Predicting and Measuring Molecular Mechanisms of Protein Aggregation

Protein aggregation is a hallmark of a number of neurodegenerative disorders including Alzheimer’s Disease, Huntington’s Disease, and Amyotrophic Lateral Sclerosis. Despite the common occurrence of protein aggregation in disease, the fundamental mechanisms controlling the propensity of a protein to aggregate are not well understood. Over the past decade, one of the most significant advancements in the field of understanding protein aggregation has been the development of several aggregation prediction algorithms. In this study, two separate approaches were used to investigate the detailed molecular mechanisms of protein aggregation. First, a thorough investigation that compared nine protein aggregation prediction techniques was performed. Protein aggregation propensity calculations were performed on wild type and mutant sequences of three diverse proteins including Superoxide Dismutase (SOD), human Acylphosphatase (AcP), and the amyloid beta peptide (Aβ42). This study presents the first wide-scale comparison of such a large number of prediction algorithms, and additionally provides new information on the ability of the algorithms to successfully predict the experimentally observed aggregation of several mutations of diverse proteins. The algorithms were predominantly developed based on a set of known amyloid-forming proteins and peptides, however, are quite diverse in the way they were designed and the proteins on which they were tested. Interestingly, significant variation was observed when predicting the aggregation propensity of identical sequences by multiple techniques, indicating that the algorithms do not possess a consensus on the primary factors that govern aggregation. Further analyses compared predicted and observed aggregation data for several mutants of the test proteins. The aggregation prediction algorithms predominantly demonstrated poor to moderate correlations with observed aggregation, and the strongest correlations occurred in instances where the test data was used in the development of the algorithms. The general lack of ability of the algorithms to predict the aggregation patterns of more than one test protein suggests that aggregation may be a much more specific process that it is generally attributed to be in that there may be inherently different properties modulating the aggregation mechanisms of different proteins towards varying aggregate structures. The second component of this project was to experimentally examine the role of salt in influencing protein aggregation as a method to elucidate the specific molecular mechanisms controlling protein aggregation pathways. The ALS-causing SOD1 mutation, A4V, in both the oxidized and reduced apo form, was used as a model protein. The role of NaCl and Na2SO4 in mediating protein aggregation was studied using several techniques. While oxidized apo A4V showed very little evidence of aggregation even in the presence of salt, for reduced apo, aggregates readily formed and were promoted by the addition of salt. This finding correlated with the increasing kosmotropic nature of the salt as described by the Hofmeister series. The aggregates formed in the presence of salt contained intermolecular disulphide bonds and demonstrated ANS and ThT binding, indicating aggregates are likely to be largely hydrophobic and possess beta-sheet morphology. Salt promotes protein aggregation in two ways: 1) electrostatic interactions shield protein charges and reduce repulsion between proteins, and 2) specific interactions stabilize various aggregation-prone conformations of the protein. This work is evidence of the important role of salt in influencing protein aggregation and provides a framework for future studies into the complex effects of solution conditions in modulating protein aggregation pathways. Both aspects of this study contribute greatly to furthering the understanding of the molecular mechanisms governing protein aggregation. This is of particular importance to neurodegenerative diseases, where uncovering the factors that modulate the formation of toxic aggregate species is important for disease treatment and prevention. The potential aggregation mechanisms of SOD1, and the contributions it may play in ALS pathogenesis, will be discussed throughout this study.1 yea

Effect of Oxidative Damage on the Stability and Dimerization of Superoxide Dismutase 1

During their life cycle, proteins are subject to different modifications involving reactive oxygen species. Such oxidative damage to proteins may lead to the formation of insoluble aggregates and cytotoxicity and is associated with age-related disorders including neurodegenerative diseases, cancer, and diabetes. Superoxide dismutase 1 (SOD1), a key antioxidant enzyme in human cells, is particularly susceptible to such modifications. Moreover, this homodimeric metalloenzyme has been directly linked to both familial and sporadic amyotrophic lateral sclerosis (ALS), a devastating, late-onset motor neuronal disease, with more than 150 ALS-related mutations in the SOD1 gene. Importantly, oxidatively damaged SOD1 aggregates have been observed in both familial and sporadic forms of the disease. However, the molecular mechanisms as well as potential implications of oxidative stress in SOD1-induced cytotoxicity remain elusive. In this study, we examine the effects of oxidative modification on SOD1 monomer and homodimer stability, the key molecular properties related to SOD1 aggregation. We use molecular dynamics simulations in combination with thermodynamic integration to study microscopic-level site-specific effects of oxidative "mutations" at the dimer interface, including lysine, arginine, proline and threonine carbonylation, and cysteine oxidation. Our results show that oxidative damage of even single residues at the interface may drastically destabilize the SOD1 homodimer, with several modifications exhibiting a comparable effect to that of the most drastic ALS-causing mutations known. Additionally, we show that the SOD1 monomer stability decreases upon oxidative stress, which may lead to partial local unfolding and consequently to increased aggregation propensity. Importantly, these results suggest that oxidative stress may play a key role in development of ALS, with the mutations in the SOD1 gene being an additional factor

Computational Design of Stable and Soluble Biocatalysts

Natural enzymes are delicate biomolecules possessing only marginal thermodynamic stability. Poorly stable, misfolded, and aggregated proteins lead to huge economic losses in the biotechnology and biopharmaceutical industries. Consequently, there is a need to design optimized protein sequences that maximize stability, solubility, and activity over a wide range of temperatures and pH values in buffers of different composition and in the presence of organic cosolvents. This has created great interest in using computational methods to enhance biocatalysts' robustness and solubility. Suitable methods include (i) energy calculations, (ii) machine learning, (iii) phylogenetic analyses, and (iv) combinations of these approaches. We have witnessed impressive progress in the design of stable enzymes over the last two decades, but predictions of protein solubility and expressibility are scarce. Stabilizing mutations can be predicted accurately using available force fields, and the number of sequences available for phylogenetic analyses is growing. In addition, complex computational workflows are being implemented in intuitive web tools, enhancing the quality of protein stability predictions. Conversely, solubility predictors are limited by the lack of robust and balanced experimental data, an inadequate understanding of fundamental principles of protein aggregation, and a dearth of structural information on folding intermediates. Here we summarize recent progress in the development of computational tools for predicting protein stability and solubility, critically assess their strengths and weaknesses, and identify apparent gaps in data and knowledge. We also present perspectives on the computational design of stable and soluble biocatalysts

Unfolded, misfolded, and self-organized short alanine-rich peptides: implications for fundamental science, human disease, and biotechnology

Protein folding is the reversible transition by which an unordered polypeptide chain attains its functional 3-D native structure. A detailed understanding of the principles which govern the protein folding process, such as how sequence codes for structure, remains elusive. Achieving a complete picture of the folding process requires information regarding structural preferences in the unfolded state. Moreover, understanding the principles which govern protein aggregation is of significant biomedical and biotechnological importance. Herein, short alanine-based peptides are used as model systems for studying both the structural preferences in the unfolded state as well as protein aggregation in relation to human disease, and exploitation of the self-assembly process for various biotechnological applications.It is now a central dogma of protein science that the unfolded state is not conformationally random, as was originally believed, but that, instead, residual structure exists. Here, we elucidate the conformational propensities of alanine in the unfolded state using short alanine-rich peptides as model systems. The intrinsic conformational propensities of alanine, as well as nearest neighbor effects are illuminated using various vibrational spectroscopic methods, combined with NMR results.Protein and peptide aggregation is affiliated with various seemingly unrelated diseases, including several neurodegenerative diseases and the systemic amyloidoses. It is of current belief that aggregation is a general feature of the protein energy landscape, suggesting that the various unrelated human pathologies linked to protein aggregation are linked by common principles. Herein, fibril formation of a short alanine-based peptide with no known disease affiliation is probed by vibrational circular dichroism (VCD) spectroscopy. In particular, it is demonstrated that peptide fibrils give rise to VCD intensity enhancement, illustrating the use of the technique as a novel means to probe aggregation kinetics.In addition to the biomedical relevance, protein and peptide self-assembly can be exploited as a means of constructing biomaterials with inherent biofunctionality. In this regard, oligopeptide-based hydrogels have shown potential as drug delivery systems and tissue engineering scaffolds. Herein, the unique properties of a novel class of self-assembling alanine-rich oligoopeptides are presented. In particular, it is demonstrated that conformational instability can be exploited to tune the physicochemical properties of hydrogels formed by such systems, for the potential use in various biotechnological applications.Ph.D., Physical Chemistry -- Drexel University, 201

Experimental Determination of the Topology of the HIV-1 gp41 C-Terminal Tail

The C-terminal tail (CTT) of HIV gp41 has been traditionally viewed as a cytoplasmic domain. Genetic studies demonstrating functional interactions between the CTT and various intracellular partners have implicitly reinforced this view. However, antibody neutralization data and biochemical studies have suggested that the CTT is, or can be, externally localized under certain condition. Additionally, other studies have demonstrated that the CTT is dispensable for in vitro virus replication. After nearly three decades of HIV research, the function and structure of the CTT remain elusive. Our goals, then, were twofold: (i) to determine the overall conservation of the CTT in an attempt to provide an understanding of the functional and structural relevance of the CTT; and, (ii) to provide an experimental topological map of the CTT in an attempt to understand and align observed CTT topology(ies) with the functional necessity of a cytoplasmic CTT. We believe that we made significant contributions to the understanding of CTT topology and its relationship to current published functional studies. The initial studies demonstrated that the CTT sequence is conserved at a level that is intermediate between the highly variable gp120 region and the relatively conserved gp41 ectodomain. Additionally, physicochemical and structural properties of CTT sequences were found to be conserved in spite of the relatively high sequencevariability. These studies demonstrated for the first time that the CTT sequence, while highly variable, contains highly conserved structural and chemical properties that suggest a functional requirement for the CTT. Topology studies of the CTT indicated that the topology of the CTT can be distinct between the surface of Env-expressing cells and viral particles. Additionally, dynamic rearrangement of the CTT was observed as a function of antibody neutralization. These findings prompted a theoretical study of gp41 CTT predicted topology and the proposal of a topological model that we believe is consistent with all published studies regarding the localization of the CTT

Faithful chaperones

This review describes the properties of some rare eukaryotic chaperones that each assist in the folding of only one target protein. In particular, we describe (1) the tubulin cofactors, (2) p47, which assists in the folding of collagen, (3) α-hemoglobin stabilizing protein (AHSP), (4) the adenovirus L4-100 K protein, which is a chaperone of the major structural viral protein, hexon, and (5) HYPK, the huntingtin-interacting protein. These various-sized proteins (102–1,190 amino acids long) are all involved in the folding of oligomeric polypeptides but are otherwise functionally unique, as they each assist only one particular client. This raises a question regarding the biosynthetic cost of the high-level production of such chaperones. As the clients of faithful chaperones are all abundant proteins that are essential cellular or viral components, it is conceivable that this necessary metabolic expenditure withstood evolutionary pressure to minimize biosynthetic costs. Nevertheless, the complexity of the folding pathways in which these chaperones are involved results in error-prone processes. Several human disorders associated with these chaperones are discussed

Exploring the Impact of the E. coli Proteostasis Network on the Folding Fate of Proteins with Different Intrinsic Biophysical Properties

The three-dimensional (3D) native structure of most proteins is crucial for their functions. Despite the complex cellular environment and the variety of challenges that proteins experience as they fold, proteins can still fold to their native states with high fidelity. The reason for this is the presence of the cellular proteostasis network (PN), consisting of molecular chaperones and degradation enzymes, that collaborates to maintain proteostasis, in which the necessary levels of functional proteins are optimized. Although extensive research has been carried out on the mechanisms of individual components of the proteostasis network, little is known about how these components contribute to the functioning of the network as a whole. A new protein can have three folding fates: natively folded, aggregated, or degraded. The fate is determined by both a protein’s intrinsic biophysical properties and the cellular proteostasis network through kinetic partitioning. To understand the interplay between a protein’s intrinsic biophysical properties and the cellular proteostasis network, an integrated computational and experimental approach was used. The folding fates of model proteins with different intrinsic biophysical properties under varying conditions of the proteostasis network were determined. Using FoldEco, the effects of the kinetic and thermodynamic properties of proteins on their folding fates were investigated systematically, and predictions were consistent with wet lab experiments. The folding fate of a protein is under a thermo-kinetic limitation, which indicates that the fate depends on either the kinetics or thermodynamics, but (for the most part) not on both at the same time. Different proteins behave according to the values of their limiting properties. Furthermore, up-regulation of the entire proteostasis network through the σ32 transcription factor has beneficial effects on model proteins with low stabilities and high aggregation propensities. However, the effects of up-regulation of individual chaperones or the major degradation enzyme, Lon are substrate-dependent and are related to their biophysical properties. Furthermore, KJE, GroELS, and Lon form an efficacious triad for maintaining proteostasis, and their contributions depend on the biophysical properties of their substrates, and on the concentrations of these PN components and substrates at any given time

A Computational Study of Amyloid Fibrils and their Structural Properties

The term amyloid describes misfolded protein aggregates in which a highly ordered cross β-sheet pattern is adopted. While there exist functional amyloids, the majority of known amyloids are associated with diseases in multicellular organisms. One example is the association is that between Amyloid β (Aβ) and Alzheimer’s disease, a neurodegenerative disorder in humans. Several mechanisms of toxicity have been proposed, yet a lack of dynamic data prevents a full molecular explanation for the toxicity of Aβ and other amyloid systems. Mutational effects often increase the degree of polymorphism in observable structures, compounding the issues with a molecular level examination. In this thesis, Molecular Dynamic (MD) simulations of wild-type and mutant sequences of both Aβ and Prion proteins are performed to explore the structural dynamics of amyloids and amyloid-like systems. The data generated will provide physics-based explanations of the traits of amyloids on a molecular level which may guide further physical experimentation into the mechanism of amyloid toxicity and formation