Explore the vast range of titles available.

Colocalization of microbial pathogens and the β-amyloid peptide (Aβ) in the brain of Alzheimer’s disease (AD) patients suggests that microbial infection may play a role in sporadic AD. Aβ exhibits antimicrobial activity against numerous pathogens, supporting a potential role for Aβ in the innate immune response. While mammalian amyloid is associated with disease, many bacteria form amyloid fibrils to fortify the biofilm that protects the cells from the surrounding environment. In the microbial AD hypothesis, Aβ aggregates in response to infection to combat the pathogen. We hypothesize that this occurs through toxic Aβ oligomers that contain α-sheet structure and form prior to fibrillization. De novo designed α-sheet peptides specifically bind to the α-sheet structure present in the oligomers of both bacterial and mammalian amyloidogenic proteins to neutralize toxicity and inhibit aggregation. Here, we measure the effect of E. coli on Aβ, including upregulation, aggregation, and toxicity. Additionally, we determined the effect of Aβ structure on E. coli amyloid fibrils, or curli comprised of the CsgA protein, and biofilm formation. We found that curli formation by E. coli increased Aβ oligomer production, and Aβ oligomers inhibited curli biogenesis and reduced biofilm cell density. Further, curli and biofilm inhibition by Aβ oligomers increased E. coli susceptibility to gentamicin. Toxic oligomers of Aβ and CsgA interact via α-sheet interactions, neutralizing their toxicity. These results suggest that exposure to toxic oligomers formed by microbial pathogens triggers Aβ oligomer upregulation and aggregation to combat infection via selective interactions between α-sheet oligomers to neutralize toxicity of both species with subsequent inhibition of fibrillization.

Alzheimer’s Disease (AD) is a neurodegenerative disorder that is characterized clinically by progressive cognitive decline and pathologically by the β-sheet rich fibril plaque deposition of the amyloid-β (Aβ) peptide in the brain. While plaques are a hallmark of AD, plaque burden is not correlated with cognitive impairment. Instead, Aβ oligomers formed during the aggregation process represent the main agents of neurotoxicity, which occurs 10–20 years before patients begin to show symptoms. These oligomers are dynamic in nature and represented by a heterogeneous distribution of aggregates ranging from low- to high-molecular weight, some of which are toxic while others are not. A major difficulty in determining the pathological mechanism(s) of Aβ, developing reliable diagnostic markers for early-stage detection, as well as effective therapeutics for AD are the differentiation and characterization of oligomers formed throughout disease propagation based on their molecular features, effects on biological function, and relevance to disease propagation and pathology. Thus, it is critical to methodically identify the mechanisms of Aβ aggregation and toxicity, as well as describe the roles of different oligomers and aggregates in disease progression and molecular pathology. Here, we describe a variety of biophysical techniques used to isolate and characterize a range of Aβ oligomer populations, as well as discuss proposed mechanisms of toxicity and therapeutic interventions aimed at specific assemblies formed during the aggregation process. The approaches being used to map the misfolding and aggregation of Aβ are like what was done during the fundamental early studies, mapping protein folding pathways using combinations of biophysical techniques in concert with protein engineering. Such information is critical to the design and molecular engineering of future diagnostics and therapeutics for AD.

Amyloid-beta (Aβ) toxic oligomers are critical early players in the molecular pathology of Alzheimer’s disease (AD). We have developed a Soluble Oligomer Binding Assay (SOBA-AD) for detection of these Aβ oligomers that contain α-sheet secondary structure that discriminates plasma samples from patients on the AD continuum from non-AD controls. We tested 265 plasma samples from two independent cohorts to investigate the performance of SOBA-AD. Testing was performed at two different sites, with different personnel, reagents, and instrumentation. Across two cohorts, SOBA-AD discriminated AD patients from cognitively unimpaired (CU) subjects with 100% sensitivity, > 95% specificity, and > 98% area under the curve (AUC) (95% CI 0.95–1.00). A SOBA-AD positive readout, reflecting α-sheet toxic oligomer burden, was found in AD patients, and not in controls, providing separation of the two populations, aside from 5 SOBA-AD positive controls. Based on an earlier SOBA-AD study, the Aβ oligomers detected in these CU subjects may represent preclinical cases of AD. The results presented here support the value of SOBA-AD as a promising blood-based tool for the detection and confirmation of AD.

Molecular dynamics simulations of the protein chymotrypsin inhibitor 2 in 8 M urea at 60° C were undertaken to investigate the molecular basis of chemical denaturation. The protein unfolded rapidly under these conditions, but it retained its native structure in a control simulation in water at the same temperature. The overall process of unfolding in urea was similar to that observed in thermal denaturation simulations above the protein's Tmof 75° C. The first step in unfolding was expansion of the hydrophobic core. Then, the core was solvated by water and later by urea. The denatured structures in both urea and at high temperature contained residual native helical structure, whereas the β-structure was completely disrupted. The average residence time for urea around hydrophilic groups was six times greater than around hydrophobic residues and in all cases greater than the corresponding water residence times. Water self-diffusion was reduced 40% in 8 M urea. Urea altered water structure and dynamics, thereby diminishing the hydrophobic effect and encouraging solvation of hydrophobic groups. In addition, through urea's weakening of water structure, water became free to compete with intraprotein interactions. Urea also interacted directly with polar residues and the peptide backbone, thereby stabilizing nonnative conformations. These simulations suggest that urea denatures proteins via both direct and indirect mechanisms.

We can track the positions and movements of all the atoms in small proteins as they fold and unfold by combining experimental studies with atomic-resolution molecular dynamics simulations. General principles as to how such complex architectures form so rapidly are now emerging from in-depth studies of a few proteins.

Uropathogenic Escherichia coli account for the largest proportion of nosocomial infections in the United States. Nosocomial infections are a major source of increased costs and treatment complications. Many infections are biofilm associated, rendering antibiotic treatments ineffective or cause additional complications (e.g., microbiome depletion). This work presents a potentially complementary non-antibiotic strategy to fight nosocomial infections by inhibiting the formation of amyloid fibrils, a proteinaceous structural reinforcement known as curli in E. coli biofilms. Despite extensive characterization of the fibrils themselves and their associated secretion system, mechanistic details of curli assembly in vivo remain unclear. We hypothesized that, like other amyloid fibrils, curli polymerization involves a unique secondary structure termed “α-sheet”. Biophysical studies herein confirmed the presence of α-sheet structure in prefibrillar species of CsgA, the major component of curli, as it aggregated. Binding of synthetic α-sheet peptides to the soluble α-sheet prefibrillar species inhibited CsgA aggregation in vitro and suppressed amyloid fibril formation in biofilms. Application of synthetic α-sheet peptides also enhanced antibiotic susceptibility and dispersed biofilm-resident bacteria for improved uptake by phagocytic cells. The ability of synthetic α-sheet peptides to reduce biofilm formation, improve antibiotic susceptibility, and enhance clearance by macrophages has broad implications for combating biofilm-associated infections.

Proteins are very sensitive to their solvent environments. Urea is a common chemical denaturant of proteins, yet some animals contain high concentrations of urea. These animals have evolved an interesting mechanism to counteract the effects of urea by using trimethylamine N-oxide (TMAO). The molecular basis for the ability of TMAO to act as a chemical chaperone remains unknown. Here, we describe molecular dynamics simulations of a small globular protein, chymotrypsin inhibitor 2, in 8 M urea and 4 M TMAO/8 M urea solutions, in addition to other control simulations, to investigate this effect at the atomic level. In 8 M urea, the protein unfolds, and urea acts in both a direct and indirect manner to achieve this effect. In contrast, introduction of 4 M TMAO counteracts the effect of urea and the protein remains well structured. TMAO makes few direct interactions with the protein. Instead, it prevents unfolding of the protein by structuring the solvent. In particular, TMAO orders the solvent and discourages it from competing with intraprotein H bonds and breaking up the hydrophobic core of the protein.

The ability to diagnose and treat prion diseases is limited by our current understanding of the conversion process of the protein from healthy to harmful isoform. Whereas the monomeric, benign species is well characterized, the misfolded conformations responsible for infectivity and neurodegeneration remain elusive. There is mounting evidence that fibrillization intermediates, or protofibrils, but not mature fibrils or plaques, are the pathogenic species in amyloid diseases. Here, we use molecular dynamics to simulate the conversion of the prion protein. Molecular dynamics simulation produces a scrapie prion protein-like conformation enriched in β-structure that is in good agreement with available experimental data. The converted conformation was then used to model a protofibril by means of the docking of hydrophobic patches of the template structure to form hydrogen-bonded sheets spanning adjacent subunits. The resulting protofibril model provides a non-branching aggregate with a 31axis of symmetry that is in good agreement with a wide variety of experimental data; importantly, it was derived from realistic simulation of the conversion process.

Previous studies suggest that the toxic soluble-oligomeric form of different amyloid proteins share a common backbone conformation, but the amorphous nature of this oligomer prevents its structural characterization by experiment. Based on molecular dynamics simulations we proposed that toxic intermediates of different amyloid proteins adopt a common, nonstandard secondary structure, called α-sheet. Here we report the experimental characterization of peptides designed to be complementary to the α-sheet conformation observed in the simulations. We demonstrate inhibition of aggregation in two different amyloid systems, β-amyloid peptide (Aβ) and transthyretin, by these designed α-sheet peptides. When immobilized the α-sheet designs preferentially bind species from solutions enriched in the toxic conformer compared with non-aggregated, nontoxic species or mature fibrils. The designs display characteristic spectroscopic signatures distinguishing them from conventional secondary structures, supporting α-sheet as a structure involved in the toxic oligomer stage of amyloid formation and paving the way for novel therapeutics and diagnostics. The build up of very thin fibres called amyloid fibrils is known to lead to more than 40 different human diseases, including Parkinson’s disease and rheumatoid arthritis. These diseases involve soluble proteins or peptides joining other proteins or peptides to form the fibrils, which are not soluble. However, the damage is done by the time the fibrils form because soluble intermediate structures formed by the proteins and peptides are toxic. The development of methods that can detect these toxic intermediate structures could lead to earlier interventions before significant damage. Amyloid fibrils are known to have a beta-sheet structure that is found in many protein systems. In 2004, based on computer simulations, researchers predicted that proteins and peptides that go on to form amyloid fibrils would pass through a related but less stable structure called an alpha-sheet, and that this structure would be toxic. Now Hopping et al., including some of the researchers involved in the 2004 work, have confirmed that the alpha-sheet structure is indeed involved in the formation of amyloid fibrils. To do this Hopping et al. designed peptides with alpha-sheet structures that could bind to the alpha-sheet structures predicted by their simulations. When these complementary designed peptides were added to a solution of peptide that causes Alzheimer’s Disease, or a protein that causes systemic amyloid disease, the designed peptides bound the toxic peptides or proteins and prevented the formation of fibrils. The results of Hopping et al. suggest that designed alpha-sheet compounds might be able to capture peptides and proteins that are implicated in a wide variety of amyloid diseases, independent of their composition and native structure, by targeting the intermediate alpha-sheet structure. Future challenges include showing that most proteins and peptides pass through this intermediate structure as they form fibrils, and improving the sensitivity of the binding in the hope of developing diagnostics for amyloid diseases.

Here, we compare the distributions of main chain (Φ,Ψ) angles (i.e., Ramachandran maps) of the 20 naturally occurring amino acids in three contexts: (i) molecular dynamics (MD) simulations of Gly-Gly-X-Gly-Gly pentapeptides in water at 298 K with exhaustive sampling, where X = the amino acid in question; (ii) 188 independent protein simulations in water at 298 K from our Dynameomics Project; and (iii) static crystal and NMR structures from the Protein Data Bank. The GGXGG peptide series is often used as a model of the unstructured denatured state of proteins. The sampling in the peptide MD simulations is neither random nor uniform. Instead, individual amino acids show preferences for particular conformations, but the peptide is dynamic, and interconversion between conformers is facile. For a given amino acid, the (Φ,Ψ) distributions in the protein simulations and the Protein Data Bank are very similar and often distinct from those in the peptide simulations. Comparison between the peptide and protein simulations shows that packing constraints, solvation, and the tendency for particular amino acids to be used for specific structural motifs can overwhelm the \"intrinsic propensities\" of amino acids for particular (Φ,Ψ) conformations. We also compare our helical propensities with experimental consensus values using the host-guest method, which appear to be determined largely by context and not necessarily the intrinsic conformational propensities of the guest residues. These simulations represent an improved coil library free from contextual effects to better model intrinsic conformational propensities and provide a detailed view of conformations making up the \"random coil\" state.