A Consensus Method for the Prediction of ‘Aggregation-Prone’ Peptides in Globular Proteins

Tsolis, Antonios C.; Παπανδρεου, Νικολαοσ; Iconomidou, Vassiliki A.; Hamodrakas, Stavros J.

doi:10.1371/journal.pone.0054175

Cited by 275 publications

(298 citation statements)

References 59 publications

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“…Aggregation sites were predicted using the programs Tango (41), Waltz (42), Aggrescan (43), FoldAmyloid (44), and Amylpred2 as well as by a consensus method combining the first three and NetCSSP, amyloid mutants, Pafig, amyloidogenic pattern, SecStr, average packing density, β-strand contiguity, and hexapeptide conformational energy (45). Sequences predicted to be aggregation-prone by at least six programs were chosen to be the aggregation sites.…”

Section: Methodsmentioning

confidence: 99%

Multisite aggregation of p53 and implications for drug rescue

Wang

Fersht

2017

Proc. Natl. Acad. Sci. U.S.A.

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Protein aggregation is involved in many diseases. Often, a unique aggregation-prone sequence polymerizes to form regular fibrils. Many oncogenic mutants of the tumor suppressor p53 rapidly aggregate but form amorphous fibrils. A peptide surrounding Ile254 is proposed to be the aggregation-driving sequence in cells. We identified several different aggregating sites from limited proteolysis of harvested aggregates and effects of mutations on kinetics and products of aggregation. We present a model whereby the amorphous nature of the aggregates results from multisite branching of polymerization after slow unfolding of the protein, which may be a common feature of aggregation of large proteins. Greatly lowering the aggregation propensity of any one single site, including the site of Ile254, by mutation did not inhibit aggregation in vitro because aggregation could still occur via the other sites. Inhibition of an individual site is, accordingly, potentially unable to prevent aggregation in vivo. However, cancer cells are specifically killed by peptides designed to inhibit the Ile254 sequence and further aggregation-driving sequences that we have found. Consistent with our proposed mechanism of aggregation, we found that such peptides did not inhibit aggregation of mutant p53 in vitro. The cytotoxicity was not eliminated by knockdown of p53 in 2D cancer cell cultures. The peptides caused rapid cell death, much faster than usually expected for p53-mediated transcription-dependent apoptosis. There may also be non-p53 targets for those peptides in cancer cells, such as p63, or the peptides may alter other interactions of partly denatured p53 with receptors.amyloid | mechanism | misfolding | disease T he tumor suppressor p53 is inactivated by mutation in a substantial number of tumors (1-3). Some 30-40% of those oncogenic mutants are simply destabilized by mutations in its core domain. Those mutants are temperature-sensitive, having a WT structure at lower temperatures, but melt at close to body temperature or below and rapidly aggregate (4-6). Protein aggregation occurs in many diseases (7-9). The best mechanistically characterized examples involve the polymerization of aggregationprone peptides (10, 11) or small proteins to give well-defined fibrils based on a regular repeat structure (12-18). The fibrillar aggregates have a characteristic cross-β X-ray diffraction pattern and bind such dyes as Congo Red and Thioflavine T (ThT) (16). The kinetics of aggregation usually follow a nucleation-growth mechanism, with very slow nucleation (19-21). WT p53 itself aggregates at body temperature (4-6, 22-24), and the oncogenic destabilized mutants aggregate even faster to give amorphous structures that display the characteristic diffraction pattern and bind those diagnostic dyes (23, 25), although under certain conditions, such as very high pressure, they will generate regular fibrils (23,26). The mechanism of initiation of aggregation of p53 differs from the usually studied examples. Two molecules of the core domain of p53 exten...

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Section: Methodsmentioning

confidence: 99%

Multisite aggregation of p53 and implications for drug rescue

Wang

Fersht

2017

Proc. Natl. Acad. Sci. U.S.A.

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“…Primary sequences of mouse Cst8 (CRES) (UniProt P32766), Cst11 (CRES2) (UniProt Q9D269), Cst12 (CRES3) (UniProt Q9DAN8), cystatin E2 (NCBI NP_084236.1) and Cst3 (cystatin C) (UniProt P21460) were analyzed by AmylPred2, an algorithm for consensus prediction of amyloidogenic determinants in polypeptide sequences (http://aias.biol.uoa.gr/ AMYLPRED2) (Tsolis et al, 2013). Briefly, AmylPred 2 uses the consensus, defined as the hit overlap of 5 of 11, different methods that are known or specifically designed to predict features related to the formation of amyloid fibrils.…”

Section: Amylpred2mentioning

confidence: 99%

Cystatin-related epididymal spermatogenic subgroup members are part of an amyloid matrix and associated with extracellular vesicles in the mouse epididymal lumen

et al. 2016

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STUDY QUESTION: Do the CRES (cystatin-related epididymal spermatogenic) subgroup members, including CRES2, CRES3 and cystatin E2, contribute to the formation of a nonpathological, functional amyloid matrix in the mouse epididymal lumen?SUMMARY ANSWER: CRES2, CRES3 and cystatin E2 self-assemble with different aggregation properties into amyloids in vitro, are part of a common amyloid matrix in the mouse epididymal lumen and are present in extracellular vesicles.WHAT IS KNOWN ALREADY: Although previously thought only to be pathological, accumulating evidence has established that amyloids, which are highly ordered protein aggregates, can also carry out functional roles in the absence of pathology. We previously demonstrated that nonpathological amyloids are present in the epididymis; specifically, that the reproductive cystatin CRES forms amyloid and is present in the mouse epididymal lumen in a film-like amyloid matrix that is intimately associated with spermatozoa. Because the related proteins CRES2, CRES3 and cystatin E2 are also expressed in the epididymis, the present studies were carried out to determine if these proteins are also amyloidogenic in vitro and in vivo and thus may coordinately function with CRES as an amyloid structure. STUDY DESIGN, SAMPLES/MATERIALS, METHODS:The epididymides from CD1 and Cst8 (CRES)129SvEv/B6 gene knockout (KO) and wild-type mice and antibodies that specifically recognize each CRES subgroup member were used for immunohistochemical and biochemical analyzes of CRES subgroup proteins. Methods classically used to identify amyloid, including the conformation-dependent dyes thioflavin S (ThS) and thioflavin T (ThT), conformation-dependent antibodies, protein aggregation disease ligand (which binds any amyloid independent of sequence) and negative stain electron microscopy (EM) were carried out to examine the amyloidogenic properties of CRES subgroup members. Immunofluorescence analysis and confocal microscopy were used for colocalization studies. MAIN RESULTS AND THE ROLE OF CHANCE:Immunoblot and immunofluorescence analyzes showed that CRES2, CRES3 and cystatin E2 were primarily found in the initial segment and intermediate zone of the epididymis and were profoundly downregulated in epididymides from CRES KO mice, suggesting integrated functions. Except for CRES3, which was only detected in a particulate form, proteins were present in the epididymal lumen in both soluble and particulate forms including in a film-like matrix and in extracellular vesicles. The use of amyloid-specific reagents determined that all CRES subgroup members were present as amyloids and colocalized to a common amyloid matrix present in the epididymal lumen. Negative stain EM, dot blot analysis and ThT plate assays showed that recombinant CRES2, CRES3 and cystatin E2 formed amyloid in vitro, albeit with different aggregation properties. Together, our studies demonstrate that a unique amyloid matrix composed of the CRES family of reproductive-specific cystatins and cystatin C is a normal component of the mouse ...

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“…30 We also compared the performance of AWSEMAmylometer with that of TANGO and Waltz on the Waltz dataset.…”

Section: Amylometermentioning

confidence: 99%

The AWSEM-Amylometer: predicting amyloid propensity and fibril topology using an optimized folding landscape model

Chen

Schafer

Zheng

et al. 2017

Preprint

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Amyloids are fibrillar protein aggregates with simple repeated structural motifs in their cores, usually β-strands but sometimes α-helices. Identifying the amyloid-prone regions within protein sequences is important both for understanding the mechanisms of amyloid-associated diseases and for understanding functional amyloids. Based on the crystal structures of seven cross-β amyloidogenic peptides with different topologies and one recently solved cross-α fiber structure, we have developed a computational approach for identifying amyloidogenic segments in protein sequences using the 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/138842 doi: bioRxiv preprint first posted online May. 17, 2017; aggregation-prone sequences in multiple datasets. The method also predicts the specific topologies (the relative arrangement of β-strands in the core) of the amyloid fibrilswell. An important advantage of the AWSEM-Amylometer over other existing methods is its direct connection with an efficient, optimized protein folding simulation model, AWSEM. This connection allows one to combine efficient and accurate search of protein sequences for amyloidogenic segments with the detailed study of the thermodynamic and kinetic roles that these segments play in folding and aggregation in the context of the entire protein sequence. We present new simulation results that highlight the free energy landscapes of peptides that can take on multiple fibril topologies. We also demonstrate how the Amylometer methodology can be straightforwardly extended to the study of functional amyloids that have the recently discovered cross-α fibril architecture.

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A Consensus Method for the Prediction of ‘Aggregation-Prone’ Peptides in Globular Proteins

Cited by 275 publications

References 59 publications

Multisite aggregation of p53 and implications for drug rescue

Multisite aggregation of p53 and implications for drug rescue

Cystatin-related epididymal spermatogenic subgroup members are part of an amyloid matrix and associated with extracellular vesicles in the mouse epididymal lumen

The AWSEM-Amylometer: predicting amyloid propensity and fibril topology using an optimized folding landscape model

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