairs from unrelated structures. We demonstrate its potential by predicting ab initio the bound structure for a variety of protein-peptide complexes. In addition, we show the potential of our method for the discovery of domain interaction sites and domain-domain docking.
Structure 04/2013; · 6.35 Impact Factor
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ABSTRACT: Data mining in protein databases, derivatives from more fundamental protein 3D structure and sequence databases, has considerable unearthed potential for the discovery of sequence motif-structural motif-function relationships as the finding of the U-shape (Huf-Zinc) motif, originally a small student's project, exemplifies. The metal ion zinc is critically involved in universal biological processes, ranging from protein-DNA complexes and transcription regulation to enzymatic catalysis and metabolic pathways. Proteins have evolved a series of motifs to specifically recognize and bind zinc ions. Many of these, so called zinc fingers, are structurally independent globular domains with discontinuous binding motifs made up of residues mostly far apart in sequence. Through a systematic approach starting from the BRIX structure fragment database, we discovered that there exists another predictable subset of zinc-binding motifs that not only have a conserved continuous sequence pattern but also share a characteristic local conformation, despite being included in totally different overall folds. While this does not allow general prediction of all Zn binding motifs, a HMM-based web server, Huf-Zinc, is available for prediction of these novel, as well as conventional, zinc finger motifs in protein sequences. The Huf-Zinc webserver can be freely accessed through this URL ( http://mendel.bii.a-star.edu.sg/METHODS/hufzinc/ ).
Journal of Bioinformatics and Computational Biology 02/2013; 11(1):1340008.
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ABSTRACT: Most proteins sequences contain one or several short aggregation prone regions (APR) that can nucleate protein aggregation. Under normal conditions these APRs are protected from aggregation by protein interactions or because they are buried in the hydrophobic core of native protein domains. However, mutation, physiological stress or age-related disregulation of protein homeostasis increases the probability that aggregation-nucleating regions become solvent exposed. Aggregation then results from the self-assembly of APRs into -structured agglomerates that vary from small soluble oligomeric assemblies to large insoluble inclusions containing thousands of molecules. The functional effects of APR-driven aggregation are diverse and protein-specific leading to distinct disease phenotypes ranging from neurodegeneration to cancer. On a cellular and physiological level both wild type loss-of-function as well as aggregation-dependent gain-of-function effects have been shown to contribute to disease. Several molecular mechanism have been proposed to contribute to gain-of-function activity of protein aggregates includingcellular membrane disregulation, saturation of the protein quality control machinery or the ability of aggregates to engage non-native interactions with proteins and nucleic acids. These different mechanisms will all to some extent contribute to gain-of-function as in essence they all contribute to the rewiring ofthe cellular interactome by aggregation-specific interactions resulting for instance in the pronounced neurotoxicity of TDP43 aggregates by the sequestration of RNA molecules or the promotion of cell proliferation by the entrapment of homologous tumor suppressor proteins in p53 aggregates in cancer. In this review we discuss the mechanism of APR driven aggregation and how APRscontribute to modifying the cellular interactome by recruiting both misfolded as well as active proteins thereby inhibiting or activating specific cellular functions. Finally, we discuss the ubiquity of APRs in protein sequences and how selective pressure shaped protein sequences to minimizeAPR aggregation.
Current topics in medicinal chemistry 01/2013; · 4.47 Impact Factor
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ABSTRACT: Amyloid fibril formation is associated with misfolding diseases, as well as fulfilling a functional role. The cross-ß molecular architecture has been reported in increasing numbers of amyloid-like fibrillar systems. The Waltz algorithm is able to predict ordered self-assembly of amyloidogenic peptides by taking into account residue type and position. This algorithm has expanded the amyloid sequence space and here we characterise the structures of amyloid-like fibrils formed by three peptides identified by Waltz that form fibrils but not crystals. The structural challenge is met by combining electron microscopy, linear and circular dichroism and X-ray fibre diffraction. We propose structures that reveal a cross-ß conformation with 'steric-zipper' features, giving insights into the role for side chains in peptide packing and stability within fibrils. The amenity of these peptides to structural characterisation makes them compelling model systems to use for understanding the relationship between sequence, self-assembly, stability and structure for amyloid fibrils.
Biochemical Journal 12/2012; · 4.90 Impact Factor
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Annelies Vandersteen,
Ellen Hubin,
Rabia Sarroukh,
Greet De Baets,
Joost Schymkowitz, Frederic Rousseau,
Vinod Subramaniam,
Vincent Raussens,
Holger Wenschuh,
Dirk Wildemann,
Kerensa Broersen
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ABSTRACT: Aggregated forms of the amyloid-β peptide are hypothesized to act as the prime toxic agents in Alzheimer disease (AD). The in vivo amyloid-β peptide pool consists of both C- and N-terminally truncated or mutated peptides, and the composition thereof significantly determines AD risk. Other variations, such as biotinylation, are introduced as molecular tools to aid the understanding of disease mechanisms. Since these modifications have the potential to alter key aggregation properties of the amyloid-beta peptide, we present a comparative study of the aggregation of a substantial set of the most common in vivo identified and in vitro produced amyloid-beta peptides. STRUCTURED SUMMARY OF PROTEIN INTERACTIONS: Amyloid beta and Amyloid betabind by fluorescence technology (View Interaction: 1, 2, 3, 4, 5) Amyloid beta and Amyloid betabind by transmission electron microscopy (View Interaction: 1, 2) Amyloid beta and Amyloid betabind by filter binding (View Interaction: 1, 2, 3).
FEBS letters 10/2012; · 3.54 Impact Factor
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Annelies Vandersteen,
Marcelo Fabricio Masman,
Greet De Baets,
Wim Jonckheere,
Kees Van der Werf,
Siewert Jan Marrink,
Jef Rozenski,
Iryna Benilova,
Bart De Strooper,
Vinod Subramaniam,
Joost Schymkowitz, Frederic Rousseau,
Kerensa Broersen
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ABSTRACT: Current therapeutic approaches under development for Alzheimer disease, including γ-secretase modulating therapy, aim at increasing the production of Aβ1-38 and Aβ1-40 at the cost of longer Aβ peptides. Here, we consider the aggregation of Aβ1-38 and Aβ1-43 in addition to Aβ1-40 and Aβ1-42; in particular their behavior in mixtures representing the complex in vivo Aβ pool. We demonstrate that Aβ1-38 and Aβ1-43 aggregate similar to Aβ1-40 and Aβ1-42, respectively, but display variation in kinetics of assembly and toxicity due to differences in short timescale conformational plasticity. In biologically relevant mixtures of Aβ, Aβ1-38 and Aβ1-43 significantly affect the behaviors of Aβ1-40 and Aβ1-42. The short timescale conformational flexibility of Aβ1-38 is suggested to be responsible for enhancing toxicity of Aβ1-40 whilst exerting a cyto-protective effect on Aβ1-42. Our results indicate that the complex in vivo Aβ peptide array, and variations thereof, is critical in Alzheimer disease, which can influence the selection of current and new therapeutic strategies.
Journal of Biological Chemistry 09/2012; · 4.77 Impact Factor
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ABSTRACT: Fabry disease is a lysosomal storage disorder caused by loss of α-galactosidase function. More than 500 Fabry disease mutants have been identified, the majority of which are structurally destabilized. A therapeutic strategy under development for lysosomal storage diseases consists of using pharmacological chaperones to stabilize the structure of the mutant protein, thereby promoting lysosomal delivery over retrograde degradation. The substrate analog 1-deoxygalactonojirimycin (DGJ) has been shown to restore activity of mutant α-galactosidase and is currently in clinical trial for treatment of Fabry disease. However, only ∼65% of tested mutants respond to treatment in cultured patient fibroblasts, and the structural underpinnings of DGJ response remain poorly explained. Using computational modeling and cell culture experiments, we show that the DGJ response is negatively affected by protein aggregation of α-galactosidase mutants, revealing a qualitative difference between misfolding-associated and aggregation-associated loss of function. A scoring function combining predicted thermodynamic stability and intrinsic aggregation propensity of mutants captures well their aggregation behavior under overexpression in HeLa cells. Interestingly, the same classifier performs well on DGJ response data of patient-derived cultured lymphoblasts, showing that protein aggregation is an important determinant of chemical chaperone efficiency under endogenous expression levels as well. Our observations reinforce the idea that treatment of aggregation-associated loss of function observed for the more severe α-galactosidase mutants could be enhanced by combining pharmacological chaperone treatment with the suppression of mutant aggregation, e.g. via proteostatic regulator compounds that increase cellular chaperone expression.
Journal of Biological Chemistry 07/2012; 287(34):28386-97. · 4.77 Impact Factor
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ABSTRACT: The most common mechanism by which proteins aggregate consists in the assembly of short hydrophobic primary sequence segments into extended β-structured agglomerates. A significant enrichment of charged residues is observed at the flank of these aggregation-prone sequence segments, suggesting selective pressure against aggregation. These so-called aggregation gatekeepers act by increasing the intrinsic solubility of aggregating sequences in vitro, but it has been suggested that they could also facilitate chaperone interactions. Here, we address whether aggregation gatekeepers affect bacterial fitness. In Escherichia coli MC4100 we overexpressed GFP fusions with an aggregation-prone segment of σ32 (further termed σ32β) flanked by gatekeeper and non-gatekeeper residues and measured pairwise competitive growth. We found that the identity of flanking residues had significant effect on bacterial growth. Overexpression of σ32β flanked by its natural gatekeepers displayed the greatest competitive fitness, followed by other combinations of gatekeepers, while absence of gatekeepers strongly affects bacterial fitness. Further analysis showed the diversity of effects of gatekeepers on the proteostasis of σ32β including synthesis and degradation rates, in vivo aggregation propensity and chaperone response. Our results suggest that gatekeeper residues affect bacterial fitness not only by modulating the intrinsic aggregation propensity of proteins but also by the manner in which they affect the processing of σ32β-GFP by the protein quality control machinery of the cell. In view of these observations, we hypothesize that variation at gatekeeper positions offers a flexible selective strategy to modulate the proteostatic regulation of proteins to the match intrinsic aggregation propensities of proteins with required expression levels.
Protein Engineering Design and Selection 06/2012; 25(7):357-66. · 2.94 Impact Factor
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Cary Esselens,
Ragna Sannerud,
Rodrigo Gallardo,
Veerle Baert,
Daniela Kaden,
Lutgarde Serneels,
Bart De Strooper, Frederic Rousseau,
Gerd Multhaup,
Joost Schymkowitz,
Johannes P M Langedijk,
Wim Annaert
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ABSTRACT: Presenilins (PSENs) form the catalytic component of the γ-secretase complex, responsible for intramembrane proteolysis of amyloid precursor protein (APP) and Notch, among many other membrane proteins. Previously, we identified a PSEN1-binding domain in APP, encompassing half of the transmembrane domain following the amyloid β (Aβ) sequence. Based on this, we designed peptides mimicking this interaction domain with the aim to selectively block APP processing and Aβ generation through interfering with enzyme-substrate binding. We identified a peptide sequence that, when fused to a virally derived translocation peptide, significantly lowered Aβ production (IC(50): 317 nM) in cell-free and cell-based assays using APP-carboxy terminal fragment as a direct γ-secretase substrate. Being derived from the APP sequence, this inhibitory peptide did not affect NotchΔE γ-cleavage, illustrating specificity and potential therapeutic value. In cell-based assays, the peptide strongly suppressed APP shedding, demonstrating that it exerts the inhibitory effect already upstream of γ-secretase, most likely through steric hindrance.
The FASEB Journal 06/2012; 26(9):3765-78. · 5.71 Impact Factor
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Lucía Chávez-Gutiérrez,
Leen Bammens,
Iryna Benilova,
Annelies Vandersteen,
Manasi Benurwar,
Marianne Borgers,
Sam Lismont,
Lujia Zhou,
Simon Van Cleynenbreugel,
Hermann Esselmann,
Jens Wiltfang,
Lutgarde Serneels,
Eric Karran,
Harrie Gijsen,
Joost Schymkowitz, Frederic Rousseau,
Kerensa Broersen,
Bart De Strooper
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ABSTRACT: The mechanisms by which mutations in the presenilins (PSEN) or the amyloid precursor protein (APP) genes cause familial Alzheimer disease (FAD) are controversial. FAD mutations increase the release of amyloid β (Aβ)42 relative to Aβ40 by an unknown, possibly gain-of-toxic-function, mechanism. However, many PSEN mutations paradoxically impair γ-secretase and 'loss-of-function' mechanisms have also been postulated. Here, we use kinetic studies to demonstrate that FAD mutations affect Aβ generation via three different mechanisms, resulting in qualitative changes in the Aβ profiles, which are not limited to Aβ42. Loss of ɛ-cleavage function is not generally observed among FAD mutants. On the other hand, γ-secretase inhibitors used in the clinic appear to block the initial ɛ-cleavage step, but unexpectedly affect more selectively Notch than APP processing, while modulators act as activators of the carboxypeptidase-like (γ) activity. Overall, we provide a coherent explanation for the effect of different FAD mutations, demonstrating the importance of qualitative rather than quantitative changes in the Aβ products, and suggest fundamental improvements for current drug development efforts.
The EMBO Journal 04/2012; 31(10):2261-74. · 9.20 Impact Factor
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ABSTRACT: Three-dimensional domain swapping is the process by which two identical protein chains exchange a part of their structure to form an intertwined dimer or higher-order oligomer. The phenomenon has been observed in the crystal structures of a range of different proteins. In this chapter we review the experiments that have been performed in order to understand the sequence and structural determinants of domain-swapping and these show how the general principles obtained can be used to engineer proteins to domain swap. We discuss the role of domain swapping in regulating protein function and as one possible mechanism of protein misfolding that can lead to aggregation and disease. We also review a number of interesting pathways of macromolecular assembly involving β-strand insertion or complementation that are related to the domain-swapping phenomenon.
Advances in experimental medicine and biology 01/2012; 747:137-52. · 1.09 Impact Factor
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Annelies Vandersteen,
Marcelo F Masman,
Greet De Baets,
Wim Jonckheere,
Kees Van Der Werf,
Siewert J Marrink,
Jef Rozenski,
Iryna Benilova,
Bart De Strooper,
Vinod Subramaniam,
Joost Schymkowitz, Frederic Rousseau,
Kerensa Broersen
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ABSTRACT: Current therapeutic approaches under development for Alzheimer disease, including γ-secretase modulating therapy, aim at increasing the production of A-beta(1-38) and A-beta(1-40) at the cost of longer A-beta peptides. Here, we consider the aggregation of A-beta(1-38) and A-beta(1-43) in addition to A-beta(1-40) and A-beta(1-42), in particular their behavior in mixtures representing the complex in vivo A-beta pool. We demonstrate that A-beta(1-38) and A-beta(1-43) aggregate similar to A-beta(1-40) and A-beta(1-42), respectively, but display a variation in the kinetics of assembly and toxicity due to differences in short timescale conformational plasticity. In biologically relevant mixtures of A-beta, A-beta(1-38) and A-beta(1-43) significantly affect the behaviors of A-beta(1-40) and A-beta(1-42). The short timescale conformational flexibility of A-beta(1-38) is suggested to be responsible for enhancing toxicity of A-beta(1-40) while exerting a cyto-protective effect on A-beta(1-42). Our results indic
Journal of Biological Chemistry. 12/2011; 287(44):36732-36743.
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Kris Pauwels,
Thomas L Williams,
Kyle L Morris,
Wim Jonckheere,
Annelies Vandersteen,
Geoff Kelly,
Joost Schymkowitz, Frederic Rousseau,
Annalisa Pastore,
Louise C Serpell,
Kerensa Broersen
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ABSTRACT: The β-amyloid peptide (Aβ) is directly related to neurotoxicity in Alzheimer disease (AD). The two most abundant alloforms of the peptide co-exist under normal physiological conditions in the brain in an Aβ(42):Aβ(40) ratio of ∼1:9. This ratio is often shifted to a higher percentage of Aβ(42) in brains of patients with familial AD and this has recently been shown to lead to increased synaptotoxicity. The molecular basis for this phenomenon is unclear. Although the aggregation characteristics of Aβ(40) and Aβ(42) individually are well established, little is known about the properties of mixtures. We have explored the biophysical and structural properties of physiologically relevant Aβ(42):Aβ(40) ratios by several techniques. We show that Aβ(40) and Aβ(42) directly interact as well as modify the behavior of the other. The structures of monomeric and fibrillar assemblies formed from Aβ(40) and Aβ(42) mixtures do not differ from those formed from either of these peptides alone. Instead, the co-assembly of Aβ(40) and Aβ(42) influences the aggregation kinetics by altering the pattern of oligomer formation as evidenced by a unique combination of solution nuclear magnetic resonance spectroscopy, high molecular weight mass spectrometry, and cross-seeding experiments. We relate these observations to the observed enhanced toxicity of relevant ratios of Aβ(42):Aβ(40) in synaptotoxicity assays and in AD patients.
Journal of Biological Chemistry 12/2011; 287(8):5650-60. · 4.77 Impact Factor
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ABSTRACT: Single nucleotide variants (SNVs) are, together with copy number variation, the primary source of variation in the human genome and are associated with phenotypic variation such as altered response to drug treatment and susceptibility to disease. Linking structural effects of non-synonymous SNVs to functional outcomes is a major issue in structural bioinformatics. The SNPeffect database (http://snpeffect.switchlab.org) uses sequence- and structure-based bioinformatics tools to predict the effect of protein-coding SNVs on the structural phenotype of proteins. It integrates aggregation prediction (TANGO), amyloid prediction (WALTZ), chaperone-binding prediction (LIMBO) and protein stability analysis (FoldX) for structural phenotyping. Additionally, SNPeffect holds information on affected catalytic sites and a number of post-translational modifications. The database contains all known human protein variants from UniProt, but users can now also submit custom protein variants for a SNPeffect analysis, including automated structure modeling. The new meta-analysis application allows plotting correlations between phenotypic features for a user-selected set of variants.
Nucleic Acids Research 11/2011; 40(Database issue):D935-9. · 8.03 Impact Factor
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ABSTRACT: Structure-based computational methods are popular tools for designing proteins and interactions between proteins because they provide the necessary insight and details required for rational engineering. Here, we first argue that large-scale databases of fragments contain a discrete but complete set of building blocks that can be used to design structures. We show that these structural alphabets can be saturated to provide conformational ensembles that sample the native structure space around energetic minima. Second, we show that catalogs of interaction patterns hold the key to overcome the lack of scaffolds when computationally designing protein interactions. Finally, we illustrate the power of database-driven computational protein design methods by recent successful applications and discuss what challenges remain to push this field forward.
Current Opinion in Structural Biology 06/2011; 21(4):452-9. · 9.42 Impact Factor
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ABSTRACT: A graphical user interface for the FoldX protein design program has been developed as a plugin for the YASARA molecular graphics suite. The most prominent FoldX commands such as free energy difference upon mutagenesis and interaction energy calculations can now be run entirely via a windowed menu system and the results are immediately shown on screen. AVAILABILITY AND IMPLEMENTATION: The plugin is written in Python and is freely available for download at http://foldxyasara.switchlab.org/ and supported on Linux, MacOSX and MS Windows.
Bioinformatics 06/2011; 27(12):1711-2. · 5.47 Impact Factor
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ABSTRACT: We previously showed the existence of selective pressure against protein aggregation by the enrichment of aggregation-opposing 'gatekeeper' residues at strategic places along the sequence of proteins. Here we analyzed the relationship between protein lifetime and protein aggregation by combining experimentally determined turnover rates, expression data, structural data and chaperone interaction data on a set of more than 500 proteins. We find that selective pressure on protein sequences against aggregation is not homogeneous but that short-living proteins on average have a higher aggregation propensity and fewer chaperone interactions than long-living proteins. We also find that short-living proteins are more often associated to deposition diseases. These findings suggest that the efficient degradation of high-turnover proteins is sufficient to preclude aggregation, but also that factors that inhibit proteasomal activity, such as physiological ageing, will primarily affect the aggregation of short-living proteins.
PLoS Computational Biology 06/2011; 7(6):e1002090. · 5.22 Impact Factor
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ABSTRACT: We provide a validated and rapid protocol for the solubilization of amyloid β-peptide (Aβ). This procedure involves sequential solubilization using structure-breaking organic solvents hexafluoroisopropanol and DMSO followed by column purification. The low solubility and tendency of Aβ to aggregate considerably impede the in vitro handling and biophysical or biological investigation of Aβ, despite the interest in this peptide because of its implication in Alzheimer's disease. The main advantage of the proposed protocol over others is that it results in standardized aggregate-free Aβ peptide samples that are biocompatible for cell culture studies and yield reproducible aggregation kinetics and cytotoxicities. This three-step protocol also enables the co-solubilization of the longer Aβ42 variant with Aβ40 in ratios relevant to Alzheimer's disease.
Protein Engineering Design and Selection 05/2011; 24(9):743-50. · 2.94 Impact Factor
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ABSTRACT: We here present a new method to measure the degree of protein-bound methionine sulfoxide formation at a proteome-wide scale. In human Jurkat cells that were stressed with hydrogen peroxide, over 2000 oxidation-sensitive methionines in more than 1600 different proteins were mapped and their extent of oxidation was quantified. Meta-analysis of the sequences surrounding the oxidized methionine residues revealed a high preference for neighboring polar residues. Using synthetic methionine sulfoxide containing peptides designed according to the observed sequence preferences in the oxidized Jurkat proteome, we discovered that the substrate specificity of the cellular methionine sulfoxide reductases is a major determinant for the steady-state of methionine oxidation. This was supported by a structural modeling of the MsrA catalytic center. Finally, we applied our method onto a serum proteome from a mouse sepsis model and identified 35 in vivo methionine oxidation events in 27 different proteins.
Molecular & Cellular Proteomics 03/2011; 10(5):M110.006866. · 7.40 Impact Factor
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Jie Xu,
Joke Reumers,
José R Couceiro,
Frederik De Smet,
Rodrigo Gallardo,
Stanislav Rudyak,
Ann Cornelis,
Jef Rozenski,
Aleksandra Zwolinska,
Jean-Christophe Marine,
Diether Lambrechts,
Young-Ah Suh, Frederic Rousseau,
Joost Schymkowitz
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ABSTRACT: Many p53 missense mutations possess dominant-negative activity and oncogenic gain of function. We report that for structurally destabilized p53 mutants, these effects result from mutant-induced coaggregation of wild-type p53 and its paralogs p63 and p73, thereby also inducing a heat-shock response. Aggregation of mutant p53 resulted from self-assembly of a conserved aggregation-nucleating sequence within the hydrophobic core of the DNA-binding domain, which becomes exposed after mutation. Suppressing the aggregation propensity of this sequence by mutagenesis abrogated gain of function and restored activity of wild-type p53 and its paralogs. In the p53 germline mutation database, tumors carrying aggregation-prone p53 mutations have a significantly lower frequency of wild-type allele loss as compared to tumors harboring nonaggregating mutations, suggesting a difference in clonal selection of aggregating mutants. Overall, our study reveals a novel disease mechanism for mutant p53 gain of function and suggests that, at least in some respects, cancer could be considered an aggregation-associated disease.
Nature Chemical Biology 03/2011; 7(5):285-95. · 14.69 Impact Factor
