The 3D profile method for identifying fibril-forming segments of proteins

Structures of segments of α-synuclein fused to maltose-binding protein suggest intermediate states during amyloid formation

Aggregates of the protein α-synuclein are the main component of Lewy bodies, the hallmark of Parkinson's disease. α-Synuclein aggregates are also found in many human neurodegenerative diseases known as synucleinopathies. In vivo, α-synuclein associates with membranes and adopts α-helical conformations. The details of how α-synuclein converts from the functional native state to amyloid aggregates remain unknown. In this study, we use maltose-binding protein (MBP) as a carrier to crystallize segments of α-synuclein. From crystal structures of fusions between MBP and four segments of α-synuclein, we have been able to trace a virtual model of the first 72 residues of α-synuclein. Instead of a mostly α-helical conformation observed in the lipid environment, our crystal structures show α-helices only at residues 1-13 and 20-34. The remaining segments are extended loops or coils. All of the predicted fiber-forming segments based on the 3D profile method are in extended conformations. We further show that the MBP fusion proteins with fiber-forming segments from α-synuclein can also form fiber-like nano-crystals or amyloid-like fibrils. Our structures suggest intermediate states during amyloid formation of α-synuclein.

Human beta-synuclein rendered fibrillogenic by designed mutations

Filamentous inclusions made of α-synuclein are found in nerve cells and glial cells in a number of human neurodegenerative diseases, including Parkinson disease, dementia with Lewy bodies, and multiple system atrophy. The assembly and spreading of these inclusions are likely to play an important role in the etiology of common dementias and movement disorders. Both α-synuclein and the homologous β-synuclein are abundantly expressed in the central nervous system; however, β-synuclein is not present in the pathological inclusions. Previously, we observed a poor correlation between filament formation and the presence of residues 73-83 of α-synuclein, which are absent in β-synuclein. Instead, filament formation correlated with the mean β-sheet propensity, charge, and hydrophilicity of the protein (global physicochemical properties) and β-strand contiguity calculated by a simple algorithm of sliding averages (local physicochemical property). In the present study, we rendered β-synuclein fibrillogenic via one set of point mutations engineered to enhance global properties and a second set engineered to enhance predominantly β-strand contiguity. Our findings show that the intrinsic physicochemical properties of synucleins influence their fibrillogenic propensity via two distinct but overlapping modalities. The implications for filament formation and the pathogenesis of neurodegenerative diseases are discussed.

Discriminating early stage A{beta}42 monomer structures using chirality-induced 2DIR spectroscopy in a simulation study

Elucidating the structural features of the Abeta monomer, the peptide constituent of amyloid fibrils found in Alzheimer's disease, can enable a direct characterization of aggregation pathways. Recent studies support the view that the ensemble of Abeta42 monomers is a mixture of diverse ordered and disordered conformational species, which can be classified according to the formation of a characteristic beta-hairpin conformation in a certain region. Despite the disparity in the structural features of these species, commonly used spectroscopic techniques such as NMR may not directly trace the conformational dynamics in the ensemble due to the limited time resolution and the lack of well-resolved spectral features for different comformers. Here we use molecular dynamics simulations combined with simulations of two-dimensional IR (2DIR) spectra to investigate the structure of these species, their interchange kinetics, and their spectral features. We show that while the discrimination efficiency of the ordinary, nonchiral 2DIR signal is limited due to its intrinsic dependence on common order parameters that are dominated by the generally unstructured part of the sequence, signals with carefully designed chirality-sensitive pulse configurations have the high resolution required for differentiating the various monomer structures. Our combined simulation studies indicate the power of the chirality-induced (CI) 2DIR technique in investigating early events in Abeta42 aggregation and open the possibility for their use as a novel experimental tool.

Protein folding and aggregation in bacteria

Proteins might experience many conformational changes and interactions during their lifetimes, from their synthesis at ribosomes to their controlled degradation. Because, in most cases, only folded proteins are functional, protein folding in bacteria is tightly controlled genetically, transcriptionally, and at the protein sequence level. In addition, important cellular machinery assists the folding of polypeptides to avoid misfolding and ensure the attainment of functional structures. When these redundant protective strategies are overcome, misfolded polypeptides are recruited into insoluble inclusion bodies. The protein embedded in these intracellular deposits might display different conformations including functional and beta-sheet-rich structures. The latter assemblies are similar to the amyloid fibrils characteristic of several human neurodegenerative diseases. Interestingly, bacteria exploit the same structural principles for functional properties such as adhesion or cytotoxicity. Overall, this review illustrates how prokaryotic organisms might provide the bedrock on which to understand the complexity of protein folding and aggregation in the cell.

Potential aggregation-prone regions in complementarity-determining regions of antibodies and their contribution towards antigen recognition: a computational analysis

PURPOSE

To analyze contribution of short aggregation-prone regions (APRs), which may self-associate via cross-beta motif and were earlier identified in therapeutic mAbs, towards antigen recognition via structural analyses of antibody-antigen complexes.

METHODS

A dataset of 29 publically available high-resolution crystal structures of Fab-antigen complexes was collected. Contribution of APRs towards the surface areas of the Fabs buried by the cognate antigens was computed. Propensities of amino acids to occur in APRs and to be involved in antigen binding were compared. Coincidence between APRs and individual CDR loops was examined.

RESULTS

All Fabs in the dataset contain at least one APR in CDR loops and adjacent framework beta-strands. The average contribution of APRs towards buried surface area of Fabs is 16.0 +/- 10.7%. Aggregation and antigen recognition may be coupled via aromatic residues (Tyr, Trp), which occur with high propensities in both APRs and antigen binding sites. APRs are infrequent in the heavy chain CDR 3 (H3) loops (7%), but are frequent in H2 loops (45%).

CONCLUSIONS

Co-incidence of APRs with antigen recognition sites can potentially lead to the loss of function upon aggregation. Rational structure-based design or selection strategies are suggested for biotherapeutics with improved druggability while maintaining potency.

Practically useful: what the Rosetta protein modeling suite can do for you

The objective of this review is to enable researchers to use the software package Rosetta for biochemical and biomedicinal studies. We provide a brief review of the six most frequent research problems tackled with Rosetta. For each of these six tasks, we provide a tutorial that illustrates a basic Rosetta protocol. The Rosetta method was originally developed for de novo protein structure prediction and is regularly one of the best performers in the community-wide biennial Critical Assessment of Structure Prediction. Predictions for protein domains with fewer than 125 amino acids regularly have a backbone root-mean-square deviation of better than 5.0 Å. More impressively, there are several cases in which Rosetta has been used to predict structures with atomic level accuracy better than 2.5 Å. In addition to de novo structure prediction, Rosetta also has methods for molecular docking, homology modeling, determining protein structures from sparse experimental NMR or EPR data, and protein design. Rosetta has been used to accurately design a novel protein structure, predict the structure of protein−protein complexes, design altered specificity protein−protein and protein−DNA interactions, and stabilize proteins and protein complexes. Most recently, Rosetta has been used to solve the X-ray crystallographic phase problem.

The clustering and spatial arrangement of beta-sheet sequence, but not order, govern alpha-synuclein fibrillogenesis

The intrinsically unstructured protein alpha-synuclein (aS) is prone to misfold into cytotoxic beta-sheet-rich oligomers and amyloid fibrils that underlie the pathogenesis of Lewy body diseases such as Parkinson's disease. An important, recognized fibrillogenesis parameter is amino acid content, whereas the influence of amino acid sequence distribution is not as well understood. The fibril core of aS encompasses five regions of high beta-sheet propensity, termed beta1-beta5. Using four aS variants with identical amino acid compositions but rearranged pseudorepeat motifs, we show that beta2-beta5 sequence clustering, but not order, is important for efficient fibrillogenesis. For molecular species progressing toward the fibrillar state, order invariably increases; i.e., the spatial arrangement of sequence elements becomes restricted. By introducing disulfide bonds in a fibril structure-based manner, we demonstrated that a successful protofibril-to-fibril conversion is dependent upon the spatial arrangement of sequence elements of high beta-sheet propensity. Moreover, a disulfide-linked aS dimer is shown to fibrillize rapidly. We propose that a conformational search underlies the emergence of a fibrillar aS nucleus that is directed by gaps in sequence between beta-sheet regions and the accessible range of spatial beta-sheet arrangements in soluble, prefibrillar oligomers. On the basis of the universal cross-beta-sheet structure of amyloid fibrils, these principles are expected to apply to a wide range of amyloidogenic proteins.

Low-level expression of a folding-incompetent protein in Escherichia coli: search for the molecular determinants of protein aggregation in vivo

Aggregation of peptides and proteins into insoluble amyloid fibrils or related intracellular inclusions is the hallmark of many degenerative diseases, including Alzheimer's disease, Parkinson's disease, and various forms of amyloidosis. In spite of the considerable progress carried out in vitro in elucidating the molecular determinants of the conversion of purified and isolated proteins into amyloid fibrils, very little is known on factors governing this process in the complex environment of living organisms. Taking advantage of increasing evidence that bacterial inclusion bodies consist of amyloid-like aggregates, we have expressed in Escherichia coli both wild type and 21 single-point mutants of the N-terminal domain of the E. coli protein HypF. All variants were expressed as folding-incompetent units in a controlled manner, at low and comparable levels. Their solubilities were measured by quantifying the protein amount contained in the soluble and insoluble fractions by Western blot analysis. A significant negative correlation was found between the solubility of the variants in E. coli and their intrinsic propensity to form amyloid fibrils, predicted using an algorithm previously validated experimentally in vitro on a number of unfolded peptides and proteins, and considering hydrophobicity, beta-sheet propensity, and charge as major sequence determinants of the aggregation process. These findings show that the physicochemical parameters previously recognized to govern amyloid formation by fully or partially unfolded proteins are largely applicable in vivo and pave the way for the molecular exploration of a process as complex as protein aggregation in living organisms.

Amyloidogenic sequences in native protein structures

Numerous short peptides have been shown to form beta-sheet amyloid aggregates in vitro. Proteins that contain such sequences are likely to be problematic for a cell, due to their potential to aggregate into toxic structures. We investigated the structures of 30 proteins containing 45 sequences known to form amyloid, to see how the proteins cope with the presence of these potentially toxic sequences, studying secondary structure, hydrogen-bonding, solvent accessible surface area and hydrophobicity. We identified two mechanisms by which proteins avoid aggregation: Firstly, amyloidogenic sequences are often found within helices, despite their inherent preference to form beta structure. Helices may offer a selective advantage, since in order to form amyloid the sequence will presumably have to first unfold and then refold into a beta structure. Secondly, amyloidogenic sequences that are found in beta structure are usually buried within the protein. Surface exposed amyloidogenic sequences are not tolerated in strands, presumably because they lead to protein aggregation via assembly of the amyloidogenic regions. The use of alpha-helices, where amyloidogenic sequences are forced into helix, despite their intrinsic preference for beta structure, is thus a widespread mechanism to avoid protein aggregation.

Protein aggregation profile of the bacterial cytosol

BACKGROUND

Protein misfolding is usually deleterious for the cell, either as a consequence of the loss of protein function or the buildup of insoluble and toxic aggregates. The aggregation behavior of a given polypeptide is strongly influenced by the intrinsic properties encoded in its sequence. This has allowed the development of effective computational methods to predict protein aggregation propensity.

METHODOLOGY/PRINCIPAL FINDINGS

Here, we use the AGGRESCAN algorithm to approximate the aggregation profile of an experimental cytosolic Escherichia coli proteome. The analysis indicates that the aggregation propensity of bacterial proteins is associated with their length, conformation, location, function, and abundance. The data are consistent with the predictions of other algorithms on different theoretical proteomes.

CONCLUSIONS/SIGNIFICANCE

Overall, the study suggests that the avoidance of protein aggregation in functional environments acts as a strong evolutionary constraint on polypeptide sequences in both prokaryotic and eukaryotic organisms.

Identifying the amylome, proteins capable of forming amyloid-like fibrils

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.

Exploring the sequence determinants of amyloid structure using position-specific scoring matrices

Protein aggregation results in beta-sheet-like assemblies that adopt either a variety of amorphous morphologies or ordered amyloid-like structures. These differences in structure also reflect biological differences; amyloid and amorphous beta-sheet aggregates have different chaperone affinities, accumulate in different cellular locations and are degraded by different mechanisms. Further, amyloid function depends entirely on a high intrinsic degree of order. Here we experimentally explored the sequence space of amyloid hexapeptides and used the derived data to build Waltz, a web-based tool that uses a position-specific scoring matrix to determine amyloid-forming sequences. Waltz allows users to identify and better distinguish between amyloid sequences and amorphous beta-sheet aggregates and allowed us to identify amyloid-forming regions in functional amyloids.

Simultaneous prediction of protein folding and docking at high resolution

Interleaved dimers and higher order symmetric oligomers are ubiquitous in biology but present a challenge to de novo structure prediction methodology: The structure adopted by a monomer can be stabilized largely by interactions with other monomers and hence not the lowest energy state of a single chain. Building on the Rosetta framework, we present a general method to simultaneously model the folding and docking of multiple-chain interleaved homo-oligomers. For more than a third of the cases in a benchmark set of interleaved homo-oligomers, the method generates near-native models of large alpha-helical bundles, interlocking beta sandwiches, and interleaved alpha/beta motifs with an accuracy high enough for molecular replacement based phasing. With the incorporation of NMR chemical shift information, accurate models can be obtained consistently for symmetric complexes with as many as 192 total amino acids; a blind prediction was within 1 A rmsd of the traditionally determined NMR structure, and fit independently collected RDC data equally well. Together, these results show that the Rosetta "fold-and-dock" protocol can produce models of homo-oligomeric complexes with near-atomic-level accuracy and should be useful for crystallographic phasing and the rapid determination of the structures of multimers with limited NMR information.

Thermodynamic selection of steric zipper patterns in the amyloid cross-beta spine

At the core of amyloid fibrils is the cross-beta spine, a long tape of beta-sheets formed by the constituent proteins. Recent high-resolution x-ray studies show that the unit of this filamentous structure is a beta-sheet bilayer with side chains within the bilayer forming a tightly interdigitating "steric zipper" interface. However, for a given peptide, different bilayer patterns are possible, and no quantitative explanation exists regarding which pattern is selected or under what condition there can be more than one pattern observed, exhibiting molecular polymorphism. We address the structural selection mechanism by performing molecular dynamics simulations to calculate the free energy of incorporating a peptide monomer into a beta-sheet bilayer. We test filaments formed by several types of peptides including GNNQQNY, NNQQ, VEALYL, KLVFFAE and STVIIE, and find that the patterns with the lowest binding free energy correspond to available atomistic structures with high accuracy. Molecular polymorphism, as exhibited by NNQQ, is likely because there are more than one most stable structures whose binding free energies differ by less than the thermal energy. Detailed analysis of individual energy terms reveals that these short peptides are not strained nor do they lose much conformational entropy upon incorporating into a beta-sheet bilayer. The selection of a bilayer pattern is determined mainly by the van der Waals and hydrophobic forces as a quantitative measure of shape complementarity among side chains between the beta-sheets. The requirement for self-complementary steric zipper formation supports that amyloid fibrils form more easily among similar or same sequences, and it also makes parallel beta-sheets generally preferred over anti-parallel ones. But the presence of charged side chains appears to kinetically drive anti-parallel beta-sheets to form at early stages of assembly, after which the bilayer formation is likely driven by energetics.

Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations

BACKGROUND

Linking structural effects of mutations to functional outcomes is a major issue in structural bioinformatics, and many tools and studies have shown that specific structural properties such as stability and residue burial can be used to distinguish neutral variations and disease associated mutations.

RESULTS

We have investigated 39 structural properties on a set of SNPs and disease mutations from the Uniprot Knowledge Base that could be mapped on high quality crystal structures and show that none of these properties can be used as a sole classification criterion to separate the two data sets. Furthermore, we have reviewed the annotation process from mutation to result and identified the liabilities in each step.

CONCLUSION

Although excellent annotation results of various research groups underline the great potential of using structural bioinformatics to investigate the mechanisms underlying disease, the interpretation of such annotations cannot always be extrapolated to proteome wide variation studies. Difficulties for large-scale studies can be found both on the technical level, i.e. the scarcity of data and the incompleteness of the structural tool suites, and on the conceptual level, i.e. the correct interpretation of the results in a cellular context.

Amyloidogenic regions and interaction surfaces overlap in globular proteins related to conformational diseases

Protein aggregation underlies a wide range of human disorders. The polypeptides involved in these pathologies might be intrinsically unstructured or display a defined 3D-structure. Little is known about how globular proteins aggregate into toxic assemblies under physiological conditions, where they display an initially folded conformation. Protein aggregation is, however, always initiated by the establishment of anomalous protein-protein interactions. Therefore, in the present work, we have explored the extent to which protein interaction surfaces and aggregation-prone regions overlap in globular proteins associated with conformational diseases. Computational analysis of the native complexes formed by these proteins shows that aggregation-prone regions do frequently overlap with protein interfaces. The spatial coincidence of interaction sites and aggregating regions suggests that the formation of functional complexes and the aggregation of their individual subunits might compete in the cell. Accordingly, single mutations affecting complex interface or stability usually result in the formation of toxic aggregates. It is suggested that the stabilization of existing interfaces in multimeric proteins or the formation of new complexes in monomeric polypeptides might become effective strategies to prevent disease-linked aggregation of globular proteins.

The aggregation of proteins in tissues is associated with the pathogenesis of more than 40 human diseases. The polypeptides underlying disorders such as Alzheimer's and Parkinson's are devoid of any regular structure, whereas the polypeptides causing familial amyotrophic lateral sclerosis or nonneuropathic systemic amyloidosis correspond to globular proteins. Little is known about the mechanism by which globular proteins under physiological conditions aggregate from their initially folded and soluble conformations. Interestingly, several of these pathogenic proteins display quaternary structure or are bound to other proteins in their physiological context. In the present work, we show that protein-protein interaction surfaces and regions with high aggregation propensity significantly overlap in these polypeptides. This suggests that the formation of native complexes and self-aggregation reactions probably compete in the cell, explaining why point mutations affecting the interface or the stability of the protein complex lead in many cases to the formation of toxic aggregates. This study proposes general strategies to fight against diseases associated with the deposition of globular polypeptides.

Molecular mechanisms for protein-encoded inheritance

In prion inheritance and transmission, strains are phenotypic variants encoded by protein 'conformations'. However, it is unclear how a protein conformation can be stable enough to endure transmission between cells or organisms. Here we describe new polymorphic crystal structures of segments of prion and other amyloid proteins, which offer two structural mechanisms for the encoding of prion strains. In packing polymorphism, prion strains are encoded by alternative packing arrangements (polymorphs) of beta-sheets formed by the same segment of a protein; in segmental polymorphism, prion strains are encoded by distinct beta-sheets built from different segments of a protein. Both forms of polymorphism can produce enduring conformations capable of encoding strains. These molecular mechanisms for transfer of protein-encoded information into prion strains share features with the familiar mechanism for transfer of nucleic acid-encoded information into microbial strains, including sequence specificity and recognition by noncovalent bonds.

Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods

Many gene defects are relatively easy to identify experimentally, but obtaining information about the effects of sequence variations and elucidation of the detailed molecular mechanisms of genetic diseases will be among the next major efforts in mutation research. Amino acid substitutions may have diverse effects on protein structure and function; thus, a detailed analysis of the mutations is essential. Experimental study of the molecular effects of mutations is laborious, whereas useful and reliable information about the effects of amino acid substitutions can readily be obtained by theoretical methods. Experimentally defined structures and molecular modeling can be used as a basis for interpretation of the mutations. The effects of missense mutations can be analyzed even when the 3D structure of the protein has not been determined, although structure-based analyses are more reliable. Structural analyses include studies of the contacts between residues, their implication for the stability of the protein, and the effects of the introduced residues. Investigations of steric and stereochemical consequences of substitutions provide insights on the molecular fit of the introduced residue. Mutations that change the electrostatic surface potential of a protein have wide-ranging effects. Analyses of the effects of mutations on interactions with ligands and partners have been performed for elucidation of functional mutations. We have employed numerous methods for predicting the effects of amino acid substitutions. We discuss the applicability of these methods in the analysis of genes, proteins, and diseases to reveal protein structure-function relationships, which is essential to gain insights into disease genotype-phenotype correlations.

Short protein segments can drive a non-fibrillizing protein into the amyloid state

Protein fibrils termed amyloid-like are associated with numerous degenerative diseases as well as some normal cellular functions. Specific short segments of amyloid-forming proteins have been shown to form fibrils themselves. However, it has not been shown in general that these segments are capable of driving a protein from its native structure into the amyloid state. We applied the 3D profile method to identify fibril-forming segments within the amyloid-forming human proteins tau, alpha-synuclein, PrP prion and amyloid-beta. Ten segments, six to eight residues in length, were chosen and inserted into the C-terminal hinge loop of the highly constrained enzyme RNase A, and tested for fibril growth and Congo red birefringence. We find that all 10 unique inserts cause RNase A to form amyloid-like fibrils which display characteristic yellow to apple-green Congo red birefringence when observed with cross polarizers. These six to eight residue inserts can fibrillize RNase A and are sufficient for amyloid fibril spine formation.

Amyloidogenic determinants are usually not buried

Background

Amyloidoses are a group of usually fatal diseases, probably caused by protein misfolding and subsequent aggregation into amyloid fibrillar deposits. The mechanisms involved in amyloid fibril formation are largely unknown and are the subject of current, intensive research. In an attempt to identify possible amyloidogenic regions in proteins for further experimental investigation, we have developed and present here a publicly available online tool that utilizes five different and independently published methods, to form a consensus prediction of amyloidogenic regions in proteins, using only protein primary structure data.

Results

It appears that the consensus prediction tool is slightly more objective than individual prediction methods alone and suggests several previously not identified amino acid stretches as potential amyloidogenic determinants, which (although several of them may be overpredictions) require further experimental studies. The tool is available at: . Utilizing molecular graphics programs, like O and PyMOL, as well as the algorithm DSSP, it was found that nearly all experimentally verified amyloidogenic determinants (short peptide stretches favouring aggregation and subsequent amyloid formation), and several predicted, with the aid of the tool AMYLPRED, but not experimentally verified amyloidogenic determinants, are located on the surface of the relevant amyloidogenic proteins. This finding may be important in efforts directed towards inhibiting amyloid fibril formation.

Conclusion

The most significant result of this work is the observation that virtually all, to date, experimentally determined amyloidogenic determinants and the majority of predicted, but not yet experimentally verified short amyloidogenic stretches, lie 'exposed' on the surface of the relevant amyloidogenic proteins, and also several of them have the ability to act as conformational 'switches'. Experiments, focused on these fragments, should be performed to test this idea.

Potential aggregation prone regions in biotherapeutics: A survey of commercial monoclonal antibodies

Aggregation of a biotherapeutic is of significant concern and judicious process and formulation development is required to minimize aggregate levels in the final product. Aggregation of a protein in solution is driven by intrinsic and extrinsic factors. In this work we have focused on aggregation as an intrinsic property of the molecule. We have studied the sequences and Fab structures of commercial and non-commercial antibody sequences for their vulnerability towards aggregation by using sequence based computational tools to identify potential aggregation-prone motifs or regions. The mAbs in our dataset contain 2 to 8 aggregation-prone motifs per heavy and light chain pair. Some of these motifs are located in variable domains, primarily in CDRs. Most aggregation-prone motifs are rich in beta branched aliphatic and aromatic residues. Hydroxyl-containing Ser/Thr residues are also found in several aggregation-prone motifs while charged residues are rare. The motifs found in light chain CDR3 are glutamine (Q)/asparagine (N) rich. These motifs are similar to the reported aggregation promoting regions found in prion and amyloidogenic proteins that are also rich in Q/N, aliphatic and aromatic residues. The implication is that one possible mechanism for aggregation of mAbs may be through formation of cross-beta structures and fibrils. Mapping on the available Fab-receptor/antigen complex structures reveals that these motifs in CDRs might also contribute significantly towards receptor/antigen binding. Our analysis identifies the opportunity and tools for simultaneous optimization of the therapeutic protein sequence for potency and specificity while reducing vulnerability towards aggregation.

Effect of pseudorepeat rearrangement on alpha-synuclein misfolding, vesicle binding, and micelle binding

The pathological and physiological hallmarks of the protein alpha-synuclein (aS) are its misfolding into cytotoxic aggregates and its binding to synaptic vesicles, respectively. Both events are mediated by seven 11-residue amphiphilic pseudorepeats and, most generally, involve a transition from intrinsically unstructured conformations to structured conformations. Based on aS interactions with aggregation-inhibiting small molecules, an aS variant termed shuffled alpha-synuclein (SaS), wherein the first six pseudorepeats had been rearranged, was introduced. Here, the effects of this rearrangement on misfolding, vesicle binding, and micelle binding are examined in reference to aS and beta-synuclein to study the sequence characteristics underlying these processes. Fibrillization correlates with the distinct clustering of residues with high beta-sheet propensities, while vesicle affinities depend on the mode of pseudorepeat interchange and loss. In the presence of micelles, the pseudorepeat region of SaS adopts an essentially continuous helix, whereas aS and beta-synuclein encounter a distinct helix break, indicating that a more homogeneous distribution of surfactant affinities in SaS prevented the formation of an extensive helix break in the micelle-bound state. By demonstrating the importance of the distribution of beta-sheet propensities and by revealing inhomogeneous aS surfactant affinities, the present study provides novel insights into two central themes of synuclein biology.

NetCSSP: web application for predicting chameleon sequences and amyloid fibril formation

The calculation of contact-dependent secondary structure propensity (CSSP) is a unique and sensitive method that detects non-native secondary structure propensities in protein sequences. This method has applications in predicting local conformational change, which typically is observed in core sequences of protein aggregation and amyloid fibril formation. NetCSSP implements the latest version of the CSSP algorithm and provides a Flash chart-based graphic interface that enables an interactive calculation of CSSP values for any user-selected regions in a given protein sequence. This feature also can quantitatively estimate the mutational effect on changes in native or non-native secondary structural propensities in local sequences. In addition, this web tool provides precalculated non-native secondary structure propensities for over 1 400 000 fragments that are seven-residues long, collected from PDB structures. They are searchable for chameleon subsequences that can serve as the core of amyloid fibril formation. The NetCSSP web tool is available at http://cssp2.sookmyung.ac.kr/.

Identification of amyloidogenic peptide sequences using a coarse-grained physicochemical model

Cross-beta amyloid is implicated in over 20 human diseases. Experiments suggest that specific sequence elements within amyloidogenic proteins play a major role in seeding amyloid formation. Identifying these seeding sequences is important for rationalizing the molecular mechanisms of amyloid formation and for elaborating therapeutic strategies that target amyloid. Theoretical techniques play an important role in facilitating the identification and structural characterization of putative seeding sequences; most amyloid species are not amenable to high resolution experimental structure techniques. In this study we have combined a coarse-grained physicochemical protein model with a highly efficient Monte Carlo sampling technique to identify amyloidogenic sequences in four proteins for which respective experimental peptide fragmentation data exist. Peptide sequences were defined as amyloidogenic if the ensemble structure predicted for three interacting peptides described a stable and regular three-stranded beta-sheet. For such peptides, free energies were calculated to provide a measure of amyloid propensity. The overall agreement between the experimental and predicted data is good, and we correctly identify several self-recognition motifs proposed to define the cross-beta amyloid fibril architectures of two of the proteins. Our results compare very favorably with those obtained using atomistic molecular dynamics methods, though our simulations are 30-40 times faster.

Prediction of amyloid fibril-forming segments based on a support vector machine

BACKGROUND

Amyloid fibrillar aggregates of proteins or polypeptides are known to be associated with many human diseases. Recent studies suggest that short protein regions trigger this aggregation. Thus, identifying these short peptides is critical for understanding diseases and finding potential therapeutic targets.

RESULTS

We propose a method, named Pafig (Prediction of amyloid fibril-forming segments) based on support vector machines, to identify the hexpeptides associated with amyloid fibrillar aggregates. The features of Pafig were obtained by a two-round selection from AAindex. Using a 10-fold cross validation test on Hexpepset dataset, Pafig performed well with regards to overall accuracy of 81% and Matthews correlation coefficient of 0.63. Pafig was used to predict the potential fibril-forming hexpeptides in all of the 64,000,000 hexpeptides. As a result, approximately 5.08% of hexpeptides showed a high aggregation propensity. In the predicted fibril-forming hexpeptides, the amino acids--alanine, phenylalanine, isoleucine, leucine and valine occurred at the higher frequencies and the amino acids--aspartic acid, glutamic acid, histidine, lysine, arginine and praline, appeared with lower frequencies.

CONCLUSION

The performance of Pafig indicates that it is a powerful tool for identifying the hexpeptides associated with fibrillar aggregates and will be useful for large-scale analysis of proteomic data.

Abeta(1-40) fibril polymorphism implies diverse interaction patterns in amyloid fibrils

Amyloid fibrils characterize a diverse group of human diseases that includes Alzheimer's disease, Creutzfeldt-Jakob and type II diabetes. Alzheimer's amyloid fibrils consist of amyloid-beta (Abeta) peptide and occur in a range of structurally different fibril morphologies. The structural characteristics of 12 single Abeta(1-40) amyloid fibrils, all formed under the same solution conditions, were determined by electron cryo-microscopy and three-dimensional reconstruction. The majority of analyzed fibrils form a range of morphologies that show almost continuously altering structural properties. The observed fibril polymorphism implies that amyloid formation can lead, for the same polypeptide sequence, to many different patterns of inter- or intra-residue interactions. This property differs significantly from native, monomeric protein folding reactions that produce, for one protein sequence, only one ordered conformation and only one set of inter-residue interactions.

Bacterial inclusion bodies contain amyloid-like structure

Protein aggregation is a process in which identical proteins self-associate into imperfectly ordered macroscopic entities. Such aggregates are generally classified as amorphous, lacking any long-range order, or highly ordered fibrils. Protein fibrils can be composed of native globular molecules, such as the hemoglobin molecules in sickle-cell fibrils, or can be reorganized beta-sheet-rich aggregates, termed amyloid-like fibrils. Amyloid fibrils are associated with several pathological conditions in humans, including Alzheimer disease and diabetes type II. We studied the structure of bacterial inclusion bodies, which have been believed to belong to the amorphous class of aggregates. We demonstrate that all three in vivo-derived inclusion bodies studied are amyloid-like and comprised of amino-acid sequence-specific cross-beta structure. These findings suggest that inclusion bodies are structured, that amyloid formation is an omnipresent process both in eukaryotes and prokaryotes, and that amino acid sequences evolve to avoid the amyloid conformation.

Aggregation propensity of the human proteome

Formation of amyloid-like fibrils is involved in numerous human protein deposition diseases, but is also an intrinsic property of polypeptide chains in general. Progress achieved recently now allows the aggregation propensity of proteins to be analyzed over large scales. In this work we used a previously developed predictive algorithm to analyze the propensity of the 34,180 protein sequences of the human proteome to form amyloid-like fibrils. We show that long proteins have, on average, less intense aggregation peaks than short ones. Human proteins involved in protein deposition diseases do not differ extensively from the rest of the proteome, further demonstrating the generality of protein aggregation. We were also able to reproduce some of the results obtained with other algorithms, demonstrating that they do not depend on the type of computational tool employed. For example, proteins with different subcellular localizations were found to have different aggregation propensities, in relation to the various efficiencies of quality control mechanisms. Membrane proteins, intrinsically disordered proteins, and folded proteins were confirmed to have very different aggregation propensities, as a consequence of their different structures and cellular microenvironments. In addition, gatekeeper residues at strategic positions of the sequences were found to protect human proteins from aggregation. The results of these comparative analyses highlight the existence of intimate links between the propensity of proteins to form aggregates with β-structure and their biology. In particular, they emphasize the existence of a negative selection pressure that finely modulates protein sequences in order to adapt their aggregation propensity to their biological context.

Amyloid-like fibrils are insoluble proteinaceous fibrillar aggregates with a characteristic structure (the cross-β core) that form and deposit in more than 40 pathological conditions in humans. These include Alzheimer's disease, Parkinson's disease, type II diabetes, and the spongiform encephalopathies. A number of proteins not involved in any disease can also form amyloid-like fibrils in vitro, suggesting that amyloid fibril formation is an intrinsic property of proteins in general. Recent efforts in understanding the physico-chemical grounds of amyloid fibril formation has led to the development of several algorithms, capable of predicting a number of aggregation-related parameters of a protein directly from its amino acid sequence. In order to study the predicted aggregation behavior of the human proteome, we have run one of these algorithms on the 34,180 human protein sequences. Our results demonstrate that molecular evolution has acted on protein sequences to finely modulate their aggregation propensities, depending on different parameters related to their in vivo environment. Together with cellular control mechanisms, this natural selection protects proteins from aggregation during their lifetime.

Charge-pairing mechanism of phosphorylation effect upon amyloid fibrillation of human tau core peptide

Phosphorylation of a fibrillogenic protein, human tau, is believed to play crucial roles in the pathogenesis of Alzheimer's disease. For elucidating molecular mechanisms of the phosphorylation effect on tau fibrillation, we synthesized a peptide, VQIVY 310K (PHF6) and its phosphorylated derivative (PHF6pY). PHF6 is a partial peptide surrounding a plausible in vivo phosphorylation site Tyr310 and forms amyloid-type fibrils similar to those generated by full-length tau. Fibrillation of PHF6 and PHF6pY were studied by spectroscopic and microscopic methods, and the critical concentration of the fibrillation was determined for comparing the fibril stability. The results showed that the phosphorylation strongly influenced the fibrillation propensity of PHF6 by changing its dependency on pH and ionic strength. On the basis of the observations, we suggested that charged sites on the phosphate group and its electrostatic pairing with the neighboring charged residues were physical origins of the phosphorylation effect. To verify this charge-pairing mechanism, we conducted experiments using a series of PHF6 derivatives with non-native charge distributions. The electrostatic interaction in an intermolecular mode was also demonstrated by the system composed of two different peptide species, which found that fibrillation of nonphosphorylated PHF6 was drastically enhanced when a trace amount of phosphorylated PHF6 molecules coexisted. A simulation analysis utilizing crystal coordinates of the PHF6 fibril was also performed for interpreting the experimental results in a molecular level. The present study using the model peptide system gave us a microscopically insightful view on the roles of tau phosphorylation in amyloid-related diseases.

Optimal design of thermally stable proteins

Motivation: For many biotechnological purposes, it is desirable to redesign proteins to be more structurally and functionally stable at higher temperatures. For example, chemical reactions are intrinsically faster at higher temperatures, so using enzymes that are stable at higher temperatures would lead to more efficient industrial processes. We describe an innovative and computationally efficient method called Improved Configurational Entropy (ICE), which can be used to redesign a protein to be more thermally stable (i.e. stable at high temperatures). This can be accomplished by systematically modifying the amino acid sequence via local structural entropy (LSE) minimization. The minimization problem is modeled as a shortest path problem in an acyclic graph with nonnegative weights and is solved efficiently using Dijkstra's method.

Contact:mitchell@biochem.wisc.edu

Atomic structure of the cross-beta spine of islet amyloid polypeptide (amylin)

Human islet amyloid polypeptide (IAPP or amylin) is a 37-residue hormone found as fibrillar deposits in pancreatic extracts of nearly all type II diabetics. Although the cellular toxicity of IAPP has been established, the structure of the fibrillar form found in these deposits is unknown. Here we have crystallized two segments from IAPP, which themselves form amyloid-like fibrils. The atomic structures of these two segments, NNFGAIL and SSTNVG, were determined, and form the basis of a model for the most commonly observed, full-length IAPP polymorph.

AMYPdb: a database dedicated to amyloid precursor proteins

Background

Misfolding and aggregation of proteins into ordered fibrillar structures is associated with a number of severe pathologies, including Alzheimer's disease, prion diseases, and type II diabetes. The rapid accumulation of knowledge about the sequences and structures of these proteins allows using of in silico methods to investigate the molecular mechanisms of their abnormal conformational changes and assembly. However, such an approach requires the collection of accurate data, which are inconveniently dispersed among several generalist databases.

Results

We therefore created a free online knowledge database (AMYPdb) dedicated to amyloid precursor proteins and we have performed large scale sequence analysis of the included data. Currently, AMYPdb integrates data on 31 families, including 1,705 proteins from nearly 600 organisms. It displays links to more than 2,300 bibliographic references and 1,200 3D-structures. A Wiki system is available to insert data into the database, providing a sharing and collaboration environment. We generated and analyzed 3,621 amino acid sequence patterns, reporting highly specific patterns for each amyloid family, along with patterns likely to be involved in protein misfolding and aggregation.

Conclusion

AMYPdb is a comprehensive online database aiming at the centralization of bioinformatic data regarding all amyloid proteins and their precursors. Our sequence pattern discovery and analysis approach unveiled protein regions of significant interest. AMYPdb is freely accessible [1].

Structural and functional properties of peptides based on the N-terminus of HIV-1 gp41 and the C-terminus of the amyloid-beta protein

Given their high alanine and glycine levels, plaque formation, alpha-helix to beta-sheet interconversion and fusogenicity, FP (i.e., the N-terminal fusion peptide of HIV-1 gp41; 23 residues) and amyloids were proposed as belonging to the same protein superfamily. Here, we further test whether FP may exhibit 'amyloid-like' characteristics, by contrasting its structural and functional properties with those of Abeta(26-42), a 17-residue peptide from the C-terminus of the amyloid-beta protein responsible for Alzheimer's. FTIR spectroscopy, electron microscopy, light scattering and predicted amyloid structure aggregation (PASTA) indicated that aqueous FP and Abeta(26-42) formed similar networked beta-sheet fibrils, although the FP fibril interactions were weaker. FP and Abeta(26-42) both lysed and aggregated human erythrocytes, with the hemolysis-onsets correlated with the conversion of alpha-helix to beta-sheet for each peptide in liposomes. Congo red (CR), a marker of amyloid plaques in situ, similarly inhibited either FP- or Abeta(26-42)-induced hemolysis, and surface plasmon resonance indicated that this may be due to direct CR-peptide binding. These findings suggest that membrane-bound beta-sheets of FP may contribute to the cytopathicity of HIV in vivo through an amyloid-type mechanism, and support the classification of HIV-1 FP as an 'amyloid homolog' (or 'amylog').

Insights into stability and toxicity of amyloid-like oligomers by replica exchange molecular dynamics analyses

Deposition of insoluble amyloid plaques is frequently associated with a large variety of neurodegenerative diseases. However, data collected in the last decade have suggested that the neurotoxic action is exerted by prefibrillar, soluble assemblies of amyloid-forming proteins and peptides. The scarcity of structural data available for both amyloid-like fibrils and soluble oligomers is a major limitation for the definition of the molecular mechanisms linked to the onset of these diseases. Recently, the structural characterization of GNNQQNY and other peptides has shown a general feature of amyloid-like fibers, the so-called steric zipper motif. However, very little is known still about the prefibrillar oligomeric forms. By using replica exchange molecular dynamics we carried out extensive analyses of the properties of several small and medium GNNQQNY aggregates arranged through the steric zipper motif. Our data show that the assembly formed by two sheets, each made of two strands, arranged as in the crystalline states are highly unstable. Conformational free energy surfaces indicate that the instability of the model can be ascribed to the high reactivity of edge backbone hydrogen bonding donors/acceptors. On the other hand, data on larger models show that steric zipper interactions may keep small oligomeric forms in a stable state. These models simultaneously display two peculiar structural motifs: a tightly packed steric zipper interface and a large number of potentially reactive exposed strands. The presence of highly reactive groups on these assemblies likely generates two distinct evolutions. On one side the reactive groups quickly lead, through self-association, to the formation of ordered fibrils, on the other they may interfere with several cellular components thereby generating toxic effects. In this scenario, fiber formation propensity and toxicity of oligomeric states are two different manifestations of the same property: the hyper-reactivity of the exposed strands.