Prediction of the aggregation propensity of proteins from the primary sequence: Aggregation properties of proteomes

Stability of Protein Pharmaceuticals: Recent Advances

There have been significant advances in the formulation and stabilization of proteins in the liquid state over the past years since our previous review. Our mechanistic understanding of protein-excipient interactions has increased, allowing one to develop formulations in a more rational fashion. The field has moved towards more complex and challenging formulations, such as high concentration formulations to allow for subcutaneous administration and co-formulation. While much of the published work has focused on mAbs, the principles appear to apply to any therapeutic protein, although mAbs clearly have some distinctive features. In this review, we first discuss chemical degradation reactions. This is followed by a section on physical instability issues. Then, more specific topics are addressed: instability induced by interactions with interfaces, predictive methods for physical stability and interplay between chemical and physical instability. The final parts are devoted to discussions how all the above impacts (co-)formulation strategies, in particular for high protein concentration solutions.'

Census of exposed aggregation-prone regions in proteomes

Loss of solubility usually leads to the detrimental elimination of protein function. In some cases, the protein aggregation is also required for beneficial functions. Given the duality of this phenomenon, it remains a fundamental question how natural selection controls the aggregation. The exponential growth of genomic sequence data and recent progress with in silico predictors of the aggregation allows approaching this problem by a large-scale bioinformatics analysis. Most of the aggregation-prone regions are hidden within the 3D structure, rendering them inaccessible for the intermolecular interactions responsible for aggregation. Thus, the most realistic census of the aggregation-prone regions requires crossing aggregation prediction with information about the location of the natively unfolded regions. This allows us to detect so-called 'exposed aggregation-prone regions' (EARs). Here, we analyzed the occurrence and distribution of the EARs in 76 reference proteomes from the three kingdoms of life. For this purpose, we used a bioinformatics pipeline, which provides a consensual result based on several predictors of aggregation. Our analysis revealed a number of new statistically significant correlations about the presence of EARs in different organisms, their dependence on protein length, cellular localizations, co-occurrence with short linear motifs and the level of protein expression. We also obtained a list of proteins with the conserved aggregation-prone sequences for further experimental tests. Insights gained from this work led to a deeper understanding of the relationship between protein evolution and aggregation.

Sequence variations of phase-separating proteins and resources for studying biomolecular condensates

Phase separation (PS) is an important mechanism underlying the formation of biomolecular condensates. Physiological condensates are associated with numerous biological processes, such as transcription, immunity, signaling, and synaptic transmission. Changes in particular amino acids or segments can disturb the protein's phase behavior and interactions with other biomolecules in condensates. It is thus presumed that variations in the phase-separating-prone domains can significantly impact the properties and functions of condensates. The dysfunction of condensates contributes to a number of pathological processes. Pharmacological perturbation of these condensates is proposed as a promising way to restore physiological states. In this review, we characterize the variations observed in PS proteins that lead to aberrant biomolecular compartmentalization. We also showcase recent advancements in bioinformatics of membraneless organelles (MLOs), focusing on available databases useful for screening PS proteins and describing endogenous condensates, guiding researchers to seek the underlying pathogenic mechanisms of biomolecular condensates.

Connecting the Dots: Macromolecular Crowding and Protein Aggregation

Proteins are one of the dynamic macromolecules that play a significant role in many physiologically important processes to sustain life on the earth. Proteins need to be properly folded into their active conformation to perform their function. Alteration in the protein folding process may lead to the formation of misfolded conformers. Accumulation of these misfolded conformers can result in the formation of protein aggregates which are attributed to many human pathological conditions including neurodegeneration, cataract, neuromuscular disorders, and diabetes. Living cells naturally have heterogeneous crowding environments with different concentrations of various biomolecules. Macromolecular crowding condition has been found to alter the protein conformation. Here in this review, we tried to show the relation between macromolecular crowding, protein aggregation, and its consequences.

In silico characterization of fructosyl peptide oxidase properties from Eupenicillium terrenum

Fructosyl peptide oxidase (FPOX) enzyme from Eupenicillium terrenum has a high potential to be applied as a diagnostic enzyme. The aim of the present study is the characterization of FPOX from E. terrenum using different bioinformatics tools. The computational prediction of the RNA and protein secondary structures of FPOX, solubility profile in Escherichia coli, stability, domains, and functional properties were performed. In the FPOX protein, six motifs were detected. The d-amino acid oxidase motif was found as the most important motif that is a FAD-dependent oxidoreductase. The cysteines including 97, 154, 234, 280, and 360 showed a lower score than -10 that have a low possibility for participitation in the formation of the SS bond. The 56.52% of FPOX amino acids are nonpolar. Random coils are dominant in the FPOX sequence, followed by alpha-helix and extended strand. The fpox gene is capable of generating a stable RNA secondary structure (-423.90 kcal/mol) in E. coli. FPOX has a large number of hydrophobic amino acids. FPOX showed a low solubility in E. coli which has several aggregation-prone sites in its 3-D structure. According to the scores, the best mutation candidate for increasing solubility was the conversion of methionine 302 to arginine. The melting temperature of FPOX based on its amino acid sequence was 55°C to 65°C. The amounts of thermodynamic parameters for the FPOX enzyme were -137.4 kcal/mol, -3.59 kcal/(mol K), and -6.8 kcal/mol for standard folding enthalpy, heat capacity, and folding free energy, respectively. In conclusion, the in silico study of proteins can provide a valuable method for better understanding the protein properties and functions for use in our purposes.

A3D 2.0 Update for the Prediction and Optimization of Protein Solubility

Protein aggregation propensity is a property imprinted in protein sequences and structures, being associated with the onset of human diseases and limiting the implementation of protein-based biotherapies. Computational approaches stand as cost-effective alternatives for reducing protein aggregation and increasing protein solubility. AGGRESCAN 3D (A3D) is a structure-based predictor of aggregation that takes into account the conformational context of a protein, aiming to identify aggregation-prone regions exposed in protein surfaces. Here we inspect the updated 2.0 version of the algorithm, which extends the application of A3D to previously inaccessible proteins and incorporates new modules to assist protein redesign. Among these features, the new server includes stability calculations and the possibility to optimize protein solubility using an experimentally validated computational pipeline. Finally, we employ defined examples to navigate the A3D RESTful service, a routine to handle extensive protein collections. Altogether, this chapter is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.

The effects of nanobubbles on the assembly of glucagon amyloid fibrils

Some recent studies have shown that the surface and interface play an important role in the assembly and aggregation of amyloid proteins. However, it is unclear how the gas-liquid interface affects the protein assembly at the nanometer scale although the presence of gas-liquid interfaces is very common in in vitro experiments. Nanobubbles have a large specific surface area, which provides a stage for interactions with various proteins and peptides on the nanometer scale. In this work, nanobubbles produced in solution were employed for studying the effects of the gas-liquid interface on the assembly of glucagon proteins. Atomic force microscopy (AFM) studies showed that nanobubble-treated glucagon solution formed fibrils with an apparent height of 4.02 ± 0.71 nm, in contrast to the fibrils formed with a height of 2.14 ± 0.53 nm in the control. Transmission electron microscopy (TEM) results also showed that nanobubbles promoted the assembly of glucagon to form more fibrils. Thioflavin T (ThT) fluorescence and Fourier transform infrared (FTIR) analyses indicated that the nanobubbles induced the change of the glucagon conformation to a β-sheet structure. A mechanism that explains how nanobubbles affect the assembly of glucagon amyloid fibrils was proposed based on the above-mentioned experimental results. Given the fact that there are a considerable amount of nanobubbles existing in protein solutions, our results indicate that nanobubbles should be considered for fully understanding the protein aggregation events in vitro.

Computational resources for identifying and describing proteins driving liquid-liquid phase separation

One of the most intriguing fields emerging in current molecular biology is the study of membraneless organelles formed via liquid–liquid phase separation (LLPS). These organelles perform crucial functions in cell regulation and signalling, and recent years have also brought about the understanding of the molecular mechanism of their formation. The LLPS field is continuously developing and optimizing dedicated in vitro and in vivo methods to identify and characterize these non-stoichiometric molecular condensates and the proteins able to drive or contribute to LLPS. Building on these observations, several computational tools and resources have emerged in parallel to serve as platforms for the collection, annotation and prediction of membraneless organelle-linked proteins. In this survey, we showcase recent advancements in LLPS bioinformatics, focusing on (i) available databases and ontologies that are necessary to describe the studied phenomena and the experimental results in an unambiguous way and (ii) prediction methods to assess the potential LLPS involvement of proteins. Through hands-on application of these resources on example proteins and representative datasets, we give a practical guide to show how they can be used in conjunction to provide in silico information on LLPS.

Effects of Dissolved Gases on the Amyloid Fibril Morphology

The onset or progression of numerous neurodegenerative diseases occurs due to aggregation of proteins that ultimately form fibrils. The assembly and morphology of fibrils are susceptible to environmental factors. In this work, we used atomic force microscopy (AFM) to investigate the effects of dissolved nitrogen and oxygen molecules on the morphology of fibrils formed by a hydrophobic amyloid peptide implicated in amyotrophic lateral sclerosis, 15 repeats of glycine-alanine, on a highly oriented pyrolytic graphite substrate. We started with preformed fibril solutions that were then diluted with buffers of different gas conditions, resulting in the aggregation of the fibrils into different morphologies that were revealed by AFM after adsorption on the substrate. Straight fibrils were observed in both degassed and ambient buffers, but a stronger lateral association was seen in degassed buffers. Smaller and softer fibrils were observed in O₂-supersaturated buffers, and plaque-like fibril aggregates of considerably large size were evident in N₂-supersaturated buffers. In overnight incubation experiments, we observed changes in both the morphology and height of the fibril aggregates, and their evolution varied with different gas conditions. These findings indicate that the gas type and concentration affect the aggregation of amyloid fibrils and may facilitate the development of biomaterial applications and treatments for amyloid-related diseases.

Extremely Amyloidogenic Single-Chain Analogues of Insulin's H-Fragment: Structural Adaptability of an Amyloid Stretch

Relatively short amino acid sequences often play a pivotal role in triggering protein aggregation leading to the formation of amyloid fibrils. In the case of insulin, various regions of A- and B-chains have been implicated as the most relevant to the protein's amyloidogenicity. Here, we focus on the highly amyloidogenic H-fragment of insulin comprising the disulfide-bonded N-terminal parts of both chains. Analysis of the aggregation behavior of single-chain peptide derivatives of the H-fragment suggests that the A-chain's part initiates the aggregation process while the disulfide-tethered B-chain reluctantly adapts to amyloid structure. Merging of both A- and B-parts into single-chain continuous peptides (A-B and B-A) results in extreme amyloidogenicity exceeding that of the double-chain H-fragment as reflected by almost instantaneous de novo fibrillization. Amyloid fibrils of A-B and B-A present distinct morphological and infrared traits and do not cross-seed insulin. Our study suggests that the N-terminal part of insulin's A-chain containing the intact Cys6-Cys11 intrachain disulfide bond may constitute insulin's major amyloid stretch which, through its bent conformation, enforces a parallel in-register alignment of β-strands. Comparison of the self-association behavior of H, A-B, and B-A peptides suggests that A-chain's N-terminal amyloid stretch is very versatile and adaptive to various structural contexts.

Computational prediction of protein aggregation: Advances in proteomics, conformation-specific algorithms and biotechnological applications

Protein aggregation is a widespread phenomenon that stems from the establishment of non-native intermolecular contacts resulting in protein precipitation. Despite its deleterious impact on fitness, protein aggregation is a generic property of polypeptide chains, indissociable from protein structure and function. Protein aggregation is behind the onset of neurodegenerative disorders and one of the serious obstacles in the production of protein-based therapeutics. The development of computational tools opened a new avenue to rationalize this phenomenon, enabling prediction of the aggregation propensity of individual proteins as well as proteome-wide analysis. These studies spotted aggregation as a major force driving protein evolution. Actual algorithms work on both protein sequences and structures, some of them accounting also for conformational fluctuations around the native state and the protein microenvironment. This toolbox allows to delineate conformation-specific routines to assist in the identification of aggregation-prone regions and to guide the optimization of more soluble and stable biotherapeutics. Here we review how the advent of predictive tools has change the way we think and address protein aggregation.

Understanding the thermal response of rice eukaryotic transcription factor eIF4A1 towards dynamic temperature stress: insights from expression profiling and molecular dynamics simulation

Eukaryotic translation initiation factors (eIFs) are the group of regulatory proteins that are involved in the initiation of translation events. Among them, eIF4A1, a member of the DEAD-box RNA helicase family, participates in a wide spectrum of activities which include, RNA splicing, ribosome biogenesis, and RNA degradation. It is well known that ATP-binding and subsequent hydrolysis activities are crucial for the functionality of such helicases. Although the stress-responsive upregulation of eIF4A1 has been reported in plants during stress, it is difficult to anticipate the functionality of the corresponding protein product. Therefore, to understand the activity of eIF4A1 in rice in response to temperature stress, we first conducted an expression analysis of the gene and further investigated the structural stability of the eIF4A1-ATP/Mg²⁺ complex through molecular dynamics (MD) simulations at different temperature conditions (277 K, 300 K, and 315 K). Our results demonstrated a three to fourfold increased expression of rice eIF4A1 both in root and shoot at 42 °C compared to control. Furthermore, the MD simulation portrayed strong ATP/Mg²⁺ binding at a higher temperature in comparison to control and cold temperature. Overall, the increased expression pattern of eIF4A1 and strong ATP/Mg²⁺ binding at higher temperature indicated the heat stress-tolerant capacity of the gene in rice. The results from our study will help in understanding the activity of gene and guide the researchers for screening of novel stress inducible candidate genes for the engineering of temperature stress tolerant plants.Communicated by Ramaswamy H. Sarma.

Structural investigation of APRs to improve the solubility of outer membrane protease (PgtE) from Salmonella enterica serotype typhi- A multi-constraint approach

Outer membrane proteins were playing a crucial role on the several functions controlled by cell membranes even though they are not naturally expressed at higher levels. In order to obtain biologically active protein, the denaturation of these inclusion bodies must be optimized using chaotropic agents. Hence, this study focuses on improving the yield of Outer Membrane Protease (PgtE) from Salmonella enterica serotype Typhi (S. Typhi) using chaotropes and additives. Denaturation methods were tried with various pH, detergents, and reducing agents were used to optimize the solubility of PgtE with biologically active form. Due to the aggregation, we failed to achieve the maximum yield of PgtE. Consequently, we predicted 9 Aggregation Prone Regions (APRs) in PgtE, which are mutated by known structural Gatekeepers. We calculated the Aggregation Index (AI) of PgtE with 10 mM of aspartic acid as an additive in optimized buffer. In addition, the mutations at specific positions within the protein structure can act as APRs suppressors without affecting protein stability with CABS flex dynamics. The multiple sequence analysis demonstrate that aspartic acid is appropriate denaturing additive for other Gram-negative pathogens of Omptin family.

pH-Dependent Aggregation in Intrinsically Disordered Proteins Is Determined by Charge and Lipophilicity

Protein aggregation is associated with an increasing number of human disorders and premature aging. Moreover, it is a central concern in the manufacturing of recombinant proteins for biotechnological and therapeutic applications. Nevertheless, the unique architecture of protein aggregates is also exploited by nature for functional purposes, from bacteria to humans. The relevance of this process in health and disease has boosted the interest in understanding and controlling aggregation, with the concomitant development of a myriad of algorithms aimed to predict aggregation propensities. However, most of these programs are blind to the protein environment and, in particular, to the influence of the pH. Here, we developed an empirical equation to model the pH-dependent aggregation of intrinsically disordered proteins (IDPs) based on the assumption that both the global protein charge and lipophilicity depend on the solution pH. Upon its parametrization with a model IDP, this simple phenomenological approach showed unprecedented accuracy in predicting the dependence of the aggregation of both pathogenic and functional amyloidogenic IDPs on the pH. The algorithm might be useful for diverse applications, from large-scale analysis of IDPs aggregation properties to the design of novel reversible nanofibrillar materials.

In vitro and in silico assessment of the developability of a designed monoclonal antibody library

Despite major advances in antibody discovery technologies, the successful development of monoclonal antibodies (mAbs) into effective therapeutic and diagnostic agents can often be impeded by developability liabilities, such as poor expression, low solubility, high viscosity and aggregation. Therefore, strategies to predict at the early phases of antibody development the risk of late-stage failure of antibody candidates are highly valuable. In this work, we employ the in silico solubility predictor CamSol to design a library of 17 variants of a humanized mAb predicted to span a broad range of solubility values, and we examine their developability potential with a battery of commonly used in vitro and in silico assays. Our results demonstrate the ability of CamSol to rationally enhance mAb developability, and provide a quantitative comparison of in vitro developability measurements with each other and with more resource-intensive solubility measurements, as well as with in silico predictors that offer a potentially faster and cheaper alternative. We observed a strong correlation between predicted and experimentally determined solubility values, as well as with measurements obtained using a panel of in vitro developability assays that probe non-specific interactions. These results indicate that computational methods have the potential to reduce or eliminate the need of carrying out laborious in vitro quality controls for large numbers of lead candidates. Overall, our study provides support to the emerging view that the implementation of in silico tools in antibody discovery campaigns can ensure rapid and early selection of antibodies with optimal developability potential.

Effects of nanobubbles on peptide self-assembly

It is believed that the aggregation of amyloid proteins or peptides is promoted by the presence of an air-water interface, and substantial evidence suggests that the characteristics of the air-water interface play critical roles in foam-induced protein aggregation during foam fractionation. However, the effects of the air-water interface on the self-assembly of amyloid-like peptides have not yet been elucidated clearly at the nanometer scale. In this work, air nanobubbles produced in water solution were employed for studying interfacial effects on the self-assembly of a model amyloid peptide termed P11. An atomic force microscopy study showed that the air nanobubbles induced the formation of peptide fibrils with a 9-13 nm helix structure in the P11 solution. Thioflavin T fluorescence and circular dichroism spectroscopic analysis indicated that the nanobubbles induced the change of the peptide conformation to a β-sheet structure. Based on these observations, we have proposed a mechanism to explain how the nanobubbles affect the self-assembly of the P11 peptide at the nanometer scale. Since air nanobubbles are present in water solutions in addition to an air-water interface in normal experiments in vitro, our results indicate that nanobubbles must be taken into account to achieve a complete understanding of protein aggregation events.

Prediction and Reduction of the Aggregation of Monoclonal Antibodies

Protein aggregation remains a major area of focus in the production of monoclonal antibodies. Improving the intrinsic properties of antibodies can improve manufacturability, attrition rates, safety, formulation, titers, immunogenicity, and solubility. Here, we explore the potential of predicting and reducing the aggregation propensity of monoclonal antibodies, based on the identification of aggregation-prone regions and their contribution to the thermodynamic stability of the protein. Although aggregation-prone regions are thought to occur in the antigen binding region to drive hydrophobic binding with antigen, we were able to rationally design variants that display a marked decrease in aggregation propensity while retaining antigen binding through the introduction of artificial aggregation gatekeeper residues. The reduction in aggregation propensity was accompanied by an increase in expression titer, showing that reducing protein aggregation is beneficial throughout the development process. The data presented show that this approach can significantly reduce liabilities in novel therapeutic antibodies and proteins, leading to a more efficient path to clinical studies.

Bacterial Inclusion Bodies: Discovering Their Better Half

Bacterial inclusion bodies (IBs) are functional, non-toxic amyloids occurring in recombinant bacteria showing analogies with secretory granules of the mammalian endocrine system. The scientific interest in these mesoscale protein aggregates has been historically masked by their status as a hurdle in recombinant protein production. However, progressive understanding of how the cell handles the quality of recombinant polypeptides and the main features of their intriguing molecular organization has stimulated the interest in inclusion bodies and spurred their use in diverse technological fields. The engineering and tailoring of IBs as functional protein particles for materials science and biomedicine is a good example of how formerly undesired bacterial byproducts can be rediscovered as promising functional materials for a broad spectrum of applications.

Oligomerization of FVFLM peptides and their ability to inhibit beta amyloid peptides aggregation: consideration as a possible model

Preeclampsia, a pregnancy-specific disorder, shares typical pathophysiological features with protein misfolding disorders including Alzheimer's disease. Characteristic for preeclampsia is the involvement of multiple proteins of which fragments of SERPINA1 and β-amyloid co-aggregate in urine and placenta of preeclamptic women. To explore the biophysical basis of this interaction, we investigated the multidimensional efficacy of the FVFLM sequence in SERPINA1, as a model inhibitory agent of β-amyloid aggregation. After studying the oligomerization of FVFLM peptides using all-atom molecular dynamics simulations with the GROMOS43a1 force field and explicit water, we report that FVFLM can aggregate and its aggregation is spontaneous with a remarkably faster rate than that recorded for KLVFF (aggregation "hot-spot" from β-amyloid). The fast kinetics of FVFLM aggregation was found to be driven primarily by core-like aromatic interactions originating from the anti-parallel orientation of complementarily uncharged strands. The conspicuously stable aggregation mechanism observed for FVFLM peptides is found not to conform to the popular 'dock-lock' scheme. We also found high propensity of FVFLM for KLVFF binding. When present, FVFLM disrupts the β-amyloid aggregation pathway and we propose that FVFLM-like peptides might be used to prevent the assembly of full-length Aβ or other pro-amyloidogenic peptides into amyloid fibrils.

The GOR Method of Protein Secondary Structure Prediction and Its Application as a Protein Aggregation Prediction Tool

The GOR method of protein secondary structure prediction is described. The original method was published by Garnier, Osguthorpe, and Robson in 1978 and was one of the first successful methods to predict protein secondary structure from amino acid sequence. The method is based on information theory, and an assumption that information function of a protein chain can be approximated by a sum of information from single residues and pairs of residues. The analysis of frequencies of occurrence of secondary structure for singlets and doublets of residues in a protein database enables prediction of secondary structure for new amino acid sequences. Because of these simple physical assumptions the GOR method has a conceptual advantage over other later developed methods such as PHD, PSIPRED, and others that are based on Machine Learning methods (like Neural Networks), give slightly better predictions, but have a "black box" nature. The GOR method has been continuously improved and modified for 30 years with the last GOR V version published in 2002, and the GOR V server developed in 2005. We discuss here the original GOR method and the GOR V program and the web server. Additionally we discuss new highly interesting and important applications of the GOR method to chameleon sequences in protein folding simulations, and for prediction of protein aggregation propensities. Our preliminary studies show that the GOR method is a promising and efficient alternative to other protein aggregation predicting tools. This shows that the GOR method despite being almost 40 years old is still important and has significant potential in application to new scientific problems.

Molecular dynamics simulations and docking enable to explore the biophysical factors controlling the yields of engineered nanobodies

Nanobodies (VHHs) have proved to be valuable substitutes of conventional antibodies for molecular recognition. Their small size represents a precious advantage for rational mutagenesis based on modelling. Here we address the problem of predicting how Camelidae nanobody sequences can tolerate mutations by developing a simulation protocol based on all-atom molecular dynamics and whole-molecule docking. The method was tested on two sets of nanobodies characterized experimentally for their biophysical features. One set contained point mutations introduced to humanize a wild type sequence, in the second the CDRs were swapped between single-domain frameworks with Camelidae and human hallmarks. The method resulted in accurate scoring approaches to predict experimental yields and enabled to identify the structural modifications induced by mutations. This work is a promising tool for the in silico development of single-domain antibodies and opens the opportunity to customize single functional domains of larger macromolecules.

Rational design of therapeutic mAbs against aggregation through protein engineering and incorporation of glycosylation motifs applied to bevacizumab

The aggregation of biotherapeutics is a major hindrance to the development of successful drug candidates; however, the propensity to aggregate is often identified too late in the development phase to permit modification to the protein's sequence. Incorporating rational design for the stability of proteins in early discovery has numerous benefits. We engineered out aggregation-prone regions on the Fab domain of a therapeutic monoclonal antibody, bevacizumab, to rationally design a biobetter drug candidate. With the purpose of stabilizing bevacizumab with respect to aggregation, 2 strategies were undertaken: single point mutations of aggregation-prone residues and engineering a glycosylation site near aggregation-prone residues to mask these residues with a carbohydrate moiety. Both of these approaches lead to comparable decreases in aggregation, with an up to 4-fold reduction in monomer loss. These single mutations and the new glycosylation pattern of the Fab domain do not modify binding to the target. Biobetters with increased stability against aggregation can therefore be generated in a rational manner, by either removing or masking the aggregation-prone region or crowding out protein-protein interactions.

Characterization of Amyloid Cores in Prion Domains

Amyloids consist of repetitions of a specific polypeptide chain in a regular cross-β-sheet conformation. Amyloid propensity is largely determined by the protein sequence, the aggregation process being nucleated by specific and short segments. Prions are special amyloids that become self-perpetuating after aggregation. Prions are responsible for neuropathology in mammals, but they can also be functional, as in yeast prions. The conversion of these last proteins to the prion state is driven by prion forming domains (PFDs), which are generally large, intrinsically disordered, enriched in glutamines/asparagines and depleted in hydrophobic residues. The self-assembly of PFDs has been thought to rely mostly on their particular amino acid composition, rather than on their sequence. Instead, we have recently proposed that specific amyloid-prone sequences within PFDs might be key to their prion behaviour. Here, we demonstrate experimentally the existence of these amyloid stretches inside the PFDs of the canonical Sup35, Swi1, Mot3 and Ure2 prions. These sequences self-assemble efficiently into highly ordered amyloid fibrils, that are functionally competent, being able to promote the PFD amyloid conversion in vitro and in vivo. Computational analyses indicate that these kind of amyloid stretches may act as typical nucleating signals in a number of different prion domains.

Staphylococcal Bap Proteins Build Amyloid Scaffold Biofilm Matrices in Response to Environmental Signals

Biofilms are communities of bacteria that grow encased in an extracellular matrix that often contains proteins. The spatial organization and the molecular interactions between matrix scaffold proteins remain in most cases largely unknown. Here, we report that Bap protein of Staphylococcus aureus self-assembles into functional amyloid aggregates to build the biofilm matrix in response to environmental conditions. Specifically, Bap is processed and fragments containing at least the N-terminus of the protein become aggregation-prone and self-assemble into amyloid-like structures under acidic pHs and low concentrations of calcium. The molten globule-like state of Bap fragments is stabilized upon binding of the cation, hindering its self-assembly into amyloid fibers. These findings define a dual function for Bap, first as a sensor and then as a scaffold protein to promote biofilm development under specific environmental conditions. Since the pH-driven multicellular behavior mediated by Bap occurs in coagulase-negative staphylococci and many other bacteria exploit Bap-like proteins to build a biofilm matrix, the mechanism of amyloid-like aggregation described here may be widespread among pathogenic bacteria.

Major components of the biofilm matrix scaffold are proteins that assemble to create a unified structure that maintain bacteria attached to each other and to surfaces. We provide evidence that a surface protein present in several staphylococcal species forms functional amyloid aggregates to build the biofilm matrix in response to specific environmental conditions. Under low Ca²⁺ concentrations and acidic pH, Bap is processed and forms insoluble aggregates with amyloidogenic properties. When the Ca²⁺ concentration increases, metal-coordinated Bap adopts a structurally more stable conformation and as a consequence, the N-terminal region is unable to assemble into amyloid aggregates. The control of Bap cleavage and assembly helps to regulate biofilm matrix development as a function of environmental changes.

Amyloids or prions? That is the question

Despite major efforts devoted to understanding the phenomenon of prion transmissibility, it is still poorly understood how this property is encoded in the amino acid sequence. In recent years, experimental data on yeast prion domains allow to start at least partially decrypting the sequence requirements of prion formation. These experiments illustrate the need for intrinsically disordered sequence regions enriched with a particularly high proportion of glutamine and asparagine. Bioinformatic analysis suggests that these regions strike a balance between sufficient amyloid nucleation propensity on the one hand and disorder on the other, which ensures availability of the amyloid prone regions but entropically prevents unwanted nucleation and facilitates brittleness required for propagation.

Mutational probing of protein aggregates to design aggregation-resistant proteins

Characterization of amorphous protein aggregates may offer insights into the process of aggregation. Eleven single amino acid mutants of lipase (LipA of Bacillus subtilis) were subjected to temperature-induced aggregation, and the resultant aggregates were characterized for recovery of activity in the presence of guanidinium chloride (GdmCl). Based on activity recovery profiles of the aggregates, the mutants could be broadly assigned into four groups. By including at least one mutation from each group, a mutant was generated that showed an increase of ~ 10 °C in melting temperature (T m) compared to the wild-type and did not aggregate even at 75 °C. This method explores characterization of amorphous protein aggregates in the presence of GdmCl and helps in identifying mutations involved in protein aggregation.

Curing bacterial infections with protein aggregates

A growing number of human diseases seem to be associated with protein misfolding and deposition into aggregates. Bednarska and colleagues exploit the cytotoxic nature of protein aggregates to target bacterial infections. Protein aggregation is at the same time generic and sequence dependent; this allowed the authors to develop novel aggregation-prone antimicrobial peptides that penetrate bacteria and induce a peptide specific proteostatic collapse that leads to fast bacterial death, without any observable effects on host cells. The applicability of this intriguing strategy was demonstrated by curing animal models from bacterial sepsis. Although the precise mechanisms underlying the bactericidal activity of the peptide aggregates are still not clear, there is no doubt that this approach offers an exciting therapeutic alternative to conventional antibiotics.

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.

What makes a protein sequence a prion?

Typical amyloid diseases such as Alzheimer's and Parkinson's were thought to exclusively result from de novo aggregation, but recently it was shown that amyloids formed in one cell can cross-seed aggregation in other cells, following a prion-like mechanism. Despite the large experimental effort devoted to understanding the phenomenon of prion transmissibility, it is still poorly understood how this property is encoded in the primary sequence. In many cases, prion structural conversion is driven by the presence of relatively large glutamine/asparagine (Q/N) enriched segments. Several studies suggest that it is the amino acid composition of these regions rather than their specific sequence that accounts for their priogenicity. However, our analysis indicates that it is instead the presence and potency of specific short amyloid-prone sequences that occur within intrinsically disordered Q/N-rich regions that determine their prion behaviour, modulated by the structural and compositional context. This provides a basis for the accurate identification and evaluation of prion candidate sequences in proteomes in the context of a unified framework for amyloid formation and prion propagation.

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.

Amyloid formation by human carboxypeptidase D transthyretin-like domain under physiological conditions

Protein aggregation is linked to a growing list of diseases, but it is also an intrinsic property of polypeptides, because the formation of functional globular proteins comes at the expense of an inherent aggregation propensity. Certain proteins can access aggregation-prone states from native-like conformations without the need to cross the energy barrier for unfolding. This is the case of transthyretin (TTR), a homotetrameric protein whose dissociation into its monomers initiates the aggregation cascade. Domains with structural homology to TTR exist in a number of proteins, including the M14B subfamily carboxypeptidases. We show here that the monomeric transthyretin-like domain of human carboxypeptidase D aggregates under close to physiological conditions into amyloid structures, with the population of folded but aggregation-prone states being controlled by the conformational stability of the domain. We thus confirm that the TTR fold keeps a generic residual aggregation propensity upon folding, resulting from the presence of preformed amyloidogenic β-strands in the native state. These structural elements should serve for functional/structural purposes, because they have not been purged out by evolution, but at the same time they put proteins like carboxypeptidase D at risk of aggregation in biological environments and thus can potentially lead to deposition diseases.

Research on protein thermal condensation detection based on phase modulation SPR imaging

This article presents a novel SPR imaging biomolecular interaction detection method based on time domain phase modulation. An experimental apparatus of SPR imaging biomolecular interaction detection based on TDPM is established to detect biomolecular interaction. During the experimental pretreatment process, we prepared the 2×2 lysozyme array chip and detected lysozyme thermal condensation state with the experimental apparatus. Using the Stoilov algorithm, we were able to extract the changed phase information as well as obtain the interactive SPR curves and calculate kinetic parameters. This method can sensitively acquire real-time phase change caused by biomolecular interaction based on interference imaging and resolve the related bioinformation, which is a potential tool for proteomics research.

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.

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.

The presence of an air-water interface affects formation and elongation of α-Synuclein fibrils

The aggregation of human α-Synuclein (α-Syn) into amyloid fibrils is related to the onset of multiple diseases termed synucleinopathies. Substantial evidence suggests that hydrophobic-hydrophilic interfaces promote the aggregation of amyloidogenic proteins and peptides in vitro. In this work the effect of the air-water interface (AWI) on α-Syn aggregation is investigated by means of thioflavin T binding measurements, dynamic light scattering, size-exclusion chromatography, electron microscopy, and atomic force microscopy. Measurements were performed with the monomeric protein alone or together with preformed seeds. In presence of the AWI, α-Syn aggregates readily into amyloid fibrils that remain adsorbed to the AWI. Instead, when the AWI is removed from the samples by replacing it with a solid-liquid interface, the interfacial aggregation of monomeric α-Syn is greatly reduced and no significant increase in ThT fluorescence is detected in the bulk, even at 900 μM concentration. Bulk aggregation is observed only when a sufficient amount of preformed seeds is added, and the initial slope of the kinetics scales with the amount of seeds as expected for first order kinetics. By contrast, in seeded experiments with the AWI, the initial slope is one order of magnitude lower and secondary nucleation pathways appear instead to be dominant. Thus, interfaces play multiple roles in the aggregation of α-Syn, influencing primary nucleation, aggregate elongation, and secondary nucleation processes. Interfacial effects must therefore be taken into account to achieve a complete understanding of protein aggregation events in vitro as well as in vivo.

Structure predictions of two Bauhinia variegata lectins reveal patterns of C-terminal properties in single chain legume lectins

Bauhinia variegata lectins (BVL-I and BVL-II) are single chain lectins isolated from the plant Bauhinia variegata. Single chain lectins undergo post-translational processing on its N-terminal and C-terminal regions, which determines their physiological targeting, carbohydrate binding activity and pattern of quaternary association. These two lectins are isoforms, BVL-I being highly glycosylated, and thus far, it has not been possible to determine their structures. The present study used prediction and validation algorithms to elucidate the likely structures of BVL-I and -II. The program Bhageerath-H was chosen from among three different structure prediction programs due to its better overall reliability. In order to predict the C-terminal region cleavage sites, other lectins known to have this modification were analysed and three rules were created: (1) the first amino acid of the excised peptide is small or hydrophobic; (2) the cleavage occurs after an acid, polar, or hydrophobic residue, but not after a basic one; and (3) the cleavage spot is located 5-8 residues after a conserved Leu amino acid. These rules predicted that BVL-I and -II would have fifteen C-terminal residues cleaved, and this was confirmed experimentally by Edman degradation sequencing of BVL-I. Furthermore, the C-terminal analyses predicted that only BVL-II underwent α-helical folding in this region, similar to that seen in SBA and DBL. Conversely, BVL-I and -II contained four conserved regions of a GS-I association, providing evidence of a previously undescribed X4+unusual oligomerisation between the truncated BVL-I and the intact BVL-II. This is the first report on the structural analysis of lectins from Bauhinia spp. and therefore is important for the characterisation C-terminal cleavage and patterns of quaternary association of single chain lectins.

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.

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.

Insights into the potential aggregation liabilities of the b12 Fab fragment via elevated temperature molecular dynamics

Aggregation is a common hurdle faced during the development of antibody therapeutics. In this study, we explore the potential aggregation liabilities of the Fab (fragment antigen-binding) from a human IgG1κ antibody via multiple elevated temperature molecular dynamic simulations, analogous to accelerated stability studies performed during formulation development. Deformation and solvent exposure changes in response to thermal stress were monitored for individual structural domains (V(H), V(L), C(H)1 and C(L)), their interfaces (V(H):V(L) and C(H)1:C(L)), edge beta-strands and sequence-predicted aggregation-prone regions (APRs). During simulations, domain interfaces deformed prior to the unfolding of individual domains. However, interfacial beta-strands retained their secondary structure and remained solvent protected longer than all other strands or loops. Thus, APRs located in interfacial beta-strands are effectively blocked from self-association. Structural deformations were also observed in complementarity-determining regions, edge beta-strands and adjoining framework beta-strands, which increased their solvent-accessible surface area and exposed APRs in these regions. From the analysis of these structural changes, two potential aggregation liabilities were identified in the V(H) domain of this Fab. Insights gained from this investigation should be useful in devising a rational structure-based strategy for the design and selection of antibody candidates with high potency and improved developability.

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.

Understanding protein aggregation from the view of monomer dynamics

Much work in recent years has been devoted to understanding the complex process of protein aggregation. This review looks at the earliest stages of aggregation, long before the formation of fibrils that are the hallmark of many aggregation-based diseases, and proposes that the first steps are controlled by the reconfiguration dynamics of the monomer. When reconfiguration is much faster or much slower than bimolecular diffusion, then aggregation is slow, but when they are similar, aggregation is fast. The experimental evidence for this model is reviewed and the prospects for small molecule aggregation inhibitors to prevent disease are discussed.