Aggregation of beta-amyloid fragments

Exploring the aggregation of amyloid-β 42 through Monte Carlo simulations

Coarse-grained Monte Carlo simulations are performed for a disordered protein, amyloid-β 42 to identify the interactions and understand the mechanism of its aggregation. A statistical potential is developed from a selected dataset of intrinsically disordered proteins, which accounts for the respective contributions of the bonded and non-bonded potentials. While, the bonded potential comprises the bond, bend, and dihedral constraints, the nonbonded interactions include van der Waals interactions, hydrogen bonds, and the two-body potential. The two-body potential captures the features of both hydrophobic and electrostatic interactions that brings the chains at a contact distance, while the repulsive van der Waals interactions prevent them from a collapse. Increased two-body hydrophobic interactions facilitate the formation of amorphous aggregates rather than the fibrillar ones. The formation of aggregates is validated from the interchain distances, and the total energy of the system. The aggregate is structurally characterized by the root-mean-square deviation, root-mean-square fluctuation and the radius of gyration. The aggregates are characterized by a decrease in SASA, an increase in the non-local interactions and a distinct free energy minimum relative to that of the monomeric state of amyloid-β 42. The hydrophobic residues help in nucleation, while the charged residues help in oligomerization and aggregation.

Microcanonical insights into the physicochemical stability of the coformulation of insulin with amylin analogues

Injections of insulin are the main treatment for diabetes, but in the long run this therapy can induce serious drawbacks. This has inspired new drugs able to decrease insulin requirements. For instance, human amylin (hIAPP) is a small hormone cosecreted by pancreatic β-cells with insulin to which is a synergistic partner. However, the high amyloidogenicity of hIAPP precluded it as a therapeutics and led to the design of pramlintide (sIAPP), a chimeric analogue with substitutions (A25P, S28P, and S29P) inherited from the aggregation-resistant rat isoform (rIAPP). Despite sIAPP advantages, it still shares with hIAPP a poorly soluble profile at physiological pH that hampers its mixture with insulin. Recent improvements, as charge-enhanced mutants, have been proposed. For instance, sIAPP⁺ was screened in silico by purely microcanonical thermostatistical methods and adds to sIAPP an S20R mutation to uplift its solubility. This suggests that such physically inspired computational approach may also be auspicious on devising effective coformulations of insulin with amylin analogues. In this seminal attempt, we make comparative multicanonical simulations of regular acting human insulin coformulated with hIAPP, sIAPP, or sIAPP⁺. To assess the respective physicochemical stabilities against aggregation, we characterize the structural-phase transitions through the microcanonical thermodynamic formalism and evaluate their time lags using the classical nucleation theory. These results are then correlated with estimates of solvation free energies, modeled by the Poisson-Boltzmann equation, and structural propensities. Experimental essays are compared to our simulations and support our methodology.

Multistep Conformation Selection in Amyloid Assembly

Defining pathways for amyloid assembly could impact therapeutic strategies for as many as 50 disease states. Here we show that amyloid assembly is subject to different forces regulating nucleation and propagation steps and provide evidence that the more global β-sheet/β-sheet facial complementarity is a critical determinant for amyloid nucleation and structural selection.

Stability of amyloid oligomers

Molecular simulations are now commonly used to complement experimental techniques in investigating amyloids and their role in human diseases. In this chapter, we will summarize techniques and approaches often used in amyloid simulations and will present recent success stories. Our examples will be focused on lessons learned from molecular dynamics simulations in aqueous environments that start from preformed aggregates. These studies explore the limitations that arise from the choice of force field, the role of mutations in the growth of amyloid aggregates, segmental polymorphism, and the importance of cross-seeding. Furthermore, they give evidence for potential toxicity mechanisms. We finally discuss the role of molecular simulations in the search for aggregation inhibitors.

Aβ(16-22) peptides can assemble into ordered β-barrels and bilayer β-sheets, while substitution of phenylalanine 19 by tryptophan increases the population of disordered aggregates

A recent experimental study reported that termini-uncapped Aβ(16-22) (with sequence KLVFFAE) peptides self-assembled into nanofibrils at pH 2.0. The oligomerization of this uncapped peptide at atomic level in acidic pH condition remains to be determined, as computational studies mainly focus on the self-assembly of capped Aβ(16-22) peptides at neutral pH condition. In this study, using replica exchange molecular dynamics (REMD) simulations with explicit solvent, we investigated the octameric structures of the uncapped Aβ(16-22) and its F19W variant at acidic pH condition. Our simulations reveal that the Aβ(16-22) octamers adopt various conformations, including closed β-barrels, bilayer β-sheets, and disordered aggregates. The closed β-barrel conformation is particularly interesting, as the cylindrical β-barrel has been reported recently as a cytotoxic species. Interpeptide contact probability analyses between all pairs of residues reveal that the hydrophobic and aromatic stacking interactions between F19 residues play an essential role in the formation of β-barrels and bilayer β-sheets. The importance of F19 and the steric effect on the structures of Aβ(16-22) octamers are further examined by REMD simulation of F19W mutant. This REMD run shows that substitution of F19 by W with a more bulky aromatic side chain significantly reduces the β-sheet content and in turn enhances the population of disordered aggregates, indicating that the steric effect significantly affect the self-assembly of low molecular weight Aβ(16-22) oligomers.

Phase networks of cross-β peptide assemblies

Recent evidence suggests that simple peptides can access diverse amphiphilic phases, and that these structures underlie the robust and widely distributed assemblies implicated in nearly 40 protein misfolding diseases. Here we exploit a minimal nucleating core of the Aβ peptide of Alzheimer's disease to map its morphologically accessible phases that include stable intermolecular molten particles, fibers, twisted and helical ribbons, and nanotubes. Analyses with both fluorescence lifetime imaging microscopy (FLIM) and transmission electron microscopy provide evidence for liquid-liquid phase separations, similar to the coexisting dilute and dense protein-rich liquid phases so critical for the liquid-solid transition in protein crystallization. We show that the observed particles are critical for transitions to the more ordered cross-β peptide phases, which are prevalent in all amyloid assemblies, and identify specific conditions that arrest assembly at the phase boundaries. We have identified a size dependence of the particles in order to transition to the para-crystalline phase and a width of the cross-β assemblies that defines the transition between twisted fibers and helically coiled ribbons. These experimental results reveal an interconnected network of increasing molecularly ordered cross-β transitions, greatly extending the initial computational models for cross-β assemblies.

Aggregation of amyloids in a cellular context: modelling and experiment

Amyloid-related diseases are a group of illnesses in which an abnormal accumulation of proteins into fibrillar structures is evident. Results from a wide range of studies, ranging from identification of amyloid-β dimers in the brain to biophysical characterization of the interactions between amyloidogenic peptides and lipid membranes during fibril growth shed light on the initial events which take place during amyloid aggregation. Accounts of fibril disaggregation and formation of globular aggregates due to interactions with lipids or fatty acids further demonstrate the complexity of the aggregation process and the difficulty to treat amyloid-related diseases. There is an inherent difficulty in generalizing from studies of aggregation in vitro, but the involvement of too many cellular components limits the ability to follow amyloid aggregation in a cellular (or extracellular) context. Fortunately, the development of experimental methods to generate stable globular aggregates suggests new means of studying the molecular events associated with amyloid aggregation. Furthermore, simulation studies enable deeper understanding of the experimental results and provide useful predictions that can be tested in the laboratory. Computer simulations can nowadays provide molecular or even atomistic details that are experimentally not available or very difficult to obtain. In the present review, recent developments on modelling and experiments of amyloid aggregation are reviewed, and an integrative account on how isolated interactions (as observed in vitro and in silico) combine during the course of amyloid-related diseases is presented. Finally, it is argued that an integrative approach is necessary to get a better understanding of the protein aggregation process.

Monte Carlo simulations of protein amyloid formation reveal origin of sigmoidal aggregation kinetics

Severe conditions and lack of cure for many amyloid diseases make it highly desired to understand the underlying principles of formation of fibrillar aggregates (amyloid). Here, amyloid formation from peptides was studied using Monte Carlo simulations. Systems of 20, 50, 100, 200 or 500 hexapeptides were simulated. Association kinetics were modeled equal for fibrillar and other (inter- and intra-peptide) contacts and assumed to be faster the lower the effective contact order, which represents the distance in space. Attempts to form contacts were thus accepted with higher probability the lower the effective contact order, whereby formation of new contacts next to preexisting ones is favored by shorter physical separation. Kinetic discrimination was invoked by using two different life-times for formed contacts. Contacts within amyloid fibrils were assumed to have on average longer life-time than other contacts. We find that the model produces fibrillation kinetics with a distinct lag phase, and that the fibrillar contacts need to dissociate on average 5-20 times slower than all other contacts for the fibrillar structure to dominate at equilibrium. Analysis of the species distribution along the aggregation process shows that no other intermediate is ever more populated than the dimer. Instead of a single nucleation event there is a concomitant increase in average aggregate size over the whole system, and the occurrence of multiple parallel processes makes the process more reproducible the larger the simulated system. The sigmoidal shape of the aggregation curves arises from cooperativity among multiple interactions within each pair of peptides in a fibril. A governing factor is the increasing probability as the aggregation process proceeds of neighboring reinforcing contacts. The results explain the very strong bias towards cross β-sheet fibrils in which the possibilities for cooperativity among interactions involving neighboring residues and the repetitive use of optimal side-chain interactions are explored at maximum.

Computer simulations of the growth of synthetic peptide fibres

We present a coarse-grained computer model designed to study the growth of fibres in a synthetic self-assembling peptide system. The system consists of two 28 residue α-helical sequences, denoted AB and CD, in which the interactions between the half peptides, A, B, C and D, may be tuned individually to promote different types of growth behaviour. In the model, AB and CD are represented by double ended rods, with interaction sites distributed along their lengths. Monte Carlo simulations are performed to follow fibre growth. It is found that lateral and longitudinal growth of the fibre are governed by different mechanisms--the former is diffusion limited with a very small activation energy for the addition of units, whereas the latter occurs via a process of secondary nucleation at the fibre ends. As a result, longitudinal growth generally proceeds more slowly than lateral growth. Furthermore, it is shown that the aspect ratio of the growing fibre may be controlled by adjusting the temperature and the relative strengths of the interactions. The predictions of the model are discussed in the context of published data from real peptide systems.

Rapid aggregation and assembly in aqueous solution of A beta (25-35) peptide

The highly toxic A beta (25-35) is a peculiar peptide that differs from all the other commonly studied beta-amyloid peptides because of its extremely rapid aggregation properties and enhanced neurotoxicity. We investigated A beta (25-35) aggregation in H2O at pH 3.0 and at pH 7.4 by means of in-solution analyses. Adopting UV spectroscopy, Congo red spectrophotometry and thioflavin T fluorimetry, we were able to quantify, in water, the very fast assembling time necessary for A beta (25-35) to form stable insoluble aggregates and their ability to seed or not seed fibril growth. Our quantitative results, which confirm a very rapid assembly leading to stable insoluble aggregates of A beta (25-35) only when incubated at pH 7.4, might be helpful for designing novel aggregation inhibitors and to shed light on the in vivo environment in which fibril formation takes place.

Interaction between amyloid-beta (1-42) peptide and phospholipid bilayers: a molecular dynamics study

The amyloid-beta (Abeta) peptide is a key aggregate species in Alzheimer's disease. Although important aspects of Abeta peptide aggregation are understood, the initial stage of aggregation from monomer to oligomer is still not clear. One potential mediator of this early aggregation process is interactions of Abeta with anionic cell membranes. We used unconstrained and umbrella sampling molecular dynamics simulations to investigate interactions between the 42-amino acid Abeta peptide and model bilayers of zwitterionic dipalmitoylphosphatidylcholine (DPPC) lipids and anionic dioleoylphosphatidylserine (DOPS) lipids. Using these methods, we determined that Abeta is attracted to the surface of DPPC and DOPS bilayers over the small length scales used in these simulations. We also found supporting evidence that the charge on both the bilayer surface and the peptide affects the free energy of binding of the peptide to the bilayer surface and the distribution of the peptide on the bilayer surface. Our work demonstrates that interactions between the Abeta peptide and lipid bilayer promotes a peptide distribution on the bilayer surface that is prone to peptide-peptide interactions, which can influence the propensity of Abeta to aggregate into higher-order structures.

Simulating oligomerization at experimental concentrations and long timescales: A Markov state model approach

Here, we present a novel computational approach for describing the formation of oligomeric assemblies at experimental concentrations and timescales. We propose an extension to the Markovian state model approach, where one includes low concentration oligomeric states analytically. This allows simulation on long timescales (seconds timescale) and at arbitrarily low concentrations (e.g., the micromolar concentrations found in experiments), while still using an all-atom model for protein and solvent. As a proof of concept, we apply this methodology to the oligomerization of an Abeta peptide fragment (Abeta(21-43)). Abeta oligomers are now widely recognized as the primary neurotoxic structures leading to Alzheimer's disease. Our computational methods predict that Abeta trimers form at micromolar concentrations in 10 ms, while tetramers form 1000 times more slowly. Moreover, the simulation results predict specific intermonomer contacts present in the oligomer ensemble as well as putative structures for small molecular weight oligomers. Based on our simulations and statistical models, we propose a novel mutation to stabilize the trimeric form of Abeta in an experimentally verifiable manner.

Nanofluidic biosensing for beta-amyloid detection using surface enhanced Raman spectroscopy

Trace detection of the conformational transition of beta-amyloid peptide (Abeta) from a predominantly alpha-helical structure to beta-sheet could have a large impact in understanding and diagnosing Alzheimer's disease. We demonstrate how a novel nanofluidic biosensor using a controlled, reproducible surface enhanced Raman spectroscopy active site was developed to observe Abeta in different conformational states during the Abeta self-assembly process as well as to distinguish Abeta from confounder proteins commonly found in cerebral spinal fluid.

Understanding protein folding: small proteins in silico

Recent improvements in methodology and increased computer power now allow atomistic computer simulations of protein folding. We briefly review several advanced Monte Carlo algorithms that have contributed to this development. Details of folding simulations of three designed mini proteins are shown. Adding global translations and rotations has allowed us to handle multiple chains and to simulate the aggregation of six beta-amyloid fragments. In a different line of research we have developed several algorithms to predict local features from sequence. In an outlook we sketch how such biasing could extend the application spectrum of Monte Carlo simulations to structure prediction of larger proteins.

Thermodynamics and kinetics of aggregation for the GNNQQNY peptide

The energy landscape of the monomer and dimer are explored for the amyloidogenic heptapeptide GNNQQNY from the N-terminal prion-determining domain of the yeast protein Sup35. The peptide is modeled by a united-atom potential and an implicit solvent representation. Replica exchange molecular dynamics is used to explore the conformational space, and discrete path sampling is employed to investigate the pathways that interconvert the most populated minima on the free energy surfaces. For the monomer, we find a rapid fluctuation between four different conformations, where a geometry intermediate between compact and extended structures is the most thermodynamically favorable. The GNNQQNY dimer forms three stable sheet structures, namely in-register parallel, off-register parallel, and antiparallel. The antiparallel dimer is stabilized by strong electrostatic interactions resulting from interpeptide hydrogen bonds, which restrict its conformational flexibility. The in-register parallel dimer, which is close to the amyloid beta-sheet structure, has fewer interpeptide hydrogen bonds, making hydrophobic interactions more important and increasing the conformational entropy compared to the antiparallel sheet. The estimated two-state rate constants indicate that the formation of dimers from monomers is fast and that the dimers are kinetically stable against dissociation at room temperature. Interconversions between the different dimers are feasible processes and are more likely than dissociation.

Effects of hydrophobic and dipole-dipole interactions on the conformational transitions of a model polypeptide

We studied the effects of hydrophobicity and dipole-dipole interactions between the nearest-neighbor amide planes on the secondary structures of a model polypeptide by calculating the free energy differences between different peptide structures. The free energy calculations were performed with low computational costs using the accelerated Monte Carlo simulation (umbrella sampling) method, with a bias-potential method used earlier in our accelerated molecular dynamics simulations. It was found that the hydrophobic interaction enhances the stability of alpha helices at both low and high temperatures but stabilizes beta structures only at high temperatures at which alpha helices are not stable. The nearest-neighbor dipole-dipole interaction stabilizes beta structures under all conditions, especially in the low temperature region where alpha helices are the stable structures. Our results indicate clearly that the dipole-dipole interaction between the nearest neighboring amide planes plays an important role in determining the peptide structures. Current research provides a more unified and quantitative picture for understanding the effects of different forms of interactions on polypeptide structures. In addition, the present model can be extended to describe DNA/RNA, polymer, copolymer, and other chain systems.