Mutagenesis of the central hydrophobic cluster in Abeta42 Alzheimer's peptide. Side-chain properties correlate with aggregation propensities

Short Peptides as Inhibitors of Amyloid Aggregation

The misfolding and aggregation of proteins into amyloid has been linked to a variety of age-related diseases. Aggregation of proteins, such as Aβ in Alzheimer’s disease and Islet Amyloid Polypeptide (IAPP, amylin) in type 2 diabetes, appears to lead to the formation of toxic assemblies. These assemblies range in size from small oligomers (2–8 proteins) to large fibrils (thousands of proteins). It remains unclear how these amyloidogenic proteins misfold and form toxic species, but growing evidence suggests that inhibiting the aggregation of these proteins could slow, if not prevent altogether, the progression of these diseases. We describe the use of small peptides (<43 amino acids) as inhibitors of amyloid-based aggregation. These peptides, often short complementary segments of the amyloid proteins, can be useful (i) for identifying the aggregation-prone regions of the amyloid proteins (ii) as models for drug discovery and (iii) as potential therapeutic agents themselves.

Key residues for the oligomerization of Aβ42 protein in Alzheimer's disease

Deposition of amyloid fibrils consisting of amyloid β (Aβ) protein as senile plaques in the brain is a pathological hallmark of Alzheimer's disease. However, a growing body of evidence shows that soluble Aβ oligomers correlate better with dementia than fibrils, suggesting that Aβ oligomers may be the primary toxic species. The structure and oligomerization mechanism of these Aβ oligomers are crucial for developing effective therapeutics. Here we investigated the oligomerization of Aβ42 in the context of a fusion protein containing GroES and ubiquitin fused to the N-terminus of Aβ sequence. The presence of fusion protein partners, in combination with a denaturing buffer containing 8M urea at pH 10, is unfavorable for Aβ42 aggregation, thus allowing only the most stable structures to be observed. Transmission electron microscopy showed that Aβ42 fusion protein formed globular oligomers, which bound weakly to thioflavin T and Congo red. SDS-PAGE shows that Aβ42 fusion protein formed SDS-resistant hexamers and tetramers. In contrast, Aβ40 fusion protein remained as monomers on SDS gel, suggesting that the oligomerization of Aβ42 fusion protein is not due to the fusion protein partners. Cysteine scanning mutagenesis at 22 residue positions further revealed that single cysteine substitutions of the C-terminal hydrophobic residues (I31, I32, L34, V39, V40, and I41) led to disruption of hexamer and tetramer formation, suggesting that hydrophobic interactions between these residues are most critical for Aβ42 oligomerization.

Prediction of amyloid aggregation in vivo

Many human diseases owe their pathology, to some degree, to the erroneous conversion of proteins from their soluble state into fibrillar, β-structured aggregates, often referred to as amyloid fibrils. Neurodegenerative diseases, such as Alzheimer and spongiform encephalopathies, as well as type 2 diabetes and both localized and systemic amyloidosis, are among the conditions that are associated with the formation of amyloid fibrils. Several mathematical tools can rationalize and even predict important parameters of amyloid fibril formation. It is not clear, however, whether such algorithms have predictive powers for in vivo systems, in which protein aggregation is affected by the presence of other biological factors. In this review, we briefly describe the existing algorithms and use them to predict the effects of mutations on the aggregation of specific proteins, for which in vivo experimental data are available. The comparison between the theoretical predictions and the experimental data obtained in vivo is shown for each algorithm and experimental data set, and statistically significant correlations are found in most cases.

Mutations that replace aromatic side chains promote aggregation of the Alzheimer's Aβ peptide

The aggregation of polypeptides into amyloid fibrils is associated with a number of human diseases. Because these fibrils--or intermediates on the aggregation pathway--play important roles in the etiology of disease, considerable effort has been expended to understand which features of the amino acid sequence promote aggregation. One feature suspected to direct aggregation is the π-stacking of aromatic residues. Such π-stacking interactions have also been proposed as the targets for various aromatic compounds that are known to inhibit aggregation. In the case of Alzheimer's disease, the aromatic side chains Phe19 and Phe20 in the wild-type amyloid beta (Aβ) peptide have been implicated. To explicitly test whether the aromaticity of these side chains plays a role in aggregation, we replaced these two phenylalanine side chains with leucines or isoleucines. These residues have similar sizes and hydrophobicities as Phe but are not capable of π-stacking. Thioflavin-T fluorescence and electron microscopy demonstrate that replacement of residues 19 and 20 by Leu or Ile did not prevent aggregation, but rather enhanced amyloid formation. Further experiments showed that aromatic inhibitors of aggregation are as effective against Ile- and Leu-substituted versions of Aβ42 as they are against wild-type Aβ. These results suggest that aromatic π-stacking interactions are not critical for Aβ aggregation or for the inhibition of Aβ aggregation.

Characterizing the structural behavior of selected Aβ-42 monomers with different solubilities

The conformational behavior of the wild-type amyloid β-42 (Aβ-42) monomer and two of its mutants was explored via all-atom replica exchange molecular dynamics simulations in explicit solvent, to identify structural features that may promote or deter early-stage oligomerization. The markers used for this purpose indicate that while the three peptides are relatively flexible they have distinct preferential structures and degree of rigidity. In particular, we found that one mutant that remains in the monomeric state in experiments displays a characteristic N-terminal structure that significantly enhances its rigidity. This finding is consistent with various studies that have detected a reduction in oligomerization frequency and Aβ-related toxicity upon sequence-specific antibody or ligand binding to the N-terminal tail of wild-type monomers, likely leading to the stabilization of this region. In general, our results highlight a potential role of the N-terminal segment on Aβ oligomerization and give insights into specific interactions that may be responsible for promoting the pronounced structural changes observed upon introducing point mutations on the wild-type Aβ-42 peptide.

Linking amyloid protein aggregation and yeast survival

Protein aggregation and amyloid formation lie behind an increasing number of human diseases. Here we describe the application of an "aggregation reporter", in which the test protein is fused to dihydrofolate reductase, as a general method to assess the intracellular solubility of amyloid proteins in eukaryotic background. Because the aggregation state of the target protein is linked directly to yeast cells survival in the presence of methotrexate, protein solubility can be monitored in vivo without the requirement of a functional assay for the protein of interest. In addition, the approach allows the in vivo visualization of the cellular location and aggregated state of the target protein. To demonstrate the applicability of the assay in the screening of genes or compounds that modulate amyloid protein aggregation in living cells, we have used as models the Alzheimer's amyloid β peptide, polyglutamine expansions of huntingtin, α-synuclein and non-aggregating variants thereof. Moreover, the anti-aggregational properties of small molecules and the effects of the yeast protein quality control machinery have also been evaluated using this method.

Hydralazine modifies Aβ fibril formation and prevents modification by lipids in vitro

Lipid oxidative damage and amyloid β (Aβ) misfolding contribute to Alzheimer's disease (AD) pathology. Thus, the prevention of oxidative damage and Aβ misfolding are attractive targets for drug discovery. At present, no AD drugs approved by the Food and Drug Administration (FDA) prevent or halt disease progression. Hydralazine, a smooth muscle relaxant, is a potential drug candidate for AD drug therapy as it reduces Aβ production and prevents oxidative damage via its antioxidant hydrazide group. We evaluated the efficacy of hydralazine, and related hydrazides, in reducing (1) Aβ misfolding and (2) Aβ protein modification by the reactive lipid 4-hydroxy-2-nonenal (HNE) using transmission electron microscopy and Western blotting. While hydralazine did not prevent Aβ aggregation as measured using the protease protection assay, there were more oligomeric species observed by electron microscopy. Hydralazine prevented lipid modification of Aβ, and Aβ was used as a proxy for classes of proteins which either misfold or are modified by HNE. All of the other hydrazides prevented lipid modification of Aβ and also did not prevent Aβ aggregation. Surprisingly, a few of the compounds, carbazochrome and niclosamide, appeared to augment Aβ formation. Thus, hydrazides reduced lipid oxidative damage, and hydralazine additionally reduced Aβ misfolding. While hydralazine would require specific chemical modifications for use as an AD therapeutic itself (to improve blood brain barrier permeability, reduce vasoactive side effects, and optimization for amyloid inhibition), this study suggests its potential merit for further AD drug development.

Selection for nonamyloidogenic mutants of islet amyloid polypeptide (IAPP) identifies an extended region for amyloidogenicity

The aggregation of the 37-residue protein, islet amyloid polypeptide (IAPP), as either insoluble amyloid or as small oligomers, appears to play a direct role in the death of pancreatic beta-islet cells in type II diabetes. While IAPP has been known to be the primary component of type II diabetes amyloid, the molecular interactions responsible for this aggregation have not been identified. To identify the aggregation-prone region(s), we constructed a library of randomly generated point mutants of IAPP. This mutant IAPP library was expressed in Escherichia coli as genetic fusions to the reporter protein enhanced green fluorescent protein (EGFP). Because IAPP aggregates rapidly, both independently and when fused to EGFP, the fusion protein does not yield a functional, fluorescent EGFP. However, mutations of IAPP that result in nonamyloidogenic sequences remain soluble and allow EGFP to fold and fluoresce. Using this screen, we identified 22 single mutations, 4 double mutations, and 2 triple mutations of IAPP that appear to be less amyloidogenic than wild-type human IAPP. A comparison of these sequences suggests residues 13 and 15-17 comprise an additional aggregation-prone region outside of the main amyloidogenic region of IAPP.

Scoring function to predict solubility mutagenesis

BACKGROUND

Mutagenesis is commonly used to engineer proteins with desirable properties not present in the wild type (WT) protein, such as increased or decreased stability, reactivity, or solubility. Experimentalists often have to choose a small subset of mutations from a large number of candidates to obtain the desired change, and computational techniques are invaluable to make the choices. While several such methods have been proposed to predict stability and reactivity mutagenesis, solubility has not received much attention.

RESULTS

We use concepts from computational geometry to define a three body scoring function that predicts the change in protein solubility due to mutations. The scoring function captures both sequence and structure information. By exploring the literature, we have assembled a substantial database of 137 single- and multiple-point solubility mutations. Our database is the largest such collection with structural information known so far. We optimize the scoring function using linear programming (LP) methods to derive its weights based on training. Starting with default values of 1, we find weights in the range [0,2] so that predictions of increase or decrease in solubility are optimized. We compare the LP method to the standard machine learning techniques of support vector machines (SVM) and the Lasso. Using statistics for leave-one-out (LOO), 10-fold, and 3-fold cross validations (CV) for training and prediction, we demonstrate that the LP method performs the best overall. For the LOOCV, the LP method has an overall accuracy of 81%.

AVAILABILITY

Executables of programs, tables of weights, and datasets of mutants are available from the following web page: http://www.wsu.edu/~kbala/OptSolMut.html.

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.

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.

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.

Critical structural and functional roles for the N-terminal insertion sequence in surfactant protein B analogs

Background

Surfactant protein B (SP-B; 79 residues) belongs to the saposin protein superfamily, and plays functional roles in lung surfactant. The disulfide cross-linked, N- and C-terminal domains of SP-B have been theoretically predicted to fold as charged, amphipathic helices, suggesting their participation in surfactant activities. Earlier structural studies with Mini-B, a disulfide-linked construct based on the N- and C-terminal regions of SP-B (i.e., ∼residues 8–25 and 63–78), confirmed that these neighboring domains are helical; moreover, Mini-B retains critical in vitro and in vivo surfactant functions of the native protein. Here, we perform similar analyses on a Super Mini-B construct that has native SP-B residues (1–7) attached to the N-terminus of Mini-B, to test whether the N-terminal sequence is also involved in surfactant activity.

Methodology/Results

FTIR spectra of Mini-B and Super Mini-B in either lipids or lipid-mimics indicated that these peptides share similar conformations, with primary α-helix and secondary β-sheet and loop-turns. Gel electrophoresis demonstrated that Super Mini-B was dimeric in SDS detergent-polyacrylamide, while Mini-B was monomeric. Surface plasmon resonance (SPR), predictive aggregation algorithms, and molecular dynamics (MD) and docking simulations further suggested a preliminary model for dimeric Super Mini-B, in which monomers self-associate to form a dimer peptide with a “saposin-like” fold. Similar to native SP-B, both Mini-B and Super Mini-B exhibit in vitro activity with spread films showing near-zero minimum surface tension during cycling using captive bubble surfactometry. In vivo, Super Mini-B demonstrates oxygenation and dynamic compliance that are greater than Mini-B and compare favorably to full-length SP-B.

Conclusion

Super Mini-B shows enhanced surfactant activity, probably due to the self-assembly of monomer peptide into dimer Super Mini-B that mimics the functions and putative structure of native SP-B.

Probing energetics of Abeta fibril elongation by molecular dynamics simulations

Using replica exchange molecular dynamics simulations and an all-atom implicit solvent model, we probed the energetics of Abeta(10-40) fibril growth. The analysis of the interactions between incoming Abeta peptides and the fibril led us to two conclusions. First, considerable variations in fibril binding propensities are observed along the Abeta sequence. The peptides in the fibril and those binding to its edge interact primarily through their N-termini. Therefore, the mutations affecting the Abeta positions 10-23 are expected to have the largest impact on fibril elongation compared with those occurring in the C-terminus and turn. Second, we performed weak perturbations of the binding free energy landscape by scanning partial deletions of side-chain interactions at various Abeta sequence positions. The results imply that strong side-chain interactions--in particular, hydrophobic contacts--impede fibril growth by favoring disordered docking of incoming peptides. Therefore, fibril elongation may be promoted by moderate reduction of Abeta hydrophobicity. The comparison with available experimental data is presented.

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.

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.

Bimodal protein solubility distribution revealed by an aggregation analysis of the entire ensemble of Escherichia coli proteins

Protein folding often competes with intermolecular aggregation, which in most cases irreversibly impairs protein function, as exemplified by the formation of inclusion bodies. Although it has been empirically determined that some proteins tend to aggregate, the relationship between the protein aggregation propensities and the primary sequences remains poorly understood. Here, we individually synthesized the entire ensemble of Escherichia coli proteins by using an in vitro reconstituted translation system and analyzed the aggregation propensities. Because the reconstituted translation system is chaperone-free, we could evaluate the inherent aggregation propensities of thousands of proteins in a translation-coupled manner. A histogram of the solubilities, based on data from 3,173 translated proteins, revealed a clear bimodal distribution, indicating that the aggregation propensities are not evenly distributed across a continuum. Instead, the proteins can be categorized into 2 groups, soluble and aggregation-prone proteins. The aggregation propensity is most prominently correlated with the structural classification of proteins, implying that the prediction of aggregation propensity requires structural information about the protein.

Thermal aggregation of a model allosteric protein in different conformational states

Protein aggregation is of crucial importance in a wide variety of situations. High temperatures, combined with other denaturing conditions, have been used very extensively to decipher some of the fundamentals related to formation of amorphous and fibrillar protein aggregates. The present study reports on the dependency of thermal aggregation of bovine liver glutamate dehydrogenase (GDH), a well-characterized allosteric enzyme, on its conformational state. The initial phases of thermal aggregation of this protein was followed in the presence of a number of well-known allosteric ligands. Positive effectors were found to decrease the rate and extent of aggregation in a concentration dependent manner, while negative effectors did the reverse. ADP, one of the most characterized GDH activators was found to stabilize a specific protein conformation resulting in loss of propensity to aggregate. The importance of this observation related to control of protein-protein interactions leading to protein aggregation is discussed.

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.

Kinetic and thermodynamic stability of bacterial intracellular aggregates

Protein aggregation is related to many human disorders and constitutes a major bottleneck in protein production. However, little is known about the conformational properties of in vivo formed aggregates and how they relate to the specific polypeptides embedded in them. Here, we show that the kinetic and thermodynamic stability of the inclusion bodies formed by the Abeta42 Alzheimer peptide and its Asp19 alloform differ significantly and correlate with their amyloidogenic propensity and solubility inside the cell. Our results indicate that the nature of the polypeptide chain determines the specific conformational properties of intracellular aggregates. This implies that different protein inclusions impose dissimilar challenges to the cellular quality-control machinery.

Studies on bacterial inclusion bodies

The field of protein misfolding and aggregation has become an extremely active area of research in recent years. Of particular interest is the deposition of polypeptides into inclusion bodies inside bacterial cells. One reason for this interest is that protein aggregation constitutes a major bottleneck in protein production and restricts the spectrum of protein-based drugs available for commercialization. Additionally, prokaryotic cells could provide a simple yet powerful system for studying the formation and prevention of toxic aggregates, such as those responsible for a number of degenerative diseases. Here, we review recent work that has challenged our understanding of the structure and physiology of inclusion bodies and provided us with a new view of intracellular protein deposition, which has important implications in microbiology, biomedicine and biotechnology.

The in vivo and in vitro aggregation properties of globular proteins correlate with their conformational stability: the SH3 case

Protein misfolding and deposition underlie an increasing number of debilitating human disorders and constitute a problem of major concern in biotechnology. In the last years, in vitro studies have provided valuable insights into the physicochemical principles underlying protein aggregation. Nevertheless, information about the determinants of protein deposition within the cell is scarce and only a few systematic studies comparing in vitro and in vivo data have been reported. Here, we have used the SH3 domain of alpha-spectrin as a model globular protein in an attempt to understand the relationship between protein aggregation in the test-tube and in the more complex cellular environment. The investigation of the aggregation in Escherichia coli of this domain and a large set of mutants, together with the analysis of their sequential and conformational properties allowed us to evaluate the contribution of different polypeptidic factors to the cellular deposition of globular proteins. The data presented here suggest that the rules that govern in vitro protein aggregation are also valid in in vivo contexts. They also provide relevant insights into intracellular protein deposition in both conformational diseases and recombinant protein production.

The distribution of residues in a polypeptide sequence is a determinant of aggregation optimized by evolution

It has been shown that the propensity of a protein to form amyloid-like fibrils can be predicted with high accuracy from the knowledge of its amino acid sequence. It has also been suggested, however, that some regions of the sequences are more important than others in determining the aggregation process. Here, we have addressed this issue by constructing a set of "sequence scrambled" variants of the first 29 residues of horse heart apomyoglobin (apoMb(1-29)), in which the sequence was modified while maintaining the same amino acid composition. The clustering of the most amyloidogenic residues in one region of the sequence was found to cause a marked increase of the elongation rate (k(agg)) and a remarkable shortening of the lag phase (t(lag)) of the fibril growth, as determined by far-UV circular dichroism and thioflavin T fluorescence. We also show that taking explicitly into consideration the presence of aggregation-promoting regions in the predictive methods results in a quantitative agreement between the theoretical and observed k(agg) and t(lag) values of the apoMb(1-29) variants. These results, together with a comparison between homologous segments from the family of globins, indicate the existence of a negative selection against the clustering of highly amyloidogenic residues in one or few regions of polypeptide sequences.

Ile-phe dipeptide self-assembly: clues to amyloid formation

Peptidic self-assembled nanostructures are said to have a wide range of applications in nanotechnology, yet the mechanistic details of hierarchical self-assembly are still poorly understood. The Phe-Phe recognition motif of the Alzheimer's Abeta peptide is the smallest peptide able to assemble into higher-order structures. Here, we show that the Ile-Phe dipeptide analog is also able to self-associate in aqueous solution as a transparent, thermoreversible gel formed by a network of fibrillar nanostructures that exhibit strong birefringence upon Congo red binding. Besides, a second dipeptide Val-Phe, differing only in a methyl group from the former, is unable to self-assemble. The detailed analysis of the differential polymeric behavior of these closely related molecules provides insight into the forces triggering the first steps in self-assembly processes such as amyloid formation.

AGGRESCAN: a server for the prediction and evaluation of "hot spots" of aggregation in polypeptides

Background

Protein aggregation correlates with the development of several debilitating human disorders of growing incidence, such as Alzheimer's and Parkinson's diseases. On the biotechnological side, protein production is often hampered by the accumulation of recombinant proteins into aggregates. Thus, the development of methods to anticipate the aggregation properties of polypeptides is receiving increasing attention. AGGRESCAN is a web-based software for the prediction of aggregation-prone segments in protein sequences, the analysis of the effect of mutations on protein aggregation propensities and the comparison of the aggregation properties of different proteins or protein sets.

Results

AGGRESCAN is based on an aggregation-propensity scale for natural amino acids derived from in vivo experiments and on the assumption that short and specific sequence stretches modulate protein aggregation. The algorithm is shown to identify a series of protein fragments involved in the aggregation of disease-related proteins and to predict the effect of genetic mutations on their deposition propensities. It also provides new insights into the differential aggregation properties displayed by globular proteins, natively unfolded polypeptides, amyloidogenic proteins and proteins found in bacterial inclusion bodies.

Conclusion

By identifying aggregation-prone segments in proteins, AGGRESCAN shall facilitate (i) the identification of possible therapeutic targets for anti-depositional strategies in conformational diseases and (ii) the anticipation of aggregation phenomena during storage or recombinant production of bioactive polypeptides or polypeptide sets.

Effect of temperature on protein quality in bacterial inclusion bodies

Increasing evidence indicates that protein aggregation in bacteria does not necessarily imply loss of biological activity. Here, we have investigated the effect of growth-temperature on both the activity and stability of the inclusion bodies formed by a point-mutant of Abeta42 Alzheimer peptide, using green fluorescent protein as a reporter. The activity in the aggregates inversely correlates with the temperature. In contrast, inclusion bodies become more stable in front of chemical denaturation and proteolysis when temperature increases. Overall, the data herein open new perspectives in protein production, while suggesting a kinetic competition between protein folding and aggregation during recombinant protein expression.

Sequence and structural determinants of amyloid fibril formation

Amyloid fibril formation is a process that represents an essential feature of the chemistry of proteins and plays a central role in human pathology and the biology of living organisms. In this Account, we shall describe some of the recent results on the sequence and structural determinants of protein aggregation. We shall describe the factors that govern aggregation of unfolded peptides and proteins. We shall then try to summarize the factors that pertain to the aggregation of partially structured states and will show that even fully folded states of proteins have an ability to aggregate into at least early oligomers with no need to undergo substantial conformational changes.