Identifying the amylome, proteins capable of forming amyloid-like fibrils. Proc Natl Acad Sci USA

Howard Hughes Medical Institute, University of California, Los Angeles, CA 90095-1570, USA.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 02/2010; 107(8):3487-92. DOI: 10.1073/pnas.0915166107
Source: PubMed

ABSTRACT The amylome is the universe of proteins that are capable of forming amyloid-like fibrils. Here we investigate the factors that enable a protein to belong to the amylome. A major factor is the presence in the protein of a segment that can form a tightly complementary interface with an identical segment, which permits the formation of a steric zipper-two self-complementary beta sheets that form the spine of an amyloid fibril. Another factor is sufficient conformational freedom of the self-complementary segment to interact with other molecules. Using RNase A as a model system, we validate our fibrillogenic predictions by the 3D profile method based on the crystal structure of NNQQNY and demonstrate that a specific residue order is required for fiber formation. Our genome-wide analysis revealed that self-complementary segments are found in almost all proteins, yet not all proteins form amyloids. The implication is that chaperoning effects have evolved to constrain self-complementary segments from interaction with each other.

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    • "Lysine residues in PAP248-286, PAP85-120, SEM1, and SEM2 peptides are frequently found within or immediately adjacent to hexapeptides predicted to form self-complementary β-strands (Figure 1C–E, underlined residues), termed steric zippers, which often comprise the spine of amyloid fibrils (Nelson et al., 2005; Goldschmidt et al., 2010; Sievers et al., 2011; Castellano and Shorter, 2012; Frohm et al., 2015). Moreover, the wealth of basic residues in PAP248-286, PAP85-120, and SEM1(45-107) (Figure 1C–E) led us to hypothesize that the lysine-and arginine-specific tweezer, CLR01, but not its derivative CLR03, which lacks hydrophobic sidewalls (Sinha et al., 2011) (Figure 1A,B), might bind to these residues and interfere with fibril assembly. "
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    ABSTRACT: Semen is the main vector for HIV transmission and contains amyloid fibrils that enhance viral infection. Available microbicides that target viral components have proven largely ineffective in preventing sexual virus transmission. In this study, we establish that CLR01, a 'molecular tweezer' specific for lysine and arginine residues, inhibits the formation of infectivity-enhancing seminal amyloids and remodels preformed fibrils. Moreover, CLR01 abrogates semen-mediated enhancement of viral infection by preventing the formation of virion-amyloid complexes and by directly disrupting the membrane integrity of HIV and other enveloped viruses. We establish that CLR01 acts by binding to the target lysine and arginine residues rather than by a non-specific, colloidal mechanism. CLR01 counteracts both host factors that may be important for HIV transmission and the pathogen itself. These combined anti-amyloid and antiviral activities make CLR01 a promising topical microbicide for blocking infection by HIV and other sexually transmitted viruses.
    eLife Sciences 08/2015; 4. DOI:10.7554/eLife.05397 · 9.32 Impact Factor
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    • "Crystal structure of amyloid microcrystal derived from Ab(37e42) showing b-sheet zipper formations (in blue). The structure is shown according to ZipperDB [62] "
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    ABSTRACT: Amyloids are highly ordered protein/peptide aggregates associated with human diseases as well as various native biological functions. Given the diverse range of physiochemical properties of amyloids, we hypothesized that higher order amyloid self-assembly could be used for fabricating novel hydrogels for biomaterial applications. For proof of concept, we designed a series of peptides based on the high aggregation prone C-terminus of Aβ42, which is associated with Alzheimer's disease. These Fmoc protected peptides self assemble to β sheet rich nanofibrils, forming hydrogels that are thermoreversible, non-toxic and thixotropic. Mechanistic studies indicate that while hydrophobic, π-π interactions and hydrogen bonding drive amyloid network formation to form supramolecular gel structure, the exposed hydrophobic surface of amyloid fibrils may render thixotropicity to these gels. We have demonstrated the utility of these hydrogels in supporting cell attachment and spreading across a diverse range of cell types. Finally, by tuning the stiffness of these gels through modulation of peptide concentration and salt concentration these hydrogels could be used as scaffolds that can drive differentiation of mesenchymal stem cells. Taken together, our results indicate that small size, ease of custom synthesis, thixotropic nature makes these amyloid-based hydrogels ideally suited for biomaterial/nanotechnology applications. Copyright © 2015 Elsevier Ltd. All rights reserved.
    Biomaterials 06/2015; 54. DOI:10.1016/j.biomaterials.2015.03.002 · 8.56 Impact Factor
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    • "So far, there are more than 20 kinds of illnesses related to protein misfolding such as Alzheimer's disease, Parkinson's disease and Type II diabetes [1] [3] [4]. Their common pathogenic characteristic is that the protein secondary structures changed from random coil and α-helix to β-folded or self-assembled amyloid deposition [5] [6]. "
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    ABSTRACT: It is essential to predict aggregation-forming sequences for elucidation of protein misfolding mechanisms and the design of effective antiamyloid inhibitors. In this work, we predict and characterize self-assembled hexapeptides by a quantitative sequence-aggregation relationship (QSAR) model, which involves characterization of factor analysis scale of generalized amino acid information (FASGAI) and modeling of supporting vector machine (SVM) with radial basis function kernel. The QSAR model achieves maximum accuracy of 78.33% and area under the receiver operating characteristic curve of 0.83 with leave one out cross-validation on 180 training hexapeptides. We determine "hotspots" and key factors that largely contribute to the self-assembly of these hexapeptides by analyzing their sequence-aggregation relationships. We also explore the applications of the present model, e.g., the first is to identify the aggregation-forming sequences within both β-amyloid peptide (Aβ42) and human islet amyloid polypeptide (hIAPP) using a 6-residue slide window, and acquire good agreement with previous experimental observations, the second is to perform in silico design of potential aggregation-forming hexapeptides which are validated by all-atom molecular dynamics simulation and density functional theory calculations, and the third is to predict the potential self-assembled tri-, tetra- and pentapeptides, in which hydrophobic amino acids such as isoleucine, leucine, valine, phenylalanine, and methionine occur at higher frequencies. The present QSAR model is helpful for (i) predicting self-assembled behaviors of peptides, (ii) scanning and identifying aggregation-forming sequences within proteins, (iii) understanding action mechanisms of peptide/protein aggregation, and (iv) designing potential self-assembled sequences applied as drug discovery and nano-materials.
    Chemometrics and Intelligent Laboratory Systems 04/2015; 145. DOI:10.1016/j.chemolab.2015.04.009 · 2.32 Impact Factor
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