A method for probing the mutational landscape of amyloid structure

O'Donnell, Barry; Waldispühl, Jérôme; Lis, Mieszko; Halfmann, Randal; Devadas, Srinivas; Lindquist, Susan; Berger, Bonnie

doi:10.1093/bioinformatics/btr238

Cited by 64 publications

(32 citation statements)

References 52 publications

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“…These algorithms use a variety of approaches, from the analysis of side chain distribution to molecular dynamics simulations, and apply a wide range of criteria, such as the side chain hydrophobicity, charge distribution, average packing density, dual α-helix and β-sheet propensity, hidden α-helix to β-sheet switches, β-sheet contiguity, correspondence to known amyloidogenic residue patterns, etc. (Galzitskaya et al 2006; López de la Paz and Serrano 2004; Fernandez-Escamilla et al 2004; Conchillo-Solé et al 2007; Hamodrakas et al 2007; Trovato et al 2007; Zhang et al 2007; Zibaee et al 2007; Kim et al 2009; Tian et al 2009; Maurer-Stroh et al 2010; Garbuzynskiy et al 2010; O’Donnell et al 2011). This multitude of criteria and approaches reflects the fact that β-aggregation and fibril formation is a complex process that can be induced in unrelated proteins by a wide range of factors.…”

Section: 3 Recent Advances In Structural and Bioinformatic Studiesmentioning

confidence: 99%

Amyloid-Forming Properties of Human Apolipoproteins: Sequence Analyses and Structural Insights

Das

Gursky

2015

Advances in Experimental Medicine and Biology

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Apolipoproteins are protein constituents of lipoproteins that transport cholesterol and fat in circulation and are central to cardiovascular health and disease. Soluble apolipoproteins can transiently dissociate from the lipoprotein surface in a labile free form that can misfold, potentially leading to amyloid disease. Misfolding of apoA-I, apoA-II, and serum amyloid A (SAA) causes systemic amyloidoses, apoE4 is a critical risk factor in Alzheimer's disease, and apolipoprotein misfolding is also implicated in cardiovascular disease. To explain why apolipoproteins are overrepresented in amyloidoses, it was proposed that the amphipathic α-helices, which form the lipid surface-binding motif in this protein family, have high amyloid-forming propensity. Here, we use 12 sequence-based bioinformatics approaches to assess amyloid-forming potential of human apolipoproteins and to identify segments that are likely to initiate β-aggregation. Mapping such segments on the available atomic structures of apolipoproteins helps explain why some of them readily form amyloid while others do not. Our analysis shows that nearly all amyloidogenic segments: (i) are largely hydrophobic, (ii) are located in the lipid-binding amphipathic α-helices in the native structures of soluble apolipoproteins, (iii) are predicted in both native α-helices and β-sheets in the insoluble apoB, and (iv) are predicted to form parallel in-register β-sheet in amyloid. Most of these predictions have been verified experimentally for apoC-II, apoA-I, apoA-II and SAA. Surprisingly, the rank order of the amino acid sequence propensity to form amyloid (apoB > apoA-II > apoC-II ≥ apoA-I, apoC-III, SAA, apoC-I > apoA-IV, apoA-V, apoE) does not correlate with the proteins' involvement in amyloidosis. Rather, it correlates directly with the strength of the protein-lipid association, which increases with increasing protein hydrophobicity. Therefore, the lipid surface-binding function and the amyloid-forming propensity are both rooted in apolipoproteins' hydrophobicity, suggesting that functional constraints make it difficult to completely eliminate pathogenic apolipoprotein misfolding. We propose that apolipoproteins have evolved protective mechanisms against misfolding, such as the sequestration of the amyloidogenic segments via the native protein-lipid and protein-protein interactions involving amphipathic α-helices and, in case of apoB, β-sheets. KeywordsLipid transport; Systemic amyloidosis; Atherosclerosis and Alzheimer's disease; Atomic protein structure; Sequence-based prediction algorithms Correspondence to: Olga Gursky. HHS Public AccessAuthor manuscript Adv Exp Med Biol. Author manuscript; available in PMC 2017 September 24.Published in final edited form as:Adv Exp Med Biol. 2015 ; 855: 175-211. doi:10.1007/978-3-319-17344-3_8. Author Manuscript Author ManuscriptAuthor ManuscriptAuthor Manuscript Lipoproteins and Apolipoproteins in Lipid Transport and MetabolismLipids in plasma, lymph and cerebrospinal fluid are transported via lipoproteins that are...

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Section: 3 Recent Advances In Structural and Bioinformatic Studiesmentioning

confidence: 99%

Amyloid-Forming Properties of Human Apolipoproteins: Sequence Analyses and Structural Insights

Das

Gursky

2015

Advances in Experimental Medicine and Biology

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“…The structure-based methods take into account the three-dimensional (3D) structures of welldefined fibrillar conformations of some proteins or peptides. These latter algorithms include: Zipper DB (Thompson et al, 2006), PASTA (Trovato et al, 2007;Walsh et al, 2014), FoldAmyloid (Galzitskaya et al, 2006), NetCSSP (Kim et al, 2009;Yoon et al, 2007), PreAmyl (Zhang et al, 2007), BETASCAN (Bryan et al, 2009), WALTZ (MaurerStroh et al, 2010), AmyloidMutants (O'Donnell et al, 2011) and STITCHER (Bryan et al, 2012). Importantly, although some of the previously enumerated algorithms were initially designed to check amyloid propensity, nowadays would to be considered that most of them really detect ␤-aggregation (including amorphous ␤-aggregates).…”

Section: ␤-Aggregation and Amyloid Prediction Algorithmsmentioning

confidence: 99%

Predicting the aggregation propensity of prion sequences

et al. 2015

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“…This method focuses on the density of protein-contact sites. In other methods, such as Zipper DB, the peptide is threaded onto an amyloid fiber backbone and then its energy and stability are determined [4][5][6]. Statistical methods include simple frequency profiles, such as the Waltz method [7].…”

Section: Introductionmentioning

confidence: 99%

Comparative modeling of hypothetical amyloid pores based on cylindrin

Zulpo

Kotulska

2015

J Mol Model

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Cylindrin is a six-stranded antiparallel beta barrel obtained from amyloidogenic strands of crystallin. It induces cell toxicity through an unknown mechanism. In this work, the potential use of the structure of cylindrin as a template for modeling amyloid pores-hypothetical transmembrane structures which appear during amyloid diseases-was studied. Using comparative modeling (performed by Modeller), we tested the stability of cylindrin-based pores made from several amyloid-forming and non-amyloid-forming strands deriving from mutated cylindrin and the prion sup35. We showed that cylindrin could be used as a template for modeling pores made from strands of amyloid proteins, but that the cylindrin structure does not result from the amyloidogenicity of these fragments, as fibril non-formers from the prion were also able to form a similar structure. Finally, we tested whether the cellular toxicity of cylindrin and related structures could be due to its incorporation into the cell membrane, leading to the creation of conducting ionic channels. The results of modeling indicate that cylindrin and tandem-repeat cylindrin, mutants of them, and cylindrin-like amyloid pores from prion sequences can only localize on the periphery of the membrane, and are not able to conduct any ions into the cell. These findings explain experimental results obtained for large unilamellar vesicles incubated with cylindrin, where conductance was not observed.

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A method for probing the mutational landscape of amyloid structure

Cited by 64 publications

References 52 publications

Amyloid-Forming Properties of Human Apolipoproteins: Sequence Analyses and Structural Insights

Amyloid-Forming Properties of Human Apolipoproteins: Sequence Analyses and Structural Insights

Predicting the aggregation propensity of prion sequences

Comparative modeling of hypothetical amyloid pores based on cylindrin

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