Contrasting disease and nondisease protein aggregation by molecular simulation

Dynamics of proteins aggregation. II. Dynamic scaling in confined media

In this paper, the second in a series devoted to molecular modeling of protein aggregation, a mesoscale model of proteins together with extensive discontinuous molecular dynamics simulation is used to study the phenomenon in a confined medium. The medium, as a model of a crowded cellular environment, is represented by a spherical cavity, as well as cylindrical tubes with two aspect ratios. The aggregation process leads to the formation of β sheets and eventually fibrils, whose deposition on biological tissues is believed to be a major factor contributing to many neuro-degenerative diseases, such as Alzheimer's, Parkinson's, and amyotrophic lateral sclerosis diseases. Several important properties of the aggregation process, including dynamic evolution of the total number of the aggregates, the mean aggregate size, and the number of peptides that contribute to the formation of the β sheets, have been computed. We show, similar to the unconfined media studied in Paper I [S. Zheng et al., J. Chem. Phys. 145, 134306 (2016)], that the computed properties follow dynamic scaling, characterized by power laws. The existence of such dynamic scaling in unconfined media was recently confirmed by experiments. The exponents that characterize the power-law dependence on time of the properties of the aggregation process in spherical cavities are shown to agree with those in unbounded fluids at the same protein density, while the exponents for aggregation in the cylindrical tubes exhibit sensitivity to the geometry of the system. The effects of the number of amino acids in the protein, as well as the size of the confined media, have also been studied. Similarities and differences between aggregation in confined and unconfined media are described, including the possibility of no fibril formation, if confinement is severe.

Knowledge-driven computational modeling in Alzheimer's disease research: Current state and future trends

Neurodegenerative diseases such as Alzheimer's disease (AD) follow a slowly progressing dysfunctional trajectory, with a large presymptomatic component and many comorbidities. Using preclinical models and large-scale omics studies ranging from genetics to imaging, a large number of processes that might be involved in AD pathology at different stages and levels have been identified. The sheer number of putative hypotheses makes it almost impossible to estimate their contribution to the clinical outcome and to develop a comprehensive view on the pathological processes driving the clinical phenotype. Traditionally, bioinformatics approaches have provided correlations and associations between processes and phenotypes. Focusing on causality, a new breed of advanced and more quantitative modeling approaches that use formalized domain expertise offer new opportunities to integrate these different modalities and outline possible paths toward new therapeutic interventions. This article reviews three different computational approaches and their possible complementarities. Process algebras, implemented using declarative programming languages such as Maude, facilitate simulation and analysis of complicated biological processes on a comprehensive but coarse-grained level. A model-driven Integration of Data and Knowledge, based on the OpenBEL platform and using reverse causative reasoning and network jump analysis, can generate mechanistic knowledge and a new, mechanism-based taxonomy of disease. Finally, Quantitative Systems Pharmacology is based on formalized implementation of domain expertise in a more fine-grained, mechanism-driven, quantitative, and predictive humanized computer model. We propose a strategy to combine the strengths of these individual approaches for developing powerful modeling methodologies that can provide actionable knowledge for rational development of preventive and therapeutic interventions. Development of these computational approaches is likely to be required for further progress in understanding and treating AD.

Dynamics of proteins aggregation. I. Universal scaling in unbounded media

It is well understood that in some cases proteins do not fold correctly and, depending on their environment, even properly-folded proteins change their conformation spontaneously, taking on a misfolded state that leads to protein aggregation and formation of large aggregates. An important factor that contributes to the aggregation is the interactions between the misfolded proteins. Depending on the aggregation environment, the aggregates may take on various shapes forming larger structures, such as protein plaques that are often toxic. Their deposition in tissues is a major contributing factor to many neuro-degenerative diseases, such as Alzheimer's, Parkinson's, amyotrophic lateral sclerosis, and prion. This paper represents the first part in a series devoted to molecular simulation of protein aggregation. We use the PRIME, a meso-scale model of proteins, together with extensive discontinuous molecular dynamics simulation to study the aggregation process in an unbounded fluid system, as the first step toward MD simulation of the same phenomenon in crowded cellular environments. Various properties of the aggregates have been computed, including dynamic evolution of aggregate-size distribution, mean aggregate size, number of peptides that contribute to the formation of β sheets, number of various types of hydrogen bonds formed in the system, radius of gyration of the aggregates, and the aggregates' diffusivity. We show that many of such quantities follow dynamic scaling, similar to those for aggregation of colloidal clusters. In particular, at long times the mean aggregate size S(t) grows with time as, S(t) ∼ t^z, where z is the dynamic exponent. To our knowledge, this is the first time that the qualitative similarity between aggregation of proteins and colloidal aggregates has been pointed out.

Mechanism of Nucleation and Growth of Aβ40 Fibrils from All-Atom and Coarse-Grained Simulations

In this work, we characterize the nucleation and elongation mechanisms of the "diseased" polymorph of the amyloid-β 40 (Aβ40) fibril using an off-lattice coarse-grained (CG) protein model. After determining the nucleation size and subsequent stable protofibrillar structure from the CG model, validated with all-atom simulations, we consider the "lock and dock" and "activated monomer" fibril elongation mechanisms for the protofibril by statistical additions of a monomer drawn from four different ensembles of the free Aβ40 peptide to grow the fibril. Our CG model shows that the dominant mechanism for fibril elongation is the lock and dock mechanism across all monomer ensembles, even when the monomer is in the activated form. Although our CG model finds no thermodynamic difference between the two fibril elongation mechanisms, the activated monomer is found to be kinetically faster by a factor of 2 for the "locking" step compared with all other structured or unstructured monomer ensembles.

Loss of RAD-23 Protects Against Models of Motor Neuron Disease by Enhancing Mutant Protein Clearance

Misfolded proteins accumulate and aggregate in neurodegenerative disease. The existence of these deposits reflects a derangement in the protein homeostasis machinery. Using a candidate gene screen, we report that loss of RAD-23 protects against the toxicity of proteins known to aggregate in amyotrophic lateral sclerosis. Loss of RAD-23 suppresses the locomotor deficit of Caenorhabditis elegans engineered to express mutTDP-43 or mutSOD1 and also protects against aging and proteotoxic insults. Knockdown of RAD-23 is further neuroprotective against the toxicity of SOD1 and TDP-43 expression in mammalian neurons. Biochemical investigation indicates that RAD-23 modifies mutTDP-43 and mutSOD1 abundance, solubility, and turnover in association with altering the ubiquitination status of these substrates. In human amyotrophic lateral sclerosis spinal cord, we find that RAD-23 abundance is increased and RAD-23 is mislocalized within motor neurons. We propose a novel pathophysiological function for RAD-23 in the stabilization of mutated proteins that cause neurodegeneration.

SIGNIFICANCE STATEMENT

In this work, we identify RAD-23, a component of the protein homeostasis network and nucleotide excision repair pathway, as a modifier of the toxicity of two disease-causing, misfolding-prone proteins, SOD1 and TDP-43. Reducing the abundance of RAD-23 accelerates the degradation of mutant SOD1 and TDP-43 and reduces the cellular content of the toxic species. The existence of endogenous proteins that act as "anti-chaperones" uncovers new and general targets for therapeutic intervention.

Interplay between the hydrophobic effect and dipole interactions in peptide aggregation at interfaces

Amphipathic octapeptide aggregation at hydrophobic–hydrophilic interfaces is largely driven by backbone dipole interactions in peptide aggregation at interfaces.

Disordered structural ensembles of vasopressin and oxytocin and their mutants

Vasopressin and oxytocin are intrinsically disordered cyclic nonapeptides belonging to a family of neurohypophysial hormones. Although unique in their functions, these peptides differ only by two residues and both feature a tocin ring formed by the disulfide bridge between first and sixth cysteine residues. This sequence and structural similarity are experimentally linked to oxytocin agonism at vasopressin receptors and vasopressin antagonism at oxytocin receptors. Yet single- or double-residue mutations in both peptides have been shown to have drastic impacts on their activities at either receptor, and possibly the ability to bind to their neurophysin carrier protein. In this study we perform molecular dynamics simulations of the unbound native and mutant sequences of the oxytocin and vasopressin hormones to characterize their structural ensembles. We classify the subpopulations of these structural ensembles on the basis of the distributions of radius of gyration and secondary structure and hydrogen-bonding features of the canonical tocin ring and disordered tail region. We then relate the structural changes observed in the unbound form of the different hormone sequences to experimental information about peptide receptor binding, and more indirectly, carrier protein binding affinity, receptor activity, and protease degradation. This study supports the hypothesis that the structural characteristics of the unbound form of an IDP can be used to predict structural or functional preferences of its functional bound form.

Neurodegenerative disorders: dysregulation of a carefully maintained balance?

The aggregation of misfolded proteins has long been regarded as a pathological event in neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease and Huntington's disease. However, the exact molecular mechanisms that govern protein metabolism that may lead to toxicity remain largely unclear. Originally targeted as the causative agent, it has since become evident that aggregation formation may not be necessary for disease progression and studies show that they may even serve functional and protective roles. Although the focus has since shifted to the toxicity of intermediate protein species preceding aggregation formation, many questions remain: Is the blame for the neural destruction to be put on one event alone, or rather on a state of cellular disequilibrium resulting from multiple events? If the cause is multifactorial, then what triggers the toxic cascade and how can this be targeted therapeutically? In order to understand the origin of toxicity, the exact underlying mechanism and impact of each contributing process must be assessed. Therefore, the structural properties, mechanism of formation, cytotoxic and/or protective effects, as well as the clinical impact of protein intermediates and aggregates will be reviewed here with the goal to establish a neurodegenerative disease model aimed at improving current therapeutics, which may ultimately contribute towards improved treatment modalities.

On the subject of rigor in the study of amyloid β-protein assembly

According to Thomas Kuhn, the success of 'normal science,' the science we all practice on a daily basis, depends on the adherence to, and practice of, a paradigm accepted by the scientific community. When great scientific upheavals occur, they involve the rejection of the current paradigm in favor of a new paradigm that better integrates the facts available and better predicts the behavior of a particular scientific system. In the field of Alzheimer's disease, a recent example of such a paradigm shift has been the apparent rejection of the 'amyloid cascade hypothesis,' promulgated by Hardy and Higgins in 1992 to explain the etiology of Alzheimer's disease, in favor of what has been referred to as the 'oligomer cascade hypothesis'. This paradigm shift has been breathtaking in its rapidity, its pervasiveness in the Alzheimer's disease field, and its adoption in an increasing number of other fields, including those of Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, and the prionoses. However, these facts do not mean, a priori, that the experiments extant, and any re-interpretation of them, should be accepted by rote as support for the new paradigm. In the discussion that follows, I consider the foundational studies leading to the oligomer cascade hypothesis and evaluate the current state of the paradigm. I argue here that, more often than not, insufficient rigor has been applied in studies upon which this new paradigm has been based. Confusion, rather than clarity, has resulted. If the field is to make progress forward using as its paradigmatic basis amyloid β-protein oligomerization, then an epistemological re-evaluation of the amyloid β-protein oligomer system is required.

Computational assembly of polymorphic amyloid fibrils reveals stable aggregates

Amyloid proteins aggregate into polymorphic fibrils that damage tissues of the brain, nerves, and heart. Experimental and computational studies have examined the structural basis and the nucleation of short fibrils, but the ability to predict and precisely quantify the stability of larger aggregates has remained elusive. We established a complete classification of fibril shapes and developed a tool called CreateFibril to build such complex, polymorphic, modular structures automatically. We applied stability landscapes, a technique we developed to reveal reliable fibril structural parameters, to assess fibril stability. CreateFibril constructed HET-s, Aβ, and amylin fibrils up to 17 nm in length, and utilized a novel dipolar solvent model that captured the effect of dipole-dipole interactions between water and very large molecular systems to assess their aqueous stability. Our results validate experimental data for HET-s and Aβ, and suggest novel (to our knowledge) findings for amylin. In particular, we predicted the correct structural parameters (rotation angles, packing distances, hydrogen bond lengths, and helical pitches) for the one and three predominant HET-s protofilaments. We reveal and structurally characterize all known Aβ polymorphic fibrils, including structures recently classified as wrapped fibrils. Finally, we elucidate the predominant amylin fibrils and assert that native amylin is more stable than its amyloid form. CreateFibril and a database of all stable polymorphic fibril models we tested, along with their structural energy landscapes, are available at http://amyloid.cs.mcgill.ca.

Using a reduced dimensionality model to compute the thermodynamic properties of finite polypeptide aggregates

By implementing a simple reduced dimensionality model to describe the interactions in finite systems composed of two seven-amino-acid peptides, the thermodynamic properties of ordered and disordered aggregates were computed. Within this model, the hydrophobicity of each amino acid was varied, and the stability of the systems computed. Accurate averages in the canonical ensemble were obtained using various replica exchange Monte Carlo algorithms. Low and high temperature regions were encountered where the ordered and disordered aggregates were stabilized. It was observed that as the degree of hydrophobicity increased, the stability of the aggregates increased, with a significant energetic stabilization obtained for the ordered aggregates. Upon decreasing the concentration of the solution, the stability of the amorphous aggregates increased when compared to the ordered systems.

Properties of membrane-incorporated WALP peptides that are anchored on only one end

Peptides of the "WALP" family, acetyl-GWW(LA)(n)LWWA-[ethanol]amide, have proven to be opportune models for investigating lipid-peptide interactions. Because the average orientations and motional behavior of the N- and C-terminal Trp (W) residues differ, it is of interest to investigate how the positions of the tryptophans influence the properties of the membrane-incorporated peptides. To address this question, we synthesized acetyl-GGWW(LA)(n)-ethanolamide and acetyl-(AL)(n)WWG-ethanolamide, in which n = 4 or 8, which we designate as "N-anchored" and "C-anchored" peptides, respectively. Selected (2)H or (15)N labels were incorporated for solid-state nuclear magnetic resonance (NMR) spectroscopy. These peptides can be considered "half"-anchored WALP peptides, having only one pair of interfacial Trp residues near either the amino or the carboxyl terminus. The hydrophobic lengths of the (n = 8) peptides are similar to that of WALP23. These longer half-anchored WALP peptides incorporate into lipid bilayers as α-helices, as reflected in their circular dichroism spectra. Solid-state NMR experiments indicate that the longer peptide helices assume defined transmembrane orientations with small non-zero average tilt angles and moderate to high dynamic averaging in bilayer membranes of 1,2-dioleoylphosphatidylcholine, 1,2-dimyristoylphosphatidylcholine, and 1,2-dilauroylphosphatidylcholine. The intrinsically small apparent tilt angles suggest that interactions of aromatic residues with lipid headgroups may play an important role in determining the magnitude of the peptide tilt in the bilayer membrane. The shorter (n = 4) peptides, in stark contrast to the longer peptides, display NMR spectra that are characteristic of greatly reduced motional averaging, probably because of peptide aggregation in the bilayer environment, and CD spectra that are characteristic of β-structure.

Influence of the valine zipper region on the structure and aggregation of the basic leucine zipper (bZIP) domain of activating transcription factor 5 (ATF5)

Protein aggregation is a major problem for biopharmaceuticals. While the control of aggregation is critically important for the future of protein pharmaceuticals, mechanisms of aggregate assembly, particularly the role that structure plays, are still poorly understood. Increasing evidence indicates that partially folded intermediates critically influence the aggregation pathway. We have previously reported the use of the basic leucine zipper (bZIP) domain of activating transcription factor 5 (ATF5) as a partially folded model system to investigate protein aggregation. This domain contains three regions with differing structural propensity: a N-terminal polybasic region, a central helical leucine zipper region, and a C-terminal extended valine zipper region. Additionally, a centrally positioned cysteine residue readily forms an intermolecular disulfide bond that reduces aggregation. Computational analysis of ATF5 predicts that the valine zipper region facilitates self-association. Here we test this hypothesis using a truncated mutant lacking the C-terminal valine zipper region. We compare the structure and aggregation of this mutant to the wild-type (WT) form under both reducing and nonreducing conditions. Our data indicate that removal of this region results in a loss of α-helical structure in the leucine zipper and a change in the mechanism of self-association. The mutant form displays increased association at low temperature but improved resistance to thermally induced aggregation.

Coarse-grained simulations of protein aggregation

Protein aggregation is believed to be responsible for a number of human diseases and limits the yields of pharmaceutical proteins during production. Computer simulations can be used to develop novel experimentally testable hypotheses pertaining to aggregation. While all-atom simulations with explicit solvent are too computationally intensive to address the multitude of relevant time scales, coarse-grained models make it possible to observe the transition of monomers to an equilibrium containing aggregates. Here, we provide the reader with background information and a list of steps for setting up, performing, and analyzing computer simulations of aggregating coarse-grained (CG) proteins.

Molecular origin of Gerstmann-Sträussler-Scheinker syndrome: insight from computer simulation of an amyloidogenic prion peptide

Prion proteins become pathogenic through misfolding. Here, we characterize the folding of a peptide consisting of residues 109-122 of the Syrian hamster prion protein (the H1 peptide) and of a more amyloidogenic A117V point mutant that leads in humans to an inheritable form of the Gerstmann-Sträussler-Scheinker syndrome. Atomistic molecular dynamics simulations are performed for 2.5 μs. Both peptides lose their α-helical starting conformations and assume a β-hairpin that is structurally similar in both systems. In each simulation several unfolding/refolding events occur, leading to convergence of the thermodynamics of the conformational states to within 1 kJ/mol. The similar stability of the β-hairpin relative to the unfolded state is observed in the two peptides. However, substantial differences are found between the two unfolded states. A local minimum is found within the free energy unfolded basin of the A117V mutant populated by misfolded collapsed conformations of comparable stability to the β-hairpin state, consistent with increased amyloidogenicity. This population, in which V117 stabilizes a hydrophobic core, is absent in the wild-type peptide. These results are supported by simulations of oligomers showing a slightly higher stability of the associated structures and a lower barrier to association for the mutated peptide. Hence, a single point mutation carrying only two additional methyl groups is here shown to be responsible for rather dramatic differences of structuring within the unfolded (misfolded) state.

Free energies for coarse-grained proteins by integrating multibody statistical contact potentials with entropies from elastic network models

We propose a novel method of calculation of free energy for coarse grained models of proteins by combining our newly developed multibody potentials with entropies computed from elastic network models of proteins. Multi-body potentials have been of much interest recently because they take into account three dimensional interactions related to residue packing and capture the cooperativity of these interactions in protein structures. Combining four-body non-sequential, four-body sequential and pairwise short range potentials with optimized weights for each term, our coarse-grained potential improved recognition of native structure among misfolded decoys, outperforming all other contact potentials for CASP8 decoy sets and performance comparable to the fully atomic empirical DFIRE potentials. By combing statistical contact potentials with entropies from elastic network models of the same structures we can compute free energy changes and improve coarse-grained modeling of protein structure and dynamics. The consideration of protein flexibility and dynamics should improve protein structure prediction and refinement of computational models. This work is the first to combine coarse-grained multibody potentials with an entropic model that takes into account contributions of the entire structure, investigating native-like decoy selection.

Probing amyloid fibril growth by two-dimensional near-ultraviolet spectroscopy

Keeping track of the aggregation kinetics of amyloid fibrils is essential for understanding their formation mechanism and eventually developing treatments for misfolded protein-related diseases. A simulation study of a series of Aβ(9-40) amyloid fibrils with different size shows that novel two-dimensional near-ultraviolet (2DNUV) spectra contain characteristic signatures of interactions between peptides. Chiral 2DNUV signals show a larger degree of exciton delocalization compared to their nonchiral counterparts. Intensities of specific peaks provide a direct measure of the number of peptides in a fibril. These signals could be used to monitor the fibril growth kinetics, one peptide at a time.

Multibody coarse-grained potentials for native structure recognition and quality assessment of protein models

Multibody potentials have been of much interest recently because they take into account three dimensional interactions related to residue packing and capture the cooperativity of these interactions in protein structures. Our goal was to combine long range multibody potentials and short range potentials to improve recognition of native structure among misfolded decoys. We optimized the weights for four-body nonsequential, four-body sequential, and short range potentials to obtain optimal model ranking results for threading and have compared these data against results obtained with other potentials (26 different coarse-grained potentials from the Potentials 'R'Us web server have been used). Our optimized multibody potentials outperform all other contact potentials in the recognition of the native structure among decoys, both for models from homology template-based modeling and from template-free modeling in CASP8 decoy sets. We have compared the results obtained for this optimized coarse-grained potentials, where each residue is represented by a single point, with results obtained by using the DFIRE potential, which takes into account atomic level information of proteins. We found that for all proteins larger than 80 amino acids our optimized coarse-grained potentials yield results comparable to those obtained with the atomic DFIRE potential.

Two-dimensional near-ultraviolet spectroscopy of aromatic residues in amyloid fibrils: a first principles study

We report a first principles study of two dimensional electronic spectroscopy of aromatic side chain transitions in the 32-residue β-amyloid (Aβ(9-40)) fibrils in the near ultraviolet (250-300 nm). An efficient exciton Hamiltonian with electrostatic fluctuations (EHEF) algorithm is used to compute the electronic excitations in the presence of environmental fluctuations. The through-space inter- and intra-molecular interactions are calculated with high level quantum mechanics (QM) approaches, and interfaced with molecular mechanics (MM) simulations. Distinct two dimensional near ultraviolet (2DNUV) spectroscopic signatures are identified for different aromatic transitions, and the couplings between them. 2DNUV signals associated with the transition couplings are shown to be very sensitive to the change of residue-residue interactions induced by residue mutations. Our simulations suggest that 2DNUV spectra could provide a useful local probe for the structure and kinetics of fibrils.

Simulation of two-dimensional ultraviolet spectroscopy of amyloid fibrils

Revealing the structure and aggregation mechanism of amyloid fibrils is essential for the treatment of over 20 diseases related to protein misfolding. Coherent two-dimensional (2D) infrared spectroscopy is a novel tool that provides a wealth of new insight into the structure and dynamics of biomolecular systems. Recently developed ultrafast laser sources are extending multidimensional spectroscopy into the ultraviolet (UV) region, and this opens up new opportunities for probing fibrils. In a simulation study, we show that 2DUV spectra of the backbone of a 32-residue β-amyloid (Aβ(9-40)) fibril associated with Alzheimer's disease and two intermediate prefibrillar structures carry characteristic signatures of fibril size and geometry that could be used to monitor its formation kinetics. The dependence of these signals on the fibril size and geometry is explored. We demonstrate that the dominant features of the β-amyloid fibril spectra are determined by intramolecular interactions within a single Aβ(9-40), and intermolecular interactions at the "external interface" have clear signatures in the fine details of these signals.

Molecular dynamics simulations of Aβ fibril interactions with β-sheet breaker peptides

Accumulation and aggregation of the 42-residue amyloid-β (Aβ) protein fragment, which originates from the cleavage of amyloid precursor protein by β and γ secretase, correlates with the pathology of Alzheimer's disease (AD). Possible therapies for AD include peptides based on the Aβ sequence, and recently identified small molecular weight compounds designed to mimic these, that interfere with the aggregation of Aβ and prevent its toxic effects on neuronal cells in culture. Here, we use molecular dynamics simulations to compare the mode of interaction of an active (LPFFD) and inactive (LHFFD) β-sheet breaker peptide with an Aβ fibril structure from solid-state NMR studies. We found that LHFFD had a weaker interaction with the fibril than the active peptide, LPFFD, from geometric and energetic considerations, as estimated by the MM/PBSA approach. Cluster analysis and computational alanine scanning identified important ligand-fibril contacts, including a possible difference in the effect of histidine on ligand-fibril π-stacking interactions, and the role of the proline residue in establishing contacts that compete with those essential for maintenance of the inter-monomer β-sheet structure of the fibril. Our results show that molecular dynamics simulations can be a useful way to classify the stability of docking sites. These mechanistic insights into the ability of LPFFD to reverse aggregation of toxic Aβ will guide the redesign of lead compounds, and aid in developing realistic therapies for AD and other diseases of protein aggregation.

An implicit solvent coarse-grained lipid model with correct stress profile

We develop a coarse-grained parametrization strategy for lipid membranes that we illustrate for a dipalmitoylphosphatidylcholine bilayer. Our coarse-graining approach eliminates the high cost of explicit solvent but maintains more lipid interaction sites. We use a broad attractive tail-tail potential and extract realistic bonded potentials of mean force from all-atom simulations, resulting in a model with a sharp gel to fluid transition, a correct bending modulus, and overall very reasonable dynamics when compared with experiment. We also determine a quantitative stress profile and correct breakdown of contributions from lipid components when compared with detailed all-atom simulation benchmarks, which has been difficult to achieve for implicit membrane models. Such a coarse-grained lipid model will be necessary for efficiently simulating complex constructs of the membrane, such as protein assembly and lipid raft formation, within these nonaqueous chemical environments.

The culprit behind amyloid beta peptide related neurotoxicity in Alzheimer's disease: oligomer size or conformation?

Since the reformulation of the amyloid cascade hypothesis to focus on oligomeric aggregates of amyloid beta as the prime toxic species causing Alzheimer's disease, many researchers refocused on detecting a specific molecular assembly of defined size thatis the main trigger of Alzheimer's disease. The result has been the identification of a host of molecular assemblies containing from two up to a hundred molecules of the amyloid beta peptide, which were all found to impair memory formation in mice. This clearly demonstrates that size is insufficient to define toxicity and peptide conformation has to be taken into account. In this review we discuss the interplay between oligomer size and peptide conformation as the key determinants of the neurotoxicity of the amyloid beta peptide.

Thermodynamic perspective on the dock-lock growth mechanism of amyloid fibrils

The mechanism of addition of a soluble unstructured monomer to a preformed ordered amyloid fibril is a complex process. On the basis of the kinetics of monomer disassociation of Abeta(1-40) from the amyloid fibril, it has been suggested that deposition is a multistep process involving a rapid reversible association of the unstructured monomer to the fibril surface (docking) followed by a slower conformational rearrangement leading to the incorporation onto the underlying fibril lattice (locking). By exploiting the vast time scale separation between the dock and lock processes and using molecular dynamics simulation of deposition of the disordered peptide fragment (35)MVGGVV(40) from the Abeta peptide onto the fibril with known crystal structure, we provide a thermodynamic basis for the dock-lock mechanism of fibril growth. Free energy profiles, computed using implicit solvent model and enhanced sampling methods with the distance (delta(C)) between the center of mass of the peptide and the fibril surface as the order parameter, show three distinct basins of attraction. When delta(C) is large, the monomer is compact and unstructured and the favorable interactions with the fibril results in stretching of the peptide at delta(C) approximately 13 A. As delta(C) is further decreased, the peptide docks onto the fibril surface with a structure that is determined by a balance between intrapeptide and peptide fibril interactions. At delta(C) approximately 4 A, a value that is commensurate with the spacing between beta-strands in the fibril, the monomer expands and locks onto the fibril. Using simulations with implicit solvent model and all atom molecular dynamics in explicit water, we show that the locked monomer, which interacts with the underlying fibril, undergoes substantial conformational fluctuations and is not stable. The cosolutes urea and TMAO destabilize the unbound phase and stabilize the docked phase. Interestingly, small crowding particles enhance the stability of the fibril-bound monomer only marginally. We predict that the experimentally measurable critical monomer concentration, C(R), at which the soluble unbound monomer is in equilibrium with the ordered fibril, increases sharply as temperature is increased under all solution conditions.

Principles governing oligomer formation in amyloidogenic peptides

Identifying the principles that describe the formation of protein oligomers and fibrils with distinct morphologies is a daunting problem. Here we summarize general principles of oligomer formation gleaned from molecular dynamics simulations of Abeta-peptides. The spectra of high free energy structures sampled by the monomer provide insights into the plausible fibril structures, providing a rationale for the 'strain phenomenon.' Heterogeneous growth dynamics of small oligomers of Abeta(16-22), whose lowest free energy structures are like nematic droplets, can be broadly described using a two-stage dock-lock mechanism. In the growth process, water is found to play various roles depending on the oligomer size, and peptide length, and sequence. Water may be an explicit element of fibril structure linked to various fibril morphologies.