Birgit Strodel

Amyloid β Protein and Alzheimer’s Disease: When Computer Simulations Complement Experimental Studies

Simulations Complement Experimental Studies Jessica Nasica-Labouze,† Phuong H. Nguyen,† Fabio Sterpone,† Olivia Berthoumieu,‡ Nicolae-Viorel Buchete, Sebastien Cote, Alfonso De Simone, Andrew J. Doig, Peter Faller,‡ Angel Garcia, Alessandro Laio, Mai Suan Li, Simone Melchionna, Normand Mousseau, Yuguang Mu, Anant Paravastu, Samuela Pasquali,† David J. Rosenman, Birgit Strodel, Bogdan Tarus,† John H. Viles, Tong Zhang,†,▲ Chunyu Wang, and Philippe Derreumaux*,†,□ †Laboratoire de Biochimie Theorique, Institut de Biologie Physico-Chimique (IBPC), UPR9080 CNRS, Universite Paris Diderot, Sorbonne Paris Cite, 13 rue Pierre et Marie Curie, 75005 Paris, France ‡LCC (Laboratoire de Chimie de Coordination), CNRS, Universite de Toulouse, Universite Paul Sabatier (UPS), Institut National Polytechnique de Toulouse (INPT), 205 route de Narbonne, BP 44099, Toulouse F-31077 Cedex 4, France School of Physics & Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland Deṕartement de Physique and Groupe de recherche sur les proteines membranaires (GEPROM), Universite de Montreal, C.P. 6128, succursale Centre-ville, Montreal, Quebec H3C 3T5, Canada Department of Life Sciences, Imperial College London, London SW7 2AZ, United Kingdom Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester M1 7DN, United Kingdom Department of Physics, Applied Physics, & Astronomy, and Department of Biology, Rensselaer Polytechnic Institute, Troy, New York 12180, United States The International School for Advanced Studies (SISSA), Via Bonomea 265, 34136 Trieste, Italy Institute of Physics, Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland Institute for Computational Science and Technology, SBI Building, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, Ho Chi Minh City, Vietnam Instituto Processi Chimico-Fisici, CNR-IPCF, Consiglio Nazionale delle Ricerche, 00185 Roma, Italy School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, 637551 Singapore Department of Chemical and Biomedical Engineering, Florida A&M University-Florida State University (FAMU-FSU) College of Engineering, 2525 Pottsdamer Street, Tallahassee, Florida 32310, United States National High Magnetic Field Laboratory, 1800 East Paul Dirac Drive, Tallahassee, Florida 32310, United States Institute of Complex Systems: Structural Biochemistry (ICS-6), Forschungszentrum Julich GmbH, 52425 Julich, Germany School of Biological and Chemical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom Institut Universitaire de France, 75005 Paris, France

Transmembrane Structures for Alzheimer’s Aβ1−42 Oligomers

We model oligomers of the Alzheimers amyloid β-peptide Aβ(1-42) in an implicit membrane to obtain insight into the mechanism of amyloid toxicity. It has been suggested that Aβ oligomers are the toxic species, causing membrane disruption in neuronal cells due to pore formation. We use basin-hopping global optimization to identify the most stable structures for the Aβ(1-42) peptide monomer and small oligomers up to the octamer inserted into a lipid bilayer. To improve the efficacy of the basin-hopping approach, we introduce a basin-hopping parallel tempering scheme and an oligomer generation procedure. The most stable membrane-spanning structure for the monomer is identified as a β-sheet, which exhibits the typical strand-turn-strand motif observed in NMR experiments. We find ordered β-sheets for the dimer to the hexamer, whereas for the octamer, we observe that the ordered structures separate into distinct tetrameric units that are rotated or shifted with respect to each other. This effect leads to an increase in favorable peptide-peptide interactions, thereby stabilizing the membrane-inserted octamer. On the basis of these results, we suggest that Aβ pores may consist of tetrameric and hexameric β-sheet subunits. These Aβ pore models are consistent with the results of biophysical and biochemical experiments.

Structures of the amyloid β-peptides Aβ1-40 and Aβ1-42 as influenced by pH and a D-peptide.

In this simulation study, we present a comparison of the secondary structure of the two major alloforms of the Alzheimers peptide (Aβ(1-40) and Aβ(1-42)) on the basis of molecular dynamics (MD) simulations on thea microsecond time scale using the two GROMOS96 force fields ffG43a2 and ffG53a6. We observe peptide and force-field related differences in the sampled conformations of Aβ(1-40) and Aβ(1-42), which we characterize in terms of NMR chemical shifts calculated from the MD trajectories and validate against the corresponding experimental NMR results. From this analysis, we can conclude that ffG53a6 is better able to model the structural propensities of Aβ(1-40) and Aβ(1-42) than ffG43a2. Furthermore, we provide a description of the influences of pH and binding of D3, a 12-residue D-enantiomeric peptide with demonstrated antiamyloid effects, on the structure of Aβ(1-42). We demonstrate that, under slightly acidic conditions, protonation of the three histidine residues in Aβ(1-42) promotes the formation of β-sheets via a reduction in electrostatic repulsion between the two terminal regions. Our studies further reveal that the binding between D3 and Aβ(1-42) is driven by electrostatic interactions between negatively charged Aβ(1-42) residues and the five positively charged arginine residues of D3. The binding of D3 was found to induce large conformational changes in the amyloid peptide, with a reduction in β-sheet units being the most significant effect recorded, possibly explaining the observed amyloid-inhibiting properties of the D-peptide.

An account of amyloid oligomers: facts and figures obtained from experiments and simulations

The deposition of amyloid in brain tissue in the context of neurodegenerative diseases involves the formation of intermediate species—termed oligomers—of lower molecular mass and with structures that deviate from those of mature amyloid fibrils. Because these oligomers are thought to be primarily responsible for the subsequent disease pathogenesis, the elucidation of their structure is of enormous interest. Nevertheless, because of the high aggregation propensity and the polydispersity of oligomeric species formed by the proteins or peptides in question, the preparation of appropriate samples for high‐resolution structural methods has proven to be rather difficult. This is why theoretical approaches have been of particular importance in gaining insights into possible oligomeric structures for some time. Only recently has it been possible to achieve some progress with regard to the experimentally based structural characterization of defined oligomeric species. Here we discuss how theory and experiment are used to determine oligomer structures and what can be done to improve the integration of the two disciplines.

How the amyloid-β peptide and membranes affect each other : An extensive simulation study

The etiology of Alzheimers disease is thought to be linked to interactions between amyloid-β (Aβ) and neural cell membranes, causing membrane disruption and increased ion conductance. The effects of Aβ on lipid behavior have been characterized experimentally, but structural and causal details are lacking. We used atomistic molecular dynamics simulations totaling over 6 μs in simulation time to investigate the behavior of Aβ(42) in zwitterionic and anionic lipid bilayers. We simulated transmembrane β-sheets (monomer and tetramer) resulting from a global optimization study and a helical structure obtained from an NMR study. In all simulations Aβ(42) remained embedded in the bilayer. It was found that the surface charge and the lipid tail type are determinants for transmembrane stability of Aβ(42) with zwitterionic surfaces and unsaturated lipids promoting stability. From the considered structures, the β-sheet tetramer is most stable as a result of interpeptide interactions. We performed an in-depth analysis of the translocation of water in the Aβ(42)-bilayer systems. We observed that this process is generally fast (within a few nanoseconds) yet generally slower than in the peptide-free bilayers. It is mainly governed by the lipid type, simulation temperature and Aβ(42) conformation. The rate limiting step is the permeation through the hydrophobic core, where interactions between Aβ(42) and permeating H(2)O molecules slow the translocation process. The β-sheet tetramer allows more water molecules to pass through the bilayer compared to monomeric Aβ, allowing us to conclude that the experimentally observed permeabilization of membranes must be due to membrane-bound Aβ oligomers, and not monomers.

Advances in the Simulation of Protein Aggregation at the Atomistic Scale

Protein aggregation into highly structured amyloid fibrils is associated with various diseases including Alzheimers disease, Parkinsons disease, and type II diabetes. Amyloids can also have normal biological functions and, in the future, could be used as the basis for novel nanoscale materials. However, a full understanding of the physicochemical forces that drive protein aggregation is still lacking. Such understanding is crucial for the development of drugs that can effectively inhibit aberrant amyloid aggregation and for the directed design of functional amyloids. Atomistic simulations can help understand protein aggregation. In particular, atomistic simulations can be used to study the initial formation of toxic oligomers which are hard to characterize experimentally and to understand the difference in aggregation behavior between different amyloidogenic peptides. Here, we review the latest atomistic simulations of protein aggregation, concentrating on amyloidogenic protein fragments, and provide an outlook for the future in this field.

A Kinetic Approach to the Sequence–Aggregation Relationship in Disease-Related Protein Assembly

It is generally accepted that oligomers of aggregating proteins play an important role in the onset of neurodegenerative diseases. While in silico aggregation studies of full length amyloidogenic proteins are computationally expensive, the assembly of short protein fragments derived from these proteins with similar aggregating properties has been extensively studied. In the present work, molecular dynamics simulations are performed to follow peptide aggregation on the microsecond time scale. By defining aggregation states, we identify transition networks, disconnectivity graphs, and first passage time distributions to describe the kinetics of the assembly process. This approach unravels differences in the aggregation into hexamers of two peptides with different primary structures. The first is GNNQQNY, a hydrophilic fragment from the prion protein Sup35, and the second is KLVFFAE, a fragment from amyloid-β protein, with a hydrophobic core delimited by two charged amino acids. The assembly of GNNQQNY suggests a mechanism of monomer addition, with a bias toward parallel peptide pairs and a gradual increase in the amount of β-strand content. For KLVFFAE, a mechanism involving dimers rather than monomers is revealed, involving a generally higher β-strand content and a transition toward a larger number of antiparallel peptide pairs during the rearrangement of the hexamer. The differences observed for the aggregation of the two peptides suggests the existence of a sequence-aggregation relationship.

Modelling proteins: conformational sampling and reconstruction of folding kinetics.

In the last decades biomolecular simulation has made tremendous inroads to help elucidate biomolecular processes in-silico. Despite enormous advances in molecular dynamics techniques and the available computational power, many problems involve long time scales and large-scale molecular rearrangements that are still difficult to sample adequately. In this review we therefore summarise recent efforts to fundamentally improve this situation by decoupling the sampling of the energy landscape from the description of the kinetics of the process. Recent years have seen the emergence of many advanced sampling techniques, which permit efficient characterisation of the relevant family of molecular conformations by dispensing with the details of the short-term kinetics of the process. Because these methods generate thermodynamic information at best, they must be complemented by techniques to reconstruct the kinetics of the process using the ensemble of relevant conformations. Here we review recent advances for both types of methods and discuss their perspectives to permit efficient and accurate modelling of large-scale conformational changes in biomolecules. This article is part of a Special Issue entitled: Protein Dynamics: Experimental and Computational Approaches.

Comparison of force fields for Alzheimer's A β42: A case study for intrinsically disordered proteins

Intrinsically disordered proteins are essential for biological processes such as cell signalling, but are also associated to devastating diseases including Alzheimers disease, Parkinsons disease or type II diabetes. Because of their lack of a stable three‐dimensional structure, molecular dynamics simulations are often used to obtain atomistic details that cannot be observed experimentally. The applicability of molecular dynamics simulations depends on the accuracy of the force field chosen to represent the underlying free energy surface of the system. Here, we use replica exchange molecular dynamics simulations to test five modern force fields, OPLS, AMBER99SB, AMBER99SB*ILDN, AMBER99SBILDN‐NMR and CHARMM22*, in their ability to model Aβ42, an intrinsically disordered peptide associated with Alzheimers disease, and compare our results to nuclear magnetic resonance (NMR) experimental data. We observe that all force fields except AMBER99SBILDN‐NMR successfully reproduce local NMR observables, with CHARMM22* being slightly better than the other force fields.

Characterization of Mn(II) ion binding to the amyloid-β peptide in Alzheimers disease

Growing evidence links neurodegenerative diseases to metal exposure. Aberrant metal ion concentrations have been noted in Alzheimers disease (AD) brains, yet the role of metals in AD pathogenesis remains unresolved. A major factor in AD pathogenesis is considered to be aggregation of and amyloid formation by amyloid-β (Aβ) peptides. Previous studies have shown that Aβ displays specific binding to Cu(II) and Zn(II) ions, and such binding has been shown to modulate Aβ aggregation. Here, we use nuclear magnetic resonance (NMR) spectroscopy to show that Mn(II) ions also bind to the N-terminal part of the Aβ(1-40) peptide, with a weak binding affinity in the milli- to micromolar range. Circular dichroism (CD) spectroscopy, solid state atomic force microscopy (AFM), fluorescence spectroscopy, and molecular modeling suggest that the weak binding of Mn(II) to Aβ may not have a large effect on the peptides aggregation into amyloid fibrils. However, identification of an additional metal ion displaying Aβ binding reveals more complex AD metal chemistry than has been previously considered in the literature.