Prediction of amyloid aggregation in vivo

Mutations of Profilin-1 Associated with Amyotrophic Lateral Sclerosis Promote Aggregation Due to Structural Changes of Its Native State

The PFN1 gene, coding for profilin-1, has recently been associated with familial amyotrophic lateral sclerosis (fALS), as three mutations, namely C71G, M114T, and G118V, have been found in patients with familial forms of the disease and another, E117G, has been proposed to be a moderate risk factor for disease onset. In this work, we have purified the four profilin-1 variants along with the wild-type protein. The resulting aggregates appear to be fibrillar, to have a weak binding to ThT, and to possess a significant amount of intermolecular β-sheet structure. Using ThT fluorescence assays, far-UV circular dichroism, and dynamic light scattering, we found that all four variants have an aggregation propensity higher than that of the wild-type counterpart. In particular, the C71G mutation was found to induce the most dramatic change in aggregation, followed by the G118V and M114T substitutions and then the E117G mutation. Such a propensity was found not to strictly correlate with the conformational stability in this group of profilin-1 variants, determined using both urea-induced denaturation at equilibrium and folding/unfolding kinetics. However, it correlated with structural changes of the folded states, as monitored with far-UV circular dichroism, intrinsic fluorescence spectroscopy, ANS binding, acrylamide quenching, and dynamic light scattering. Overall, the results suggest that all four mutations increase the tendency of profilin-1 to aggregate and that such aggregation behavior is largely determined by the mutation-induced structural changes occurring in the folded state of the protein.

Prediction of Peptide and Protein Propensity for Amyloid Formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔG° values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation.

Mechanisms of amyloid formation revealed by solution NMR

Amyloid fibrils are proteinaceous elongated aggregates involved in more than fifty human diseases. Recent advances in electron microscopy and solid state NMR have allowed the characterization of fibril structures to different extents of refinement. However, structural details about the mechanism of fibril formation remain relatively poorly defined. This is mainly due to the complex, heterogeneous and transient nature of the species responsible for assembly; properties that make them difficult to detect and characterize in structural detail using biophysical techniques. The ability of solution NMR spectroscopy to investigate exchange between multiple protein states, to characterize transient and low-population species, and to study high molecular weight assemblies, render NMR an invaluable technique for studies of amyloid assembly. In this article we review state-of-the-art solution NMR methods for investigations of: (a) protein dynamics that lead to the formation of aggregation-prone species; (b) amyloidogenic intrinsically disordered proteins; and (c) protein-protein interactions on pathway to fibril formation. Together, these topics highlight the power and potential of NMR to provide atomic level information about the molecular mechanisms of one of the most fascinating problems in structural biology.

Predicting aggregation-prone sequences in proteins

Owing to its association with a diverse range of human diseases, the determinants of protein aggregation are studied intensively. It is generally accepted that the effective aggregation tendency of a protein depends on many factors such as folding efficiency towards the native state, thermodynamic stability of that conformation, intrinsic aggregation propensity of the polypeptide sequence and its ability to be recognized by the protein quality control system. The intrinsic aggregation propensity of a polypeptide sequence is related to the presence of short APRs (aggregation-prone regions) that self-associate to form intermolecular β-structured assemblies. These are typically short sequence segments (5-15 amino acids) that display high hydrophobicity, low net charge and a high tendency to form β-structures. As the presence of such APRs is a prerequisite for aggregation, a plethora of methods have been developed to identify APRs in amino acid sequences. In the present chapter, the methodological basis of these approaches is discussed, as well as some practical applications.

Distinct role of hydration water in protein misfolding and aggregation revealed by fluctuating thermodynamics analysis

Protein aggregation in aqueous cellular environments is linked to diverse human diseases. Protein aggregation proceeds through a multistep process initiated by conformational transitions, called protein misfolding, of monomer species toward aggregation-prone structures. Various forms of aggregate species are generated through the association of misfolded monomers including soluble oligomers and amyloid fibrils. Elucidating the molecular mechanisms and driving forces involved in the misfolding and subsequent association has been a central issue for understanding and preventing protein aggregation diseases such as Alzheimer's, Parkinson's, and type II diabetes. In this Account, we provide a thermodynamic perspective of the misfolding and aggregation of the amyloid-beta (Aβ) protein implicated in Alzheimer's disease through the application of fluctuating thermodynamics. This approach "dissects" the conventional thermodynamic characterization of the end states into the one of the fluctuating processes connecting them, and enables one to analyze variations in the thermodynamic functions that occur during the course of protein conformational changes. The central quantity in this approach is the solvent-averaged effective energy, f = Eu + Gsolv, comprising the protein potential energy (Eu) and the solvation free energy (Gsolv), whose time variation reflects the protein dynamics on the free energy landscape. Protein configurational entropy is quantified by the magnitude of fluctuations in f. We find that misfolding of the Aβ monomer when released from a membrane environment to an aqueous phase is driven by favorable changes in protein potential energy and configurational entropy, but it is also accompanied by an unfavorable increase in solvation free energy. The subsequent dimerization of the misfolded Aβ monomers occurs in two steps. The first step, where two widely separated monomers come into contact distance, is driven by water-mediated attraction, that is, by a decrease in solvation free energy, harnessing the monomer solvation free energy earned during the misfolding. The second step, where a compact dimer structure is formed, is driven by direct protein-protein interactions, but again it is accompanied by an increase in solvation free energy. The increased solvation free energy of the dimer will function as the driving force to recruit another Aβ protein in the approach stage of subsequent oligomerizations. The fluctuating thermodynamics analysis of the misfolding and dimerization of the Aβ protein indicates that the interaction of the protein with surrounding water plays a critical role in protein aggregation. Such a water-centric perspective is further corroborated by demonstrating that, for a large number of Aβ mutants and mutants of other protein systems, the change in the experimental aggregation propensity upon mutation has a significant correlation with the protein solvation free energy change. We also find striking discrimination between the positively and negatively charged residues on the protein surface by surrounding water molecules, which is shown to play a crucial role in determining the protein aggregation propensity. We argue that the protein total charge dictates such striking behavior of the surrounding water molecules. Our results provide new insights for understanding and predicting the protein aggregation propensity, thereby offering novel design principles for producing aggregation-resistant proteins for biotherapeutics.

AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures

Protein aggregation underlies an increasing number of disorders and constitutes a major bottleneck in the development of therapeutic proteins. Our present understanding on the molecular determinants of protein aggregation has crystalized in a series of predictive algorithms to identify aggregation-prone sites. A majority of these methods rely only on sequence. Therefore, they find difficulties to predict the aggregation properties of folded globular proteins, where aggregation-prone sites are often not contiguous in sequence or buried inside the native structure. The AGGRESCAN3D (A3D) server overcomes these limitations by taking into account the protein structure and the experimental aggregation propensity scale from the well-established AGGRESCAN method. Using the A3D server, the identified aggregation-prone residues can be virtually mutated to design variants with increased solubility, or to test the impact of pathogenic mutations. Additionally, A3D server enables to take into account the dynamic fluctuations of protein structure in solution, which may influence aggregation propensity. This is possible in A3D Dynamic Mode that exploits the CABS-flex approach for the fast simulations of flexibility of globular proteins. The A3D server can be accessed at http://biocomp.chem.uw.edu.pl/A3D/.

Predicting the aggregation propensity of prion sequences

The presence of prions can result in debilitating and neurodegenerative diseases in mammals and protein-based genetic elements in fungi. Prions are defined as a subclass of amyloids in which the self-aggregation process becomes self-perpetuating and infectious. Like all amyloids, prions polymerize into fibres with a common core formed of β-sheet structures oriented perpendicular to the fibril axes which form a structure known as a cross-β structure. The intermolecular β-sheet propensity, a characteristic of the amyloid pattern, as well as other key parameters of amyloid fibril formation can be predicted. Mathematical algorithms have been proposed to predict both amyloid and prion propensities. However, it has been shown that the presence of amyloid-prone regions in a polypeptide sequence could be insufficient for amyloid formation. It has also often been stated that the formation of amyloid fibrils does not imply that these are prions. Despite these limitations, in silico prediction of amyloid and prion propensities should help detect potential new prion sequences in mammals. In addition, the determination of amyloid-prone regions in prion sequences could be very useful in understanding the effect of sporadic mutations and polymorphisms as well as in the search for therapeutic targets.

Supersaturation is a major driving force for protein aggregation in neurodegenerative diseases

The solubility of proteins is an essential requirement for their function. Nevertheless, these ubiquitous molecules can undergo aberrant aggregation when the protein homeostasis system becomes impaired. Here we ask: what are the driving forces for protein aggregation in the cellular environment? Emerging evidence suggests that this phenomenon arises at least in part because the native states of many proteins are inherently metastable when their cellular concentrations exceed their critical values. Such 'supersaturated' proteins, which form a 'metastable subproteome', are strongly driven towards aggregation, and are over-represented in specific biochemical pathways associated with neurodegenerative conditions. These observations suggest that effective therapeutic approaches designed to combat neurodegenerative diseases could be aimed at enhancing the ability of the cell to maintain the homeostasis of the metastable subproteome.

Characterization of amyloid-like properties in bacterial intracellular aggregates

Protein aggregation into amyloid conformations is associated with more than 50 different human disorders. Recent studies demonstrate that the expression in bacteria of amyloid proteins results in the formation of intracellular aggregates structurally related to those underlying human diseases. The ease with which prokaryotic organisms can be genetically and biochemically manipulated makes them useful systems for studying how and why protein aggregates inside the cell, providing a tractable environment to rationally model in vivo amyloid formation. In this chapter we present an overview of the methods used to characterize the kinetic, structural, and functional properties of amyloid-like bacterial intracellular aggregates and how they can be employed to screen for lead compounds that might modulate amyloid deposition.

Biochemical properties and aggregation propensity of transforming growth factor-induced protein (TGFBIp) and the amyloid forming mutants

TGFBI-associated corneal dystrophies are characterized by accumulation of insoluble deposits of the mutant protein transforming growth factor β-induced protein (TGFBIp) in the cornea. Depending on the nature of mutation, the lesions appear as granular (non-amyloid) or lattice lines (amyloid) in the Bowman's layer or in the stroma. This review article emphasizes the structural biology aspects of TGFBIp. We discuss the tinctorial properties and ultrastructure of deposits observed in granular and lattice corneal dystrophic mutants with amyloid and non-amyloid forms of other human protein deposition diseases and review the biochemical and putative functional role of the protein. Using bioinformatics tools, we identify intrinsic aggregation propensity and discuss the possible protective role of gatekeepers close to the "aggregation-prone" regions of native TGFBIp. We describe the relative aggregation rates of lattice corneal dystrophy (LCD) and granular corneal dystrophy (GCD2) mutants using the three-parameter model, which is based on intrinsic properties of polypeptide chains. The predictive power of this model is compared with two other algorithms. We conclude that the model is able to predict the aggregation rate of mutants which do not alter overall net charge of the protein. The need to understand the mechanism of corneal dystrophies from the structural biology viewpoint is emphasized.

Association between foldability and aggregation propensity in small disulfide-rich proteins

AIMS

Disulfide-rich domains (DRDs) are small proteins whose native structure is stabilized by the presence of covalent disulfide bonds. These domains are versatile and can perform a wide range of functions. Many of these domains readily unfold on disulfide bond reduction, suggesting that in the absence of covalent bonding they might display significant disorder.

RESULTS

Here, we analyzed the degree of disorder in 97 domains representative of the different DRDs families and demonstrate that, in terms of sequence, many of them can be classified as intrinsically disordered proteins (IDPs) or contain predicted disordered regions. The analysis of the aggregation propensity of these domains indicates that, similar to IDPs, their sequences are more soluble and have less aggregating regions than those of other globular domains, suggesting that they might have evolved to avoid aggregation after protein synthesis and before they can attain its compact and covalently linked native structure.

INNOVATION AND CONCLUSION

DRDs, which resemble IDPs in the reduced state and become globular when their disulfide bonds are formed, illustrate the link between protein folding and aggregation propensities and how these two properties cannot be easily dissociated, determining the main traits of the folding routes followed by these small proteins to attain their native oxidized states.

Amyloidogenic mutations in human apolipoprotein A-I are not necessarily destabilizing - a common mechanism of apolipoprotein A-I misfolding in familial amyloidosis and atherosclerosis

High-density lipoproteins and their major protein, apolipoprotein A-I (apoA-I), remove excess cellular cholesterol and protect against atherosclerosis. However, in acquired amyloidosis, nonvariant full-length apoA-I deposits as fibrils in atherosclerotic plaques; in familial amyloidosis, N-terminal fragments of variant apoA-I deposit in vital organs, damaging them. Recently, we used the crystal structure of Δ(185-243)apoA-I to show that amyloidogenic mutations destabilize apoA-I and increase solvent exposure of the extended strand 44-55 that initiates β-aggregation. In the present study, we test this hypothesis by exploring naturally occurring human amyloidogenic mutations, W50R and G26R, within or close to this strand. The mutations caused small changes in the protein's α-helical content, stability, proteolytic pattern and protein-lipid interactions. These changes alone were unlikely to account for amyloidosis, suggesting the importance of other factors. Sequence analysis predicted several amyloid-prone segments that can initiate apoA-I misfolding. Aggregation studies using N-terminal fragments verified this prediction experimentally. Three predicted N-terminal amyloid-prone segments, mapped on the crystal structure, formed an α-helical cluster. Structural analysis indicates that amyloidogenic mutations or Met86 oxidation perturb native packing in this cluster. Taken together, the results suggest that structural perturbations in the amyloid-prone segments trigger α-helix to β-sheet conversion in the N-terminal ~ 75 residues forming the amyloid core. Polypeptide outside this core can be proteolysed to form 9-11 kDa N-terminal fragments found in familial amyloidosis. Our results imply that apoA-I misfolding in familial and acquired amyloidosis follows a similar mechanism that does not require significant structural destabilization or proteolysis. This novel mechanism suggests potential therapeutic interventions for apoA-I amyloidosis.

Intermolecular β-strand networks avoid hub residues and favor low interconnectedness: a potential protection mechanism against chain dissociation upon mutation

Altogether few protein oligomers undergo a conformational transition to a state that impairs their function and leads to diseases. But when it happens, the consequences are not harmless and the so-called conformational diseases pose serious public health problems. Notorious examples are the Alzheimer's disease and some cancers associated with a conformational change of the amyloid precursor protein (APP) and of the p53 tumor suppressor, respectively. The transition is linked with the propensity of β-strands to aggregate into amyloid fibers. Nevertheless, a huge number of protein oligomers associate chains via β-strand interactions (intermolecular β-strand interface) without ever evolving into fibers. We analyzed the layout of 1048 intermolecular β-strand interfaces looking for features that could provide the β-strands resistance to conformational transitions. The interfaces were reconstructed as networks with the residues as the nodes and the interactions between residues as the links. The networks followed an exponential decay degree distribution, implying an absence of hubs and nodes with few links. Such layout provides robustness to changes. Few links per nodes do not restrict the choices of amino acids capable of making an interface and maintain high sequence plasticity. Few links reduce the “bonding” cost of making an interface. Finally, few links moderate the vulnerability to amino acid mutation because it entails limited communication between the nodes. This confines the effects of a mutation to few residues instead of propagating them to many residues via hubs. We propose that intermolecular β-strand interfaces are organized in networks that tolerate amino acid mutation to avoid chain dissociation, the first step towards fiber formation. This is tested by looking at the intermolecular β-strand network of the p53 tetramer.

Computational approaches to understanding protein aggregation in neurodegeneration

The generation of toxic non-native protein conformers has emerged as a unifying thread among disorders such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Atomic-level detail regarding dynamical changes that facilitate protein aggregation, as well as the structural features of large-scale ordered aggregates and soluble non-native oligomers, would contribute significantly to current understanding of these complex phenomena and offer potential strategies for inhibiting formation of cytotoxic species. However, experimental limitations often preclude the acquisition of high-resolution structural and mechanistic information for aggregating systems. Computational methods, particularly those combine both all-atom and coarse-grained simulations to cover a wide range of time and length scales, have thus emerged as crucial tools for investigating protein aggregation. Here we review the current state of computational methodology for the study of protein self-assembly, with a focus on the application of these methods toward understanding of protein aggregates in human neurodegenerative disorders.

Interaction with the surrounding water plays a key role in determining the aggregation propensity of proteins

Understanding the molecular determinants of the relative propensities of proteins to aggregate in a cellular environment is a central issue for treating protein-aggregation diseases and developing peptide-based therapeutics. Despite the expectation that protein aggregation can largely be attributed to direct protein-protein interactions, a crucial role the surrounding water in determining the aggregation propensity of proteins both in vitro and in vivo was identified. The overall protein hydrophobicity, defined solely by the hydration free energy of a protein in its monomeric state sampling its equilibrium structures, was shown to be the predominant determinant of protein aggregation propensity in aqueous solution. Striking discrimination of positively and negatively charged residues by the surrounding water was also found. This effect depends on the protein net charge and plays a crucial role in regulating the solubility of the protein. These results pave the way for the design of aggregation-resistant proteins as biotherapeutics.

Computational and theoretical methods for protein folding

A computational approach is essential whenever the complexity of the process under study is such that direct theoretical or experimental approaches are not viable. This is the case for protein folding, for which a significant amount of data are being collected. This paper reports on the essential role of in silico methods and the unprecedented interplay of computational and theoretical approaches, which is a defining point of the interdisciplinary investigations of the protein folding process. Besides giving an overview of the available computational methods and tools, we argue that computation plays not merely an ancillary role but has a more constructive function in that computational work may precede theory and experiments. More precisely, computation can provide the primary conceptual clues to inspire subsequent theoretical and experimental work even in a case where no preexisting evidence or theoretical frameworks are available. This is cogently manifested in the application of machine learning methods to come to grips with the folding dynamics. These close relationships suggested complementing the review of computational methods within the appropriate theoretical context to provide a self-contained outlook of the basic concepts that have converged into a unified description of folding and have grown in a synergic relationship with their computational counterpart. Finally, the advantages and limitations of current computational methodologies are discussed to show how the smart analysis of large amounts of data and the development of more effective algorithms can improve our understanding of protein folding.

MetAmyl: a METa-predictor for AMYLoid proteins

The aggregation of proteins or peptides in amyloid fibrils is associated with a number of clinical disorders, including Alzheimer's, Huntington's and prion diseases, medullary thyroid cancer, renal and cardiac amyloidosis. Despite extensive studies, the molecular mechanisms underlying the initiation of fibril formation remain largely unknown. Several lines of evidence revealed that short amino-acid segments (hot spots), located in amyloid precursor proteins act as seeds for fibril elongation. Therefore, hot spots are potential targets for diagnostic/therapeutic applications, and a current challenge in bioinformatics is the development of methods to accurately predict hot spots from protein sequences. In this paper, we combined existing methods into a meta-predictor for hot spots prediction, called MetAmyl for METapredictor for AMYLoid proteins. MetAmyl is based on a logistic regression model that aims at weighting predictions from a set of popular algorithms, statistically selected as being the most informative and complementary predictors. We evaluated the performances of MetAmyl through a large scale comparative study based on three independent datasets and thus demonstrated its ability to differentiate between amyloidogenic and non-amyloidogenic polypeptides. Compared to 9 other methods, MetAmyl provides significant improvement in prediction on studied datasets. We further show that MetAmyl is efficient to highlight the effect of point mutations involved in human amyloidosis, so we suggest this program should be a useful complementary tool for the diagnosis of these diseases.

Widespread aggregation and neurodegenerative diseases are associated with supersaturated proteins

The maintenance of protein solubility is a fundamental aspect of cellular homeostasis because protein aggregation is associated with a wide variety of human diseases. Numerous proteins unrelated in sequence and structure, however, can misfold and aggregate, and widespread aggregation can occur in living systems under stress or aging. A crucial question in this context is why only certain proteins appear to aggregate readily in vivo, whereas others do not. We identify here the proteins most vulnerable to aggregation as those whose cellular concentrations are high relative to their solubilities. We find that these supersaturated proteins represent a metastable subproteome involved in pathological aggregation during stress and aging and are overrepresented in biochemical processes associated with neurodegenerative disorders. Consequently, such cellular processes become dysfunctional when the ability to keep intrinsically supersaturated proteins soluble is compromised. Thus, the simultaneous analysis of abundance and solubility can rationalize the diverse cellular pathologies linked to neurodegenerative diseases and aging.

N-terminally truncated forms of human cathepsin F accumulate in aggresome-like inclusions

The contribution of individual cysteine cathepsins as positive mediators of programmed cell death is dependent on several factors, such as the type of stimuli, intensity and duration of the stimulus, and cell type involved. Of the eleven human cysteine cathepsins, cathepsin F is the only cathepsin that exhibits an extended N-terminal proregion, which contains a cystatin-like domain. We predicted that the wild-type human cathepsin F contains three natively disordered regions within the enzyme's propeptide and various amino acid stretches with high fibrillation propensity. Wild-type human cathepsin F and its N-terminally truncated forms, Ala(20)-Asp(484) (Δ(19)CatF), Pro(126)-Asp(484) (Δ(125)CatF), and Met(147)-Asp(484) (Δ(146)CatF) were cloned into the pcDNA3 vector and overexpressed in HEK 293T cells. Wild-type human cathepsin F displayed a clear vesicular labeling and colocalized with the LAMP2 protein, a lysosomal marker. However, all three N-terminally truncated forms of human cathepsin F were recovered as insoluble proteins, suggesting that the deletion of at least the signal peptides (Δ(19)CatF), results in protein aggregation. Noteworthy, they concentrated large perinuclear-juxtanuclear aggregates that accumulated within aggresome-like inclusions. These inclusions showed p62-positive immunoreactivity and were colocalized with the autophagy marker LC3B, but not with the LAMP2 protein. In addition, an approximately 2-3 fold increase in DEVDase activity was not sufficient to induce apoptotic cell death. These results suggested the clearance of the N-terminally truncated forms of human cathepsin F via the autophagy pathway, underlying its protective and prosurvival mechanisms.

Effect of metal loading and subcellular pH on net charge of superoxide dismutase-1

The net charge of a folded protein is hypothesized to influence myriad biochemical processes (e.g., protein misfolding, electron transfer, molecular recognition); however, few tools exist for measuring net charge and this elusive property remains undetermined--at any pH--for nearly all proteins. This study used lysine-acetyl "protein charge ladders" and capillary electrophoresis to measure the net charge of superoxide dismutase-1 (SOD1)--whose aggregation causes amyotrophic lateral sclerosis (ALS)--as a function of coordinated metal ions and pH. The net negative charge of apo-SOD1 was similar to predicted values; however, the binding of a single Zn(2+) or Cu(2+) ion reduced the net negative charge by a greater magnitude than predicted (i.e., ~4 units, instead of 2), whereas the SOD1 protein underwent charge regulation upon binding 2-4 metal ions. From pH5 to pH8 (i.e., a range consistent with the multiple subcellular loci of SOD1), the holo-SOD1 protein underwent smaller fluctuations in net negative charge than predicted (i.e., ~3 units, instead of ~14) and did not undergo charge inversion at its isoelectric point (pI=5.3) but remained anionic. The regulation of SOD1 net charge along its pathways of metal binding, and across solvent pH, provides insight into its metal-induced maturation and enzymatic activity (which remains diffusion-limited across pH5-8). The anionic nature of holo-SOD1 across subcellular pH suggests that ~45 different ALS-linked mutations to SOD1 will reduce its net negative charge regardless of subcellular localization.

Protein aggregation propensity is a crucial determinant of intracellular inclusion formation and quality control degradation

Protein aggregation is linked to many pathological conditions, including several neurodegenerative diseases. The aggregation propensities of proteins are thought to be controlled to a large extent by the physicochemical properties encoded in the primary sequence. We have previously exploited a set of amyloid β peptide (Aβ42) variants exhibiting a continuous gradient of intrinsic aggregation propensities to demonstrate that this rule applies in vivo in bacteria. In the present work we have characterized the behavior of these Aβ42 mutants when expressed in yeast. In contrast to bacteria, the intrinsic aggregation propensity is gated by yeast, in such a way that this property correlates with the formation of intracellular inclusions only above a specific aggregation threshold. Proteins displaying solubility levels above this threshold escape the inclusion formation pathway. In addition, the most aggregation-prone variants are selectively cleared by the yeast quality control degradation machinery. Thus, both inclusion formation and proteolysis target the same aggregation-prone variants and cooperate to minimize the presence of these potentially dangerous species in the cytosol. The demonstration that sorting to these pathways in eukaryotes is strongly influenced by protein primary sequence should facilitate the development of rational approaches to predict and hopefully prevent in vivo protein deposition.

Microcanonical thermostatistics of coarse-grained proteins with amyloidogenic propensity

The formation of fibrillar aggregates seems to be a common characteristic of polypeptide chains, although the observation of these aggregates may depend on appropriate experimental conditions. Partially folded intermediates seem to have an important role in the generation of protein aggregates, and a mechanism for this fibril formation considers that these intermediates also correspond to metastable states with respect to the fibrillar ones. Here, using a coarse-grained (CG) off-lattice model, we carry out a comparative analysis of the thermodynamic aspects characterizing the folding transition with respect to the propensity for aggregation of four different systems: two isoforms of the amyloid β-protein, the Src SH3 domain, and the human prion proteins (hPrP). Microcanonical analysis of the data obtained from replica exchange method is conducted to evaluate the free-energy barrier and latent heat in these models. The simulations of the amyloid β isoforms and Src SH3 domain indicated that the folding process described by this CG model is related to a negative specific heat, a phenomenon that can only be verified in the microcanonical ensemble in first-order phase transitions. The CG simulation of the hPrP heteropolymer yielded a continuous folding transition. The absence of a free-energy barrier and latent heat favors the presence of partially unfolded conformations, and in this context, this thermodynamic aspect could explain the reason why the hPrP heteropolymer is more aggregation-prone than the other heteropolymers considered in this study. We introduced the hydrophobic radius of gyration as an order parameter and found that it can be used to obtain reliable information about the hydrophobic packing and the transition temperatures in the folding process.

Myelin membrane assembly is driven by a phase transition of myelin basic proteins into a cohesive protein meshwork

Rapid conduction of nerve impulses requires coating of axons by myelin. To function as an electrical insulator, myelin is generated as a tightly packed, lipid-rich multilayered membrane sheath. Knowledge about the mechanisms that govern myelin membrane biogenesis is required to understand myelin disassembly as it occurs in diseases such as multiple sclerosis. Here, we show that myelin basic protein drives myelin biogenesis using weak forces arising from its inherent capacity to phase separate. The association of myelin basic protein molecules to the inner leaflet of the membrane bilayer induces a phase transition into a cohesive mesh-like protein network. The formation of this protein network shares features with amyloid fibril formation. The process is driven by phenylalanine-mediated hydrophobic and amyloid-like interactions that provide the molecular basis for protein extrusion and myelin membrane zippering. These findings uncover a physicochemical mechanism of how a cytosolic protein regulates the morphology of a complex membrane architecture. These results provide a key mechanism in myelin membrane biogenesis with implications for disabling demyelinating diseases of the central nervous system.

Distinct position-specific sequence features of hexa-peptides that form amyloid-fibrils: application to discriminate between amyloid fibril and amorphous β-aggregate forming peptide sequences

Background

Comparison of short peptides which form amyloid-fibrils with their homologues that may form amorphous β-aggregates but not fibrils, can aid development of novel amyloid-containing nanomaterials with well defined morphologies and characteristics. The knowledge gained from the comparative analysis could also be applied towards identifying potential aggregation prone regions in proteins, which are important for biotechnology applications or have been implicated in neurodegenerative diseases. In this work we have systematically analyzed a set of 139 amyloid-fibril hexa-peptides along with a highly homologous set of 168 hexa-peptides that do not form amyloid fibrils for their position-wise as well as overall amino acid compositions and averages of 49 selected amino acid properties.

Results

Amyloid-fibril forming peptides show distinct preferences and avoidances for amino acid residues to occur at each of the six positions. As expected, the amyloid fibril peptides are also more hydrophobic than non-amyloid peptides. We have used the results of this analysis to develop statistical potential energy values for the 20 amino acid residues to occur at each of the six different positions in the hexa-peptides. The distribution of the potential energy values in 139 amyloid and 168 non-amyloid fibrils are distinct and the amyloid-fibril peptides tend to be more stable (lower total potential energy values) than non-amyloid peptides. The average frequency of occurrence of these peptides with lower than specific cutoff energies at different positions is 72% and 50%, respectively. The potential energy values were used to devise a statistical discriminator to distinguish between amyloid-fibril and non-amyloid peptides. Our method could identify the amyloid-fibril forming hexa-peptides to an accuracy of 89%. On the other hand, the accuracy of identifying non-amyloid peptides was only 54%. Further attempts were made to improve the prediction accuracy via machine learning. This resulted in an overall accuracy of 82.7% with the sensitivity and specificity of 81.3% and 83.9%, respectively, in 10-fold cross-validation method.

Conclusions

Amyloid-fibril forming hexa-peptides show position specific sequence features that are different from those which may form amorphous β-aggregates. These positional preferences are found to be important features for discriminating amyloid-fibril forming peptides from their homologues that don't form amyloid-fibrils.

The N-terminal helix controls the transition between the soluble and amyloid states of an FF domain

Background

Protein aggregation is linked to the onset of an increasing number of human nonneuropathic (either localized or systemic) and neurodegenerative disorders. In particular, misfolding of native α-helical structures and their self-assembly into nonnative intermolecular β-sheets has been proposed to trigger amyloid fibril formation in Alzheimer’s and Parkinson’s diseases.

Methods

Here, we use a battery of biophysical techniques to elucidate the conformational conversion of native α-helices into amyloid fibrils using an all-α FF domain as a model system.

Results

We show that under mild denaturing conditions at low pH this FF domain self-assembles into amyloid fibrils. Theoretical and experimental dissection of the secondary structure elements in this domain indicates that the helix 1 at the N-terminus has both the highest α-helical and amyloid propensities, controlling the transition between soluble and aggregated states of the protein.

Conclusions

The data illustrates the overlap between the propensity to form native α-helices and amyloid structures in protein segments.

Significance

The results presented contribute to explain why proteins cannot avoid the presence of aggregation-prone regions and indeed use stable α-helices as a strategy to neutralize such potentially deleterious stretches.

Amyloidogenic peptides of yeast cell wall glucantransferase Bgl2p as a model for the investigation of its pH-dependent fibril formation

The pH-dependence of the ability of Bgl2p to form fibrils was studied using synthetic peptides with potential amyloidogenic determinants (PADs) predicted in the Bgl2p sequence. Three PADs, FTIFVGV, SWNVLVA and NAFS, were selected on the basis of combination of computational algorithms. Peptides AEGFTIFVGV, VDSWNVLVAG and VMANAFSYWQ, containing these PADs, were synthesized. It was demonstrated that these peptides had an ability to fibrillate at pH values from 3.2 to 5.0. The PAD-containing peptides, except for VDSWNVLVAG, could fibrillate also at pH values from pH 5.0 to 7.6. We supposed that the ability of Bgl2p to form fibrils most likely depended on the coordination of fibrillation activity of the PAD-containing areas and Bgl2p could fibrillate at mild acid and neutral pH values and lose the ability to fibrillate with the increasing of pH values. It was demonstrated that Bgl2p was able to fibrillate at pH value 5.0, to form fibrils of various morphology at neutral pH values and lost the fibrillation ability at pH value 7.6. The results obtained allowed us to suggest a new simple approach for the isolation of Bgl2p from Saccharomyces cerevisiae cell wall.

Protein aggregation profile of the human kinome

Protein aggregation into amyloid fibrils is associated with the onset of an increasing number of human disorders, including Alzheimer's disease, diabetes, and some types of cancer. The ability to form toxic amyloids appears to be a property of most polypeptides. Accordingly, it has been proposed that reducing aggregation and its effect in cell fitness is a driving force in the evolution of proteins sequences. This control of protein solubility should be especially important for regulatory hubs in biological networks, like protein kinases. These enzymes are implicated in practically all processes in normal and abnormal cell physiology, and phosphorylation is one of the most frequent protein modifications used to control protein activity. Here, we use the AGGRESCAN algorithm to study the aggregation propensity of kinase sequences. We compared them with the rest of globular proteins to decipher whether they display differential aggregation properties. In addition, we compared the human kinase complement with the kinomes of other organisms to see if we can identify any evolutionary trend in the aggregational properties of this protein superfamily. Our analysis indicates that kinase domains display significant aggregation propensity, a property that decreases with increasing organism complexity.

A rationally designed six-residue swap generates comparability in the aggregation behavior of α-synuclein and β-synuclein

The aggregation process of α-synuclein, a protein closely associated with Parkinson's disease, is highly sensitive to sequence variations. It is therefore of great importance to understand the factors that define the aggregation propensity of specific mutational variants as well as their toxic behavior in the cellular environment. In this context, we investigated the extent to which the aggregation behavior of α-synuclein can be altered to resemble that of β-synuclein, an aggregation-resistant homologue of α-synuclein not associated with disease, by swapping residues between the two proteins. Because of the vast number of possible swaps, we have applied a rational design procedure to single out a mutational variant, called α2β, in which two short stretches of the sequence in the NAC region have been replaced in α-synuclein from β-synuclein. We find not only that the aggregation rate of α2β is close to that of β-synuclein, being much lower than that of α-synuclein, but also that α2β effectively changes the cellular toxicity of α-synuclein to a value similar to that of β-synuclein upon exposure of SH-SY5Y cells to preformed oligomers. Remarkably, control experiments on the corresponding mutational variant of β-synuclein, called β2α, confirmed that the mutations that we have identified also shift the aggregation behavior of this protein toward that of α-synuclein. These results demonstrate that it is becoming possible to control in quantitative detail the sequence code that defines the aggregation behavior and toxicity of α-synuclein.

Thermodynamic stability, unfolding kinetics, and aggregation of the N-terminal actin-binding domains of utrophin and dystrophin

Muscular dystrophy (MD) is the most common genetic lethal disorder in children. Mutations in dystrophin trigger the most common form of MD, Duchenne, and its allelic variant Becker MD. Utrophin is the closest homologue and has been shown to compensate for the loss of dystrophin in human disease animal models. However, the structural and functional similarities and differences between utrophin and dystrophin are less understood. Both proteins interact with actin through their N-terminal actin-binding domain (N-ABD). In this study, we examined the thermodynamic stability and aggregation of utrophin N-ABD and compared with that of dystrophin. Our results show that utrophin N-ABD has spectroscopic properties similar to dystrophin N-ABD. However, utrophin N-ABD has decreased denaturant and thermal stability, unfolds faster, and is correspondingly more susceptible to proteolysis, which might account for its decreased in vivo half-life compared to dystrophin. In addition, utrophin N-ABD aggregates to a lesser extent compared with dystrophin N-ABD, contrary to the general behavior of proteins in which decreased stability enhances protein aggregation. Despite these differences in stability and aggregation, both proteins exhibit deleterious effects of mutations. When utrophin N-ABD mutations analogous in position to the dystrophin disease-causing mutations were generated, they behaved similarly to dystrophin mutants in terms of decreased stability and the formation of cross-β aggregates, indicating a possible role for utrophin mutations in disease mechanisms.

Fibrillization propensity for short designed hexapeptides predicted by computer simulation

Assembly of normally soluble proteins into ordered aggregates, known as amyloid fibrils, is a cause or associated symptom of numerous human disorders, including Alzheimer's and the prion diseases. Here, we test the ability of discontinuous molecular dynamics (DMD) simulations based on PRIME20, a new intermediate-resolution protein force field, to predict which designed hexapeptide sequences will form fibrils, which will not, and how this depends on temperature and concentration. Simulations were performed on 48-peptide systems containing STVIIE, STVIFE, STVIVE, STAIIE, STVIAE, STVIGE, and STVIEE starting from random-coil configurations. By the end of the simulations, STVIIE and STVIFE (which form fibrils in vitro) form fibrils over a range of temperatures, STVIEE (which does not form fibrils in vitro) does not form fibrils, and STVIVE, STAIIE, STVIAE, and STVIGE (which do not form fibrils in vitro) form fibrils at lower temperatures but stop forming fibrils at higher temperatures. At the highest temperatures simulated, the results on the fibrillization propensity of the seven short de novo designed peptides all agree with the experiments of López de la Paz and Serrano. Our results suggest that the fibrillization temperature (temperature above which fibrils cease to form) is a measure of fibril stability and that by rank ordering the fibrillization temperatures of various sequences, PRIME20/DMD simulations could be used to ascertain their relative fibrillization propensities. A phase diagram showing regions in the temperature-concentration plane where fibrils are formed in our simulations is presented.

Sequence-based prediction of protein solubility

In order to investigate the relationship between the thermodynamics and kinetics of protein aggregation, we compared the solubility of proteins with their aggregation rates. We found a significant correlation between these two quantities by considering a database of protein solubility values measured using an in vitro reconstituted translation system containing about 70% of Escherichia coli proteins. The existence of such correlation suggests that the thermodynamic stability of the native states of proteins relative to the aggregate states is closely linked with the kinetic barriers that separate them. In order to create the possibility of conducting computational studies at the proteome level to investigate further this concept, we developed a method of predicting the solubility of proteins based on their physicochemical properties.

Interactions of AChE with Aβ Aggregates in Alzheimer's Brain: Therapeutic Relevance of IDN 5706

Acetylcholinesterase (AChE; EC 3.1.1.7) plays a crucial role in the rapid hydrolysis of the neurotransmitter acetylcholine, in the central and peripheral nervous system and might also participate in non-cholinergic mechanism related to neurodegenerative diseases. Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by a progressive deterioration of cognitive abilities, amyloid-β (Aβ) peptide accumulation and synaptic alterations. We have previously shown that AChE is able to accelerate the Aβ peptide assembly into Alzheimer-type aggregates increasing its neurotoxicity. Furthermore, AChE activity is altered in brain and blood of Alzheimer’s patients. The enzyme associated to amyloid plaques changes its enzymatic and pharmacological properties, as well as, increases its resistant to low pH, inhibitors and excess of substrate. Here, we reviewed the effects of IDN 5706, a hyperforin derivative that has potential preventive effects on the development of AD. Our results show that treatment with IDN 5706 for 10 weeks increases brain AChE activity in 7-month-old double transgenic mice (APP_SWE–PS1) and decreases the content of AChE associated with different types of amyloid plaques in this Alzheimer’s model. We concluded that early treatment with IDN 5706 decreases AChE–Aβ interaction and this effect might be of therapeutic interest in the treatment of AD.

The synaptic protein neuroligin-1 interacts with the amyloid β-peptide. Is there a role in Alzheimer's disease?

Amyloid β-peptide (Aβ) is the main component of the amyloid plaques associated with Alzheimer's disease (AD). In the early steps of the disease soluble Aβ oligomers are produced. According to the current "amyloid hypothesis" these oligomers can accumulate over time, leading progressively to the loss of synaptic function and the cognitive failure characteristic of AD. To understand the role of oligomeric Aβ species in AD pathology, it is important to understand the mechanism by which Aβ oligomers are targeted to synaptic junction. We report here the interaction between Aβ with neuroligin-1 (NL-1), a postsynaptic cell-adhesion protein specific for excitatory synapses, which shares a high degree of similarity with acetylcholinesterase, the first synaptic protein described to interact with Aβ. Using intrinsic fluorescence and surface plasmon resonance, we found that Aβ binds to the extracellular domain of NL-1 with a K(d) in the nanomolar range. In the case of NL-2, a postsynaptic cell-adhesion protein specific for inhibitory synapses, just a very weak interaction with Aβ was observed. Aβ polymerization analysis-studied by thioflavin-T assay and electron microscopy-indicated that NL-1 stabilized Aβ aggregates in vitro. Moreover, NL-1 acts as a nucleating factor during the Aβ aggregation process, stimulating the formation of Aβ oligomers. Besides, immunoprecipitation assays confirm that Aβ oligomers interact with NL-1 but not with NL-2. In conclusion, our results show that NL-1 interacts with Aβ increasing the formation of Aβ oligomers, suggesting that this interaction could triggers the targeting of Aβ oligomer to the postsynaptic regions of excitatory synapses.