Self-assembly Of Amyloid Aggregates Simulated With Molecular Dynamics

Amyloids are highly ordered cross-β sheet aggregates that are associated with many diseases such as Alzheimer‟s, type II diabetes and prion diseases. Recently a progress has been made in structure elucidation, environmental effects and thermodynamic properties of amyloid aggregates. However, detailed understanding of how mutation, packing polymorphism and small organic molecules influence amyloid structure and dynamics is still lacking. Atomistic modeling of these phenomena with molecular dynamics (MD) simulations holds a great promise to bridge this gap. This Thesis describes the results of MD simulations, which provide insight into the effects of mutation, packing polymorphism and molecular inhibitors on amyloid peptides aggregation. Chapter 1 discusses the structure of amyloid peptides, diseases associated with amyloid aggregation, mechanism of aggregation and strategies to treat amyloid diseases. Chapter 2 describes the basic principles of molecular dynamic simulation and methods of trajectory analysis used in the Thesis. Chapter 3 presents the results of the study of several all-atom molecular dynamics simulations with explicit solvent, starting from the crystalline fragments of two to ten monomers each. Three different hexapeptides and their analogs produced with single glycine replacement were investigated to study the structural stability, aggregation behavior and thermodynamics of the amyloid oligomers. Chapter 4 presents multiple molecular dynamics (MD) simulation of a pair polymorphic form of five short segments of amyloid peptide. Chapter 5 describes MD study of single-layer oligomers of the full-length insulin with a goal to identify the structural elements that are important for insulin amyloid stability, and to suggest single glycine mutants that may improve formulation. Chapter 6 presents the investigation of the mechanism of the interaction of polyphenols molecules with the protofibrils formed by an amyloidogenic hexapeptide fragment (VQIVYK) of Tau peptide by molecular dynamics iii simulations in explicit solvent. We analyzed the trajectories of the large (7×4) aggregate with and without the polyphenols. Our MD simulations for both the short and full length amyloids revealed adding strands enhances the internal stability of wildtype aggregates. The degree of structural similarity between the oligomers in simulation and the fibril models constructed based on experimental data may explain why adding oligomers shortens the experimentally observed nucleation lag phase of amyloid aggregation. The MM-PBSA free energy calculation revealed nonpolar components of the free energy is more favorable while electrostatic solvation is unfavorable for the sheet to sheet interaction. This explains the acceleration of aggregation by adding nonpolar co-solvents (methanol, trifluoroethanol, and hexafluoroisopropanol). Free energy decomposition shows residues situated at the interface were found to make favorable contribution to the peptide -peptide association. The results from the simulations might provide both the valuable insight for amyloid aggregation as well as assist in inhibitor design efforts. First, the simulation of the single glycine mutants at the steric zipper of the short segments of various pathological peptides indicates the intersheet steric zipper is important for amyloid stability. Mutation of the side chains at the dry steric zipper disrupts the sheet to sheet packing, making the aggregation unstable. Thus, designing new peptidomimetic inhibitors able to prevent the fibril formation based on the steric zipper motif of the oligomers, similar to the ones examined in this study may become a viable therapeutic strategy. The various steric zipper microcrystal structures of short amyloid segments could be used as a template to design aggregation inhibitor that can block growth of the aggregates. Modification of the steric zipper structure (structure based design) with a single amino acid changes, shuffling the sequences, N- methylation of peptide amide bonds to suppress hydrogen iv bonding ability of NH groups or replacement with D amino acid sequence that interact with the parent steric zipper could be used in computational search for the new inhibitors. Second, the polyphenols were found to interact with performed oligomer through hydrogen bonding and induce conformational change creating an altered aggregate. The conformational change disrupts the intermolecular amyloid contact remodeling the amyloid aggregate. The recently reported microcrystal structure of short segments of amyloid peptides with small organic molecules could serve as a pharamcophore for virtual screening of aggregation inhibitor using combined docking and MD simulation with possible enhancement of lead enrichment. Finally, our MD simulation of short segments of amyloids with steric zipper polymorphism showed the stability depends on both sequence and packing arrangements. The hydrophilic polar GNNQQNY and NNQNTF with interface containing large polar and/or aromatic side chains (Q/N) are more stable than steric zipper interfaces made of small or hydrophobic residues (SSTNVG, VQIVYK, and MVGGVV). The larger sheet to sheet interface of the dry steric zipper through polar Q/N rich side chains was found to holds the sheets together better than non Q/N rich short amyloid segments. The packing polymorphism could influence the structure based design of aggregation inhibitor and a combination of different aggregation inhibitors might be required to bind to various morphologic forms of the amyloid peptides

Amyloid Fibril Nucleation In Reverse Micelles

The 40-residue amyloid beta protein (Abeta) is the unstructured cleavage product of a common membrane protein that is produced in large quantities, but normally cleared from the brain before it exerts any apparent toxicity. Under some conditions, however, it undergoes a conformational change and aggregates into fibrils. These fibrils then coalesce into amyloid plaques, which are the pathognomonic brain lesions of Alzheimer‘s disease. The plaques are centers of active oxidative stress and neuronal death, so the conditions under which fibrils form is of high interest. When Abeta is encapsulated in a reverse micelle, its infrared spectrum indicates that it spontaneously adopts a fibril-like structure, which is remarkable because only one Abeta strand is present in each reverse micelle. That observation suggests that some aspect of the reverse micelle environment such as crowding, dehydration, proximity to a membrane, or high ionic strength may induce Abeta to nucleate amyloid fibril formation. Therefore, an understanding of the factors that induce Abeta to adopt fibril-like structure in reverse micelles may reveal what causes amyloid fibrils to form in Alzheimer\u27s disease. Molecular dynamics simulations of Abeta in reverse micelles have been performed to identify and understand these factors. Results indicate that Abeta side chains penetrate the reverse micelle surface, anchoring the peptide in the membrane. Other interactions between peptide and membrane stabilize intrachain hydrogen bond formation and secondary structure. These interactions may be important factors in the formation of amyloid fibrils and the pathogenesis of Alzheimer‘s disease

Interaction studies between biocompatible polymers and amyloid-B peptides

A informação relativa aos orientadores da tese foi retirada da página do SIFEUPTese de doutoramento. Engenharia Química e Biológica. Faculdade de Engenharia. Universidade do Porto. 200

Targeting protein kinases to manage or prevent Alzheimer’s disease

Due to the pressing need for new disease-modifying drugs for Alzheimer’s disease (AD), new treatment strategies and alternative drug targets are currently being heavily researched. One such strategy is to modulate protein kinases such as cyclin-dependent kinase 1 (CDK1), cyclin-dependent kinase 5 (CDK5), glycogen synthase kinase-3 (GSK-3α and GSK-3β), and the protein kinase RNA-like endoplasmic reticulum kinase (PERK). AD intervention by reduction of amyloid beta (Aβ) levels is also possible through development of protein kinase C-epsilon (PKC-ϵ) activators to recover α-secretase levels and decrease toxic Aβ levels, thereby restoring synaptogenesis and cognitive function. In this way, we aim to develop new AD drugs by targeting kinases that participate in AD pathophysiology. In our studies, comparative modeling was performed to construct 3D models for kinases whose crystal structures have not yet been identified. The information from structurally similar proteins was used to define the amino acid residues in the ATP binding site as well as other important sites and motifs. We searched for the comstructural motifs and domains of GSK-3β, CDK5 and PERK. Further, we identified the conserved water molecules in GSK-3β, CDK5 and PERK through calculation of the degree of water conservation. We investigated the protein-ligand interaction profiles of CDK1, CDK5, GSK-3α, GSK-3β and PERK based on molecular dynamics (MD) simulations, which provided a time-dependent demonstration of the interactions and contacts for each ligand. In addition, we explored the protein-protein interactions between CDK5 and p25. Small molecules which target this interaction may offer a prospective therapeutic benefit for AD. In order to identify new modulators for protein kinase targets in AD, we implemented three virtual screening protocols. The first protocol was a combined ligand- and protein structure-based approach to find new PERK inhibitors. In the second protocol, protein structure-based virtual screening was applied to find multiple-kinase inhibitors through parallel docking simulations into validated models of CDK1, CDK5 and GSK-3 kinases. In the third protocol, we searched for potential activators of PKC-ϵ based on the structure of its C1B domain

Statistical Mechanics for Network Structure and Evolution

In this thesis, we address problems in complex networks using the methods of statistical mechanics and information theory. We particularly focus on the thermodynamic characterisation of networks and entropic analysis on statistics and dynamics of network evolution. After a brief introduction of background and motivation behind the thesis in Chapter 1, we provide a review of relevant literature in Chapter 2, and elaborate the main methods from Chapter 3 to Chapter 6. In Chapter 3, we explore the normalised Laplacian matrix as the Hamiltonian operator of the network which governs the particle occupations corresponding to Maxwell-Boltzmann, Bose-Einstein and Fermi-Dirac statistics. The relevant partition functions derive the thermodynamic quantities in revealing network structural characterisations. Chapter 4 further decomposes the global network entropy in three statistics on edge-connection components. This decompensation reflects the detailed distribution of entropy across the edges of a network, and is particularly useful if the analysis of non-homogeneous networks with a strong community and hub structure is being attempted. Furthermore, Chapter 5 and Chapter 6 provide the theoretical approaches to analyse the dynamic network evolution and the application of the real-world networks. In Chapter 5, we investigate both undirected and directed network evolution using the Euler-Lagrange equation. This variational principle is based on the von Neumann entropy for time-varying network structure. The presented model not only provides an accurate simulation of the degree statistics in network evolution, but also captures the topological variations taking place when the structure of a network changes violently. Chapter 6 studies the fMRI regional brain interaction networks using directed graphs. We further develop a novel method for characterising networks using Bose-Einstein entropy and the Jensen-Shannon divergence. It offers a high discrimination among patients with suspected Alzheimer's disease. Finally, Chapter 7 concludes the thesis and discusses the limitations of our methodologies, which also supplies the potential research in the future

NMR Investigations of the Self-Organization and Dynamics of Mutated Amyloid Protein Fibrils

This work investigates the influence of mutations at selected positions on the structure formation of the Alzheimer’s disease peptide amyloid β. Amyloid β is a member of the class of intrinsically disordered proteins that can aggregate into fibrils, which are characterized by a highly stable secondary structure, called cross-β structure. A central contact during fibrillation is the hydrophobic F19-L34 contact, which is located within the core of the cross-β structure. Modifications of this contact are known to influence the local molecular structure whereas the fibril morphology and the cross-β structure remain stable. In contrast, toxicity of amyloid β was completely lost for all previously investigated mutants of F19 and L34. This work characterizes the properties of this contact and answers the question what the minimally tolerated modifications are. To characterize the structure, structure formation process and biological activity of the Aβ variants a set of experiments was carried out. The local structure and dynamics were investigated using NMR experiments focusing on 13C-chemical shift changes and 1H-13C dipolar couplings, respectively. The fibril morphology and cross- β structure was verified by electron microscopy, circular dichroism spectroscopy and X-ray diffraction. Toxicity and biological activity was investigated using complementary cell culture experiments. The work was divided in three parts. First, L34 was substituted with three highly similar amino acids: the isomer isoleucine, valine that is one methylene group shorter but also a branched chain amino acid and the stereoisomer D-leucine. The L34 position proved to be important for the initiation of the structure formation, oligomer stability, fibril growth and the biological activity of amyloid β. These characteristics and properties were highly sensitive also to minor modifications but the different mutants showed no specific but qualitatively similar effects. The second part complemented previous mutation studies of the F19 position. Four new mutants were designed testing mild modification of the F19-L34 contact: phenylglycine and the homophenylalanine (S)-2-amino-4-phenyl-butyric acid change the length of the side chain, cyclohexyl-alanine eliminates the π-aromaticity of the ring system and increases the 3D steric demand, and (1-naphtyl)-alanine increases the 2D steric demand while maintaining the aromaticity. Mutations at the F19 position caused qualitatively similar effects as L34 modifications but proved to have quantitatively greater impact. Furthermore, they showed some specificity as steric constraints caused larger changes than modifications of the ring system. The third part investigates the influence of β-methylamino-L-alanine (BMAA) substitutions at positions F19, S8, and S26. The serine to BMAA substitutions were included because of their potential medical relevance. A F19BMAA substitution caused similar effects like other modifications at this position. Replacement of serine lead to a structural reorientation of the Aβ N-terminus and turn region. Furthermore, the pathways of the cell response changed from mitochondrial activity and plasma membrane integrity to apoptosis and neuronal stress reaction. Summarizing, it could be shown that, although the formation and structure of amyloid β fibrils is robust against different modifications the fibrillation kinetics, local structure and especially biological activity is highly sensitive and to some extend specific to even minor modifications

Theoretical-experimental study on protein-ligand interactions based on thermodynamics methods, molecular docking and perturbation models

The current doctoral thesis focuses on understanding the thermodynamic events of protein-ligand interactions which have been of paramount importance from traditional Medicinal Chemistry to Nanobiotechnology. Particular attention has been made on the application of state-of-the-art methodologies to address thermodynamic studies of the protein-ligand interactions by integrating structure-based molecular docking techniques, classical fractal approaches to solve protein-ligand complementarity problems, perturbation models to study allosteric signal propagation, predictive nano-quantitative structure-toxicity relationship models coupled with powerful experimental validation techniques. The contributions provided by this work could open an unlimited horizon to the fields of Drug-Discovery, Materials Sciences, Molecular Diagnosis, and Environmental Health Sciences

Nonlinear analysis of EEG signals at different mental states

BACKGROUND: The EEG (Electroencephalogram) is a representative signal containing information about the condition of the brain. The shape of the wave may contain useful information about the state of the brain. However, the human observer can not directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. This work discusses the effect on the EEG signal due to music and reflexological stimulation. METHODS: In this work, nonlinear parameters like Correlation Dimension (CD), Largest Lyapunov Exponent (LLE), Hurst Exponent (H) and Approximate Entropy (ApEn) are evaluated from the EEG signals under different mental states. RESULTS: The results obtained show that EEG to become less complex relative to the normal state with a confidence level of more than 85% due to stimulation. CONCLUSIONS: It is found that the measures are significantly lower when the subjects are under sound or reflexologic stimulation as compared to the normal state. The dimension increases with the degree of the cognitive activity. This suggests that when the subjects are under sound or reflexologic stimuli, the number of parallel functional processes active in the brain is less and the brain goes to a more relaxed stat