Effects of macromolecular crowding on amyloid beta (16-22) aggregation using coarse-grained simulations

Can local heating and molecular crowders disintegrate amyloid aggregates?

The present study employs a blend of molecular dynamics simulations and a theoretical model to explore the potential disintegration mechanism of a matured Aβ octamer, aiming to offer a strategy to combat Alzheimer's disease. We investigate local heating and crowding effects on Aβ disintegration by selectively heating key Aβ segments and varying the concentration of sodium dodecyl sulphate (SDS), respectively. Despite initiation of disruption, Aβ aggregates resist complete disintegration during local heating due to rapid thermal energy distribution to the surrounding water. Conversely, although SDS molecules effectively inhibit Aβ aggregation at higher concentration through micelle formation, they fail to completely disintegrate the aggregate due to the exceedingly high energy barrier. To address the sampling challenge posed by the formidable energy barrier, we have performed well-tempered metadynamics simulations. Simulations reveal a multi-step disintegration mechanism for the Aβ octamer, suggesting a probable sequence: octamer → pentamer/hexamer ⇌ tetramer → monomer, with a rate-determining step constituting 45 kJ mol-1 barrier during the octamer to pentamer/hexamer transition. Additionally, we have proposed a novel two-state mean-field model based on Ising spins that offers an insight into the kinetics of the Aβ growth process and external perturbation effects on disintegration. Thus, the current simulation study, coupled with the newly introduced mean-field model, offers an insight into the detailed mechanisms underlying the Aβ aggregation process, guiding potential strategies for effective disintegration of Aβ aggregates.

Modulation of Aβ 16-22 aggregation by glucose

The self-assembly of amyloid-beta (Aβ) peptides into fibrillar structures in the brain is a signature of Alzheimer's disease. Recent studies have reported correlations between Alzheimer's disease and type-2 diabetes. Structurally, hyperglycemia induces covalent protein crosslinkings by advanced glycation end products (AGE), which can affect the stability of Aβ oligomers. In this work, we leverage physics-based coarse-grained molecular simulations to probe alternate thermodynamic pathways that affect peptide aggregation propensities at varying concentrations of glucose molecules. Similar to previous experimental reports, our simulations show a glucose concentration-dependent increase in Aβ aggregation rates, without changes in the overall secondary structure content. We discovered that glucose molecules prefer partitioning onto the aggregate-water interface at a specific orientation, resulting in a loss of molecular rotational entropy. This effectively hastens the aggregation rates, as peptide self-assembly can reduce the available surface area for peptide-glucose interactions. This work introduces a new thermodynamic-driven pathway, beyond chemical cross-linking, that can modulate Aβ aggregation.

Effect of the Macromolecular Crowding Agents on the Structure and Function of Human Arginase-I, a Therapeutically Important Enzyme

Macromolecular crowding has been known to influence the structure and function of many enzymes through excluded volume effects and/or soft interactions. Here, we employed two synthetic macromolecular crowders, Dextrans and poly(ethylene glycol)s (PEGs) with varying molecular masses, to examine how they affected the structure and function of a therapeutically important enzyme, human arginase-I that catalyzes the conversion of l-arginine to l-ornithine and urea. Except at greater concentrations of Dextran 200, Dextrans were observed to slightly reduce the enzymatic activity, indicating that they exert their influence mainly through the excluded volume effects. Similar outcomes were seen with PEGs, with the exception of PEG 1000, where the activity decreased with increasing PEG concentrations, showing the maximum effect at a 20 g/L concentration. This finding suggests that the enzyme function is reduced by the soft interactions of this macromolecule with the enzyme, supported by the binding measurement. Secondary and local tertiary structures and thermodynamic stability were also affected, suggesting that PEG 1000 has an impact on the protein's structure. Furthermore, molecular dynamics simulation studies suggest that the catalytic pocket is disturbed, presumably by the unwinding of neighboring helix 9. As a result, the positioning of nearby Glu277 is altered, which prevents His141 and Glu277 from making contact. This hampers the proton transfer from the catalytic His141 to the intermediate species to form ornithine, a crucial step for the substrate hydrolysis reaction by this arginase. Overall, the knowledge gained from this study might be helpful for understanding how different enzymes work in a crowded/cellular environment.

Fibrillization Process of Human Amyloid-Beta Protein (1-40) under a Molecular Crowding Environment Mimicking the Interior of Living Cells Using Cell Debris

Molecular crowding environments play a crucial role in understanding the mechanisms of biological reactions. Inside living cells, a diverse array of molecules coexists within a volume fraction ranging from 10% to 30% v/v. However, conventional spectroscopic methods often face difficulties in selectively observing the structures of particular proteins or membranes within such molecularly crowded environments due to the presence of high background signals. Therefore, it is crucial to establish in vitro measurement conditions that closely resemble the intracellular environment. Meanwhile, the neutron scattering method offers a significant advantage in selectively observing target biological components, even within crowded environments. Recently, we have demonstrated a novel scattering method capable of selectively detecting the structures of targeted proteins or membranes in a closely mimicking intracellular milieu achieved utilizing whole-cell contents (deuterated-cell debris). This method relies on the inverse contrast matching technique in neutron scattering. By employing this method, we successfully observed the fibrillization process of human amyloid beta-protein (Aβ 1-40) under a molecular crowding environment (13.1% w/v cell debris, Aβ/cell debris = ~1/25 w/w) that closely mimics the interior of living cells. Aβ protein is well known as a major pathogenic component of Alzheimer's disease. The present results combining model simulation analyses clearly show that the intracellular environment facilitates the potential formation of even more intricate higher-order aggregates of Aβ proteins than those previously reported.

Ethylene glycol energetically disfavours oligomerization of pseudoisocyanine dyestuffs at crowded concentrations

The intriguing role of the intracellular crowded environment in regulating protein aggregation remains elusive. The convolution of several factors such as the protein sequence-dependence, crowder's shape and size and diverse intermolecular interactions makes it complex to identify systematic trends. One of the ways to simplify the problem is to study a synthetic model for self-assembling proteins. In this study, we examine the aggregation behaviour of the cationic pseudoisocyanine chloride (PIC) dyestuff which is known to self-assemble and form fibril-like J-aggregates in aqueous solutions, similar to those formed by amyloid-forming proteins. Prior experimental studies have shown that polyethylene glycol impedes and Ficoll-400 promotes the self-assembly of PIC dyes. To achieve molecular insights, we examine the effect of crowding by ethylene glycol on the solvation thermodynamics of oligomerization of dyes into H-type and J-type oligomers using extensive molecular dynamics simulations. The binding free energy calculations show that the formation of J-oligomers is more favourable than that of H-oligomers in water. The stability of H- and J- tetramers and pentamers decreases in crowded solutions. The formation of oligomers is supported by the favourable change in dye-solvent interaction energy in both pure water and aqueous ethylene glycol solution although it is opposed by the reduced dye-solvent entropy. Ethylene glycol, as a molecular crowder, disfavours the H- as well as J-oligomerization via preferential binding to the dye oligomers. An unfavourable change in dye-crowder and dye-dye interaction energy on dye association makes the H-oligomer formation less favourable in crowded solution than in pure water solution. In the case of J-oligomers, however, the unfavourable change in dye-crowder interaction energy primarily contributes to making total dye-solvent energy unfavourable. The results are supported by isothermal titration calorimetry measurements where the binding of ethylene glycol to PIC molecules is found to be endothermic. The results provide an emerging view that a crowded environment can disfavour self-assembly of PIC dyes by interactions with the oligomeric states. The findings have implications in understanding the role of a crowded environment in shaping the free energy landscapes of proteins.

Conformational Plasticity in α-Synuclein and How Crowded Environment Modulates It

A 140-residue intrinsically disordered protein (IDP), α-synuclein (αS), is known to adopt conformations that are vastly plastic and susceptible to environmental cues and crowders. However, the inherently heterogeneous nature of αS has precluded a clear demarcation of its monomeric precursor between aggregation-prone and functionally relevant aggregation-resistant states and how a crowded environment could modulate their mutual dynamic equilibrium. Here, we identify an optimal set of distinct metastable states of αS in aqueous media by dissecting a 73 μs-long molecular dynamics ensemble via building a comprehensive Markov state model (MSM). Notably, the most populated metastable state corroborates with the dimension obtained from PRE-NMR studies of αS monomer, and it undergoes kinetic transition at diverse time scales with a weakly populated random-coil-like ensemble and a globular protein-like state. However, subjecting αS to a crowded environment results in a nonmonotonic compaction of these metastable conformations, thereby skewing the ensemble by either introducing new tertiary contacts or by reinforcing the innate contacts. The early stage of dimerization process is found to be considerably expedited in the presence of crowders, albeit promoting nonspecific interactions. Together with this, using an extensively sampled ensemble of αS, this exposition demonstrates that crowded environments can potentially modulate the conformational preferences of IDP that can either promote or inhibit aggregation events.

Energy landscapes of Aβ monomers are sculpted in accordance with Ostwald's rule of stages

The transition from a disordered to an assembly-competent monomeric state (N*) in amyloidogenic sequences is a crucial event in the aggregation cascade. Using a well-calibrated model for intrinsically disordered proteins (IDPs), we show that the N* states, which bear considerable resemblance to the polymorphic fibril structures found in experiments, not only appear as excitations in the free energy landscapes of Aβ40 and Aβ42, but also initiate the aggregation cascade. For Aβ42, the transitions to the different N* states are in accord with Ostwald's rule of stages, with the least stable structures forming ahead of thermodynamically favored ones. The Aβ40 and Aβ42 monomer landscapes exhibit different extents of local frustration, which we show have profound implications in dictating subsequent self-assembly. Using kinetic transition networks, we illustrate that the most favored dimerization routes proceed via N* states. We argue that Ostwald's rule also holds for the aggregation of fused in sarcoma and polyglutamine proteins.

Conformation and dynamics of an active filament in crowded media

The structural and dynamical properties of active filamentous objects under macromolecular crowding have a great relevance in biology. By means of Brownian dynamics simulations, we perform a comparative study for the conformational change and diffusion dynamics of an active chain in pure solvents and in crowded media. Our result shows a robust compaction-to-swelling conformational change with the augment of the Péclet number. The presence of crowding facilitates self-trapping of monomers and, thus, reinforces the activity mediated compaction. In addition, the efficient collisions between the self-propelled monomers and crowders induce a coil-to-globulelike transition, indicated by a marked change of the Flory scaling exponent of the gyration radius. Moreover, the diffusion dynamics of the active chain in crowded solutions demonstrates activity-enhanced subdiffusion. The center of mass diffusion manifests rather new scaling relations with respect to both the chain length and Péclet number. The interplay of chain activity and medium crowding provides a new mechanism to understand the non-trivial properties of active filaments in complex environments.

Self-Assembly of Amyloid-Beta (Aβ) Peptides from Solution to Near In Vivo Conditions

Understanding the atomistic resolution changes during the self-assembly of amyloid peptides or proteins is important to develop compounds or conditions to alter the aggregation pathways and suppress the toxicity and potentially aid in the development of drugs. However, the complexity of protein aggregation and the transient order/disorder of oligomers along the pathways to fibril are very challenging. In this Perspective, we discuss computational studies of amyloid polypeptides carried out under various conditions, including conditions closely mimicking in vivo and point out the challenges in obtaining physiologically relevant results, focusing mainly on the amyloid-beta Aβ peptides.

An Alzheimer's Disease Mechanism Based on Early Pathology, Anatomy, Vascular-Induced Flow, and Migration of Maximum Flow Stress Energy Location with Increasing Vascular Disease

This paper suggests a chemical mechanism for the earliest stages of Alzheimer's disease (AD). Cerebrospinal fluid (CSF) flow stresses provide the energy needed to induce molecular conformation changes leading to AD by initiating amyloid-β (Aβ) and tau aggregation. Shear and extensional flow stresses initiate aggregation in the laboratory and in natural biophysical processes. Energy-rich CSF flow regions are mainly found in lower brain regions. MRI studies reveal flow stress "hot spots" in basal cisterns and brain ventricles that have chaotic flow properties that can distort molecules such as Aβ and tau trapped in these regions into unusual conformations. Such fluid disturbance is surrounded by tissue deformation. There is strong mapping overlap between the locations of these hot spots and of early-stage AD pathology. Our mechanism creates pure and mixed protein dimers, followed by tissue surface adsorption, and long-term tissue agitation ultimately inducing chemical reactions forming more stable, toxic oligomer seeds that initiate AD. It is proposed that different flow stress energies and flow types in different basal brain regions produce different neurotoxic aggregates. Proliferating artery hardening is responsible for enhanced heart systolic pulses that drive energetic CSF pulses, whose critical maximum systolic pulse energy location migrates further from the heart with increasing vascular disease. Two glymphatic systems, carotid and basilar, are suggested to contain the earliest Aβ and tau AD disease pathologies. A key to the proposed AD mechanism is a comparison of early chronic traumatic encephalopathy and AD pathologies. Experiments that test the proposed mechanism are needed.

Transferable and Polarizable Coarse Grained Model for Proteins─ProMPT

The application of classical molecular dynamics (MD) simulations at atomic resolution (fine-grained level, FG), to most biomolecular processes, remains limited because of the associated computational complexity of representing all the atoms. This problem is magnified in the presence of protein-based biomolecular systems that have a very large conformational space, and MD simulations with fine-grained resolution have slow dynamics to explore this space. Current transferable coarse grained (CG) force fields in literature are either limited to only peptides with the environment encoded in an implicit form or cannot capture transitions into secondary/tertiary peptide structures from a primary sequence of amino acids. In this work, we present a transferable CG force field with an explicit representation of the environment for accurate simulations with proteins. The force field consists of a set of pseudoatoms representing different chemical groups that can be joined/associated together to create different biomolecular systems. This preserves the transferability of the force field to multiple environments and simulation conditions. We have added electronic polarization that can respond to environmental heterogeneity/fluctuations and couple it to protein's structural transitions. The nonbonded interactions are parametrized with physics-based features such as solvation and partitioning free energies determined by thermodynamic calculations and matched with experiments and/or atomistic simulations. The bonded potentials are inferred from corresponding distributions in nonredundant protein structure databases. We present validations of the CG model with simulations of well-studied aqueous protein systems with specific protein fold types─Trp-cage, Trpzip4, villin, WW-domain, and β-α-β. We also explore the applications of the force field to study aqueous aggregation of Aβ 16-22 peptides.

Distribution and Structure Analysis of Fibril-Forming Peptides Focusing on Concentration Dependency

We focus on the concentration dependency of fibril-forming peptides, which have the potential of aggregation by themselves. In this study, we performed replica-exchange molecular dynamics simulations of Lys-Phe-Phe-Glu (KFFE) fragments, which are known to form fibrils in experiments under different concentration environments. The analysis by static structure factors suggested that the density fluctuation of the KFFE fragments becomes large as the concentration increases. It was also found that the number of β-structures and oligomers also increases under a high concentration environment. Hence, a high concentration environment of fibril-forming peptides is likely to cause protein aggregation.

Passive and active tracer dynamics in polymer solutions with isotropic-to-nematic phase transition

Macromolecular crowding plays a crucial role in determining the dynamics in a living cell. We adopt Langevin dynamics simulations to investigate the anomalous diffusion dynamics of passive and active particles in a solution of polymer chains with tunable stiffness. The solution's anisotropic feature is modulated by changing both the polymer stiffness and volume fraction, where isotropic-to-nematic phase transition is involved. Our results demonstrate the significant impact of polymer flexibility on the dynamics of both passive and active probes. The distinct diffusion mechanism for an active particle is clarified by the interplay between polymer stiffness, crowdedness and activity. Polymer stiffness leads to a global inhibition effect on passive particle diffusion. The diffusion coefficient exhibits an intriguing non-monotonic variation at increasing polymer stiffness, which is due to the fact that the alignment of polymer chains is beneficial for diffusion along the nematic direction but unfavorable for that in the direction perpendicular to it. In sharp contrast, polymer stiffness plays a dominant role in facilitating active particle diffusion. Self-propulsion of the particle can utilize stiffness-induced elastic interactions more efficiently, which promotes its mobility in both directions. Meanwhile, an active particle might have a stronger ability to take advantage of the polymer alignment, contributing substantially enhanced diffusivity. In addition, the diffusion coefficient of an active particle is subject to a tendency of degeneration against varying volume fraction. This counter-intuitive behavior is due to the contrasting factors that increasing crowdedness induces a lower particle speed but a longer persistent motion time.

Computational models for studying physical instabilities in high concentration biotherapeutic formulations

Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.

Polymorphism of Alpha-Synuclein Amyloid Fibrils Depends on Ionic Strength and Protein Concentration

Protein aggregate formation is linked with multiple amyloidoses, including Alzheimer's and Parkinson's diseases. Currently, the understanding of such fibrillar structure formation and propagation is still not sufficient, the outcome of which is a lack of potent, anti-amyloid drugs. The environmental conditions used during in vitro protein aggregation assays play an important role in determining both the aggregation kinetic parameters, as well as resulting fibril structure. In the case of alpha-synuclein, ionic strength has been shown as a crucial factor in its amyloid aggregation. In this work, we examine a large sample size of alpha-synuclein aggregation reactions under thirty different ionic strength and protein concentration combinations and determine the resulting fibril structural variations using their dye-binding properties, secondary structure and morphology. We show that both ionic strength and protein concentration determine the structural variability of alpha-synuclein amyloid fibrils and that sometimes even identical conditions can result in up to four distinct types of aggregates.

An Overview of Several Inhibitors for Alzheimer's Disease: Characterization and Failure

Amyloid beta (Aβ) oligomers are the most neurotoxic aggregates causing neuronal death and cognitive damage. A detailed elucidation of the aggregation pathways from oligomers to fibril formation is crucial to develop therapeutic strategies for Alzheimer's disease (AD). Although experimental techniques rely on the measure of time- and space-average properties, they face severe difficulties in the investigation of Aβ peptide aggregation due to their intrinsically disorder character. Computer simulation is a tool that allows tracing the molecular motion of molecules; hence it complements Aβ experiments, as it allows to explore the binding mechanism between metal ions and Aβ oligomers close to the cellular membrane at the atomic resolution. In this context, integrated studies of experiments and computer simulations can assist in mapping the complete pathways of aggregation and toxicity of Aβ peptides. Aβ oligomers are disordered proteins, and due to a rapid exploration of their intrinsic conformational space in real-time, they are challenging therapeutic targets. Therefore, no good drug candidate could have been identified for clinical use. Our previous investigations identified two small molecules, M30 (2-Octahydroisoquinolin-2(1H)-ylethanamine) and Gabapentin, capable of Aβ binding and inhibiting molecular aggregation, synaptotoxicity, intracellular calcium signaling, cellular toxicity and memory losses induced by Aβ. Thus, we recommend these molecules as novel candidates to assist anti-AD drug discovery in the near future. This review discusses the most recent research investigations about the Aβ dynamics in water, close contact with cell membranes, and several therapeutic strategies to remove plaque formation.

Crowding affects structural dynamics and contributes to membrane association of the NS3/4A complex

Using molecular dynamics simulations, we describe how crowded environments affect the internal dynamics and diffusion of the hepatitis C virus proteases NS3/4A. This protease plays a key role in viral replication and is successfully used as a target for antiviral treatment. The NS3 enzyme requires a peptide cofactor, called NS4A, with its central part interacting with the NS3 β-sheet, and flexible, protruding terminal tails that are unstructured in water solution. The simulations describe the enzyme and water molecules at atomistic resolution, whereas crowders are modeled via either all-atom or coarse-grained models to emphasize different aspects of crowding. Crowders reflect the polyethylene glycol (PEG) molecules used in the experiments to mimic the crowded surrounding. A bead-shell model of folded coarse-grained PEG molecules considers mainly the excluded volume effect, whereas all-atom PEG models afford more protein-like crowder interactions. Circular dichroism spectroscopy experiments of the NS4A N-terminal tail show that a helical structure is formed in the presence of PEG crowders. The simulations suggest that crowding may assist in the formation of an NS4A helical fragment, positioned exactly where a transmembrane helix would fold upon the NS4A contact with the membrane. In addition, partially interactive PEGs help the NS4A N-tail to detach from the protease surface, thus enabling the process of helix insertion and potentially helping the virus establish a replication machinery needed to produce new viruses. Results point to an active role of crowding in assisting structural changes in disordered protein fragments that are necessary for their biological function.

De novo design of peptides that coassemble into β sheet-based nanofibrils

Peptides’ hierarchical coassembly into nanostructures enables controllable fabrication of multicomponent biomaterials. In this work, we describe a computational and experimental approach to design pairs of charge-complementary peptides that selectively coassemble into β-sheet nanofibers when mixed together but remain unassembled when isolated separately. The key advance is a peptide coassembly design (PepCAD) algorithm that searches for pairs of coassembling peptides. Six peptide pairs are identified from a pool of ~10⁶ candidates via the PepCAD algorithm and then subjected to DMD/PRIME20 simulations to examine their co-/self-association kinetics. The five pairs that spontaneously aggregate in kinetic simulations selectively coassemble in biophysical experiments, with four forming β-sheet nanofibers and one forming a stable nonfibrillar aggregate. Solid-state NMR, which is applied to characterize the coassembling pairs, suggests that the in silico peptides exhibit a higher degree of structural order than the previously reported CATCH(+/−) peptides.

Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis

Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.

Different Aggregation Pathways and Structures for Aβ40 and Aβ42 Peptides

Self-aggregation of amyloid-β (Aβ) peptides has been known to play a vital role in the onset stage of neurodegenerative diseases, indicating the necessity of understanding the aggregation process of Aβ peptides. Despite previous studies on the aggregation process of Aβ peptides, the aggregation pathways of Aβ isoforms (i.e., Aβ40 and Aβ42) and their related structures have not been fully understood yet. Here, we study the aggregation pathways of Aβ40 and Aβ42, and the structures of Aβ40 and Aβ42 aggregates during the process, based on fluorescence and atomic force microscopy (AFM) experiments. It is shown that in the beginning of aggregation process for both Aβ40 and Aβ42, a number of particles (i.e., spherical oligomers) are formed. These particles are subsequently self-assembled together, resulting in the formation of different shapes of amyloid fibrils. Our finding suggests that the different aggregation pathways of Aβ isoforms lead to the amyloid fibrils with contrasting structure.

Studies on the structure and conformational flexibility of secondary structures in amyloid beta — A quantum chemical study

Density functional theory (DFT) calculations are performed to study the conformational flexibility of secondary structures in amyloid beta (A[Formula: see text]) polypeptide. In DFT, M06-2X/6-31[Formula: see text]G(d, p) method is used to optimize the secondary structures of 2LFM and 2BEG in gas phase and in solution phase. Our calculations show that the secondary structures are energetically more stable in solution phase than in gas phase. This is due to the presence of strong solvent interaction with the secondary structures considered in this study. Among the backbone [Formula: see text] and [Formula: see text] dihedral angles, [Formula: see text] varies significantly in sheet structure. This is due to the absence of intermolecular hydrogen bond (H-bond) interactions in sheets considered in this study. Our calculations show that the conformational transition of helix/coil to sheet or vice-versa is due to the floppiness of the amino acid residues. This is observed from the Ramachandran map of the studied secondary structures. Further, it is noted that the intramolecular H-bond interactions play a significant role in the conformational transition of secondary structures of A[Formula: see text].

On the Conformational Dynamics of β-Amyloid Forming Peptides: A Computational Perspective

Understanding the conformational dynamics of proteins and peptides involved in important functions is still a difficult task in computational structural biology. Because such conformational transitions in β-amyloid (Aβ) forming peptides play a crucial role in many neurological disorders, researchers from different scientific fields have been trying to address issues related to the folding of Aβ forming peptides together. Many theoretical models have been proposed in the recent years for studying Aβ peptides using mathematical, physicochemical, and molecular dynamics simulation, and machine learning approaches. In this article, we have comprehensively reviewed the developmental advances in the theoretical models for Aβ peptide folding and interactions, particularly in the context of neurological disorders. Furthermore, we have extensively reviewed the advances in molecular dynamics simulation as a tool used for studying the conversions between polymorphic amyloid forms and applications of using machine learning approaches in predicting Aβ peptides and aggregation-prone regions in proteins. We have also provided details on the theoretical advances in the study of Aβ peptides, which would enhance our understanding of these peptides at the molecular level and eventually lead to the development of targeted therapies for certain acute neurological disorders such as Alzheimer's disease in the future.

Aggregation of disease-related peptides

Protein misfolding and aggregation of amyloid proteins is the fundamental cause of more than 20 diseases. Molecular mechanisms of the self-assembly and the formation of the toxic aggregates are still elusive. Computer simulations have been intensively used to study the aggregation of amyloid peptides of various amino acid lengths related to neurodegenerative diseases. We review atomistic and coarse-grained simulations of short amyloid peptides aimed at determining their transient oligomeric structures and the early and late aggregation steps.

Modeling Crowded Environment in Molecular Simulations

Biomolecules perform their various functions in living cells, namely in an environment that is crowded by many macromolecules. Thus, simulating the dynamics and interactions of biomolecules should take into account not only water and ions but also other binding partners, metabolites, lipids and macromolecules found in cells. In the last decade, research on how to model macromolecular crowders around proteins in order to simulate their dynamics in models of cellular environments has gained a lot of attention. In this mini-review we focus on the models of crowding agents that have been used in computer modeling studies of proteins and peptides, especially via molecular dynamics simulations.

Recent Advances in Coarse-Grained Models for Biomolecules and Their Applications

Molecular dynamics simulations have emerged as a powerful tool to study biological systems at varied length and timescales. The conventional all-atom molecular dynamics simulations are being used by the wider scientific community in routine to capture the conformational dynamics and local motions. In addition, recent developments in coarse-grained models have opened the way to study the macromolecular complexes for time scales up to milliseconds. In this review, we have discussed the principle, applicability and recent development in coarse-grained models for biological systems. The potential of coarse-grained simulation has been reviewed through state-of-the-art examples of protein folding and structure prediction, self-assembly of complexes, membrane systems and carbohydrates fiber models. The multiscale simulation approaches have also been discussed in the context of their emerging role in unravelling hierarchical level information of biosystems. We conclude this review with the future scope of coarse-grained simulations as a constantly evolving tool to capture the dynamics of biosystems.

Quantifying the protein-protein association rate in polymer solutions: crowding-induced diffusion and energy modifications

A theoretical framework is developed to study protein-protein association in polymer solutions under diffusion-limited conditions. Starting from the basal association rate, two fundamental aspects concerning macromolecular crowding are particularly taken into account. One is the effect of microviscosity on protein diffusion. The length-scale dependent relations of translational and rotational diffusion coefficients are incorporated. Another is relevant to the crowding-induced effective interaction between the pair of proteins. The resultant energy modifications to the basal association rate are properly introduced, following an instructive classification with increasing crowder size: repulsive interaction dominant, repulsive and attractive interactions competitive, and attractive interaction prevailing. With specific energy modification terms, we are able to investigate the deviations of the association rate from the Stokes-Einstein (SE) behavior (i.e., the linear relationship with respect to the reciprocal of macroviscosity) in a quantitative manner. Our theory is applied to study the association of TEM1-β-lactamase (TEM) and the β-lactamase inhibitor protein (BLIP) in polyethylene glycol (PEG) solutions, with varying concentration and polymerization. We explicitly evaluate the relative association rate constant as a function of the solution macroviscosity. The theoretical results demonstrate very good agreement with the experimental data. Moreover, the complicated non-trivial deviations, either positive (slower than SE) or negative (faster than SE), are systematically rationalized. The precise role of energy modifications and the microviscosity effect on diffusion, in particular on rotational diffusion, are clearly unraveled.

Influence of crowding and surfaces on protein amyloidogenesis: A thermo-kinetic perspective

The last few decades have irreversibly implicated protein self-assembly and aggregation leading to amyloid fibril formation in proteopathies that include several neurodegenerative diseases. Emerging studies recognize the importance of eliciting the pathways leading to protein aggregation in the context of the crowded intracellular environment rather than in conventional in vitro conditions. It is found that crowded environments can have acceleratory as well as inhibitory effects on protein aggregation, depending on the interplay of underlying factors on the crucial rate limiting steps. The aggregation mechanism and transient species formed along the pathway are further altered when they interface with natural and artificial surfaces in the cellular milieu. An increasing number of studies probe the autocatalytic nature of amyloid surfaces as well as membrane bilayer effects on amyloidogenesis. Moreover, exposure to modern nanosurfaces via nanomedicines and other sources potentially invokes beneficial or deleterious biological response that needs rigorous investigation. Mounting evidences indicate that nanoparticles can either promote or impede amyloid aggregation, spurring efforts to tune their interactions for developing effective anti-amyloid strategies. Mechanistic insights into nanoparticle mediated aggregation pathways are therefore crucial for engineering anti-amyloid nanoparticle strategies that are biocompatible and sustainable. This review is a compilation of studies that contribute to the current understanding of the altering effects of molecular crowding as well as natural and artificial surfaces on protein amyloidogenesis.

Thermodynamic phase diagram of amyloid-β (16-22) peptide

The aggregation of monomeric amyloid β protein (Aβ) peptide into oligomers and amyloid fibrils in the mammalian brain is associated with Alzheimer's disease. Insight into the thermodynamic stability of the Aβ peptide in different polymeric states is fundamental to defining and predicting the aggregation process. Experimental determination of Aβ thermodynamic behavior is challenging due to the transient nature of Aβ oligomers and the low peptide solubility. Furthermore, quantitative calculation of a thermodynamic phase diagram for a specific peptide requires extremely long computational times. Here, using a coarse-grained protein model, molecular dynamics (MD) simulations are performed to determine an equilibrium concentration and temperature phase diagram for the amyloidogenic peptide fragment Aβ_16-22 Our results reveal that the only thermodynamically stable phases are the solution phase and the macroscopic fibrillar phase, and that there also exists a hierarchy of metastable phases. The boundary line between the solution phase and fibril phase is found by calculating the temperature-dependent solubility of a macroscopic Aβ_16-22 fibril consisting of an infinite number of β-sheet layers. This in silico determination of an equilibrium (solubility) phase diagram for a real amyloid-forming peptide, Aβ_16-22, over the temperature range of 277-330 K agrees well with fibrillation experiments and transmission electron microscopy (TEM) measurements of the fibril morphologies formed. This in silico approach of predicting peptide solubility is also potentially useful for optimizing biopharmaceutical production and manufacturing nanofiber scaffolds for tissue engineering.

Crowding Effects on Energy-Transfer Efficiencies of Hetero-FRET Probes As Measured Using Time-Resolved Fluorescence Anisotropy

Macromolecular crowding is prevalent in all living cells due to the presence of large biomolecules and organelles. Cellular crowding is heterogeneous and is known to influence biomolecular transport, biochemical reactions, and protein folding. Emerging evidence suggests that some cell pathologies may be correlated with compartmentalized crowding. As a result, there is a need for robust biosensors that are sensitive to crowding as well as quantitative, noninvasive fluorescence methods that are compatible with living cells studies. Here, we have developed a model that describes the rotational dynamics of hetero-Förster resonance energy transfer (FRET) biosensors as a means to determine the energy-transfer efficiency and donor-acceptor distance. The model was tested on wavelength-dependent time-resolved fluorescence anisotropy of hetero-FRET probes (mCerulean3-linker-mCitrine) with variable linkers in both crowded (Ficoll-70) and viscous (glycerol) solutions at room temperature. Our results indicate that the energy-transfer efficiencies of these FRET probes increase as the linker becomes shorter and more flexible in pure buffer at room temperature. In addition, the FRET probes favor compact structures with enhanced energy-transfer efficiencies and a shorter donor-acceptor distance in the heterogeneous, polymer-crowded environment due to steric hindrance. In contrast, the extended conformation of these FRET probes is more favorable in viscous, homogeneous environments with a reduced energy-transfer efficiency compared to those in pure buffer, which we attribute to reduced structural fluctuations of the mCerulean3-mCitrine FRET pair in the glycerol-enriched buffer. Our results represent an important step toward the application of quantitative and noninvasive time-resolved fluorescence anisotropy of hetero-FRET probes to investigate compartmentalized macromolecular crowding and protein-protein interactions in living cells as well as in controlled environments.

On the Applicability of Force Fields To Study the Aggregation of Amyloidogenic Peptides Using Molecular Dynamics Simulations

Molecular dynamics simulations play an essential role in understanding biomolecular processes such as protein aggregation at temporal and spatial resolutions which are not attainable by experimental methods. For a correct modeling of protein aggregation, force fields must accurately represent molecular interactions. Here, we study the effect of five different force fields on the oligomer formation of Alzheimer's Aβ_16-22 peptide and two of its mutants: Aβ_16-22(F19V,F20V), which does not form fibrils, and Aβ_16-22(F19L) which forms fibrils faster than the wild type. We observe that while oligomer formation kinetics depends strongly on the force field, structural properties, such as the most relevant protein-protein contacts, are similar between them. The oligomer formation kinetics obtained with different force fields differ more from each other than the kinetics between aggregating and nonaggregating peptides simulated with a single force field. We discuss the difficulties in comparing atomistic simulations of amyloid oligomer formation with experimental observables.

Seeding and cross-seeding fibrillation of N-terminal prion protein peptides PrP(120-144)

Prion diseases are infectious neurodegenerative diseases that are capable of cross-species transmission, thus arousing public health concerns. Seed-templating propagation of prion protein is believed to underlie prion cross-species transmission pathology. Understanding the molecular fundamentals of prion propagation is key to unravelling the pathology of prion diseases. In this study, we use coarse-grained molecular dynamics to investigate the seeding and cross-seeding aggregation of three prion protein fragments PrP(120-144) originating from human (Hu), bank vole (BV), and Syrian hamster (SHa). We find that the seed accelerates the aggregation of the monomer peptides by eliminating the lag phase. The monomer aggregation kinetics are mainly determined by the structure of the seed. The stronger the hydrophobic residues on the seed associate with each other, the higher the probability that the seed recruits monomer peptides to its surface/interface. For cross-seeding aggregation, we show that Hu has a strong tendency to adopt the conformation of the BV seed and vice versa; the Hu and BV monomers have a weak tendency to adopt the conformation of the SHa seed. These two findings are consistent with Apostol et al.'s experimental findings on PrP(138-143) and partially consistent with Jones et al.'s finding on PrP(23-144). We also identify several conformational mismatches when SHa cross-seeds BV and Hu peptides, indicating the existence of a cross-seeding barrier between SHa and the other two sequences. This study sheds light on the molecular mechanism of seed-templating aggregation of prion protein fragments underlying the sequence-dependent transmission barrier in prion diseases.

How accurate are your simulations? Effects of confined aqueous volume and AMBER FF99SB and CHARMM22/CMAP force field parameters on structural ensembles of intrinsically disordered proteins: Amyloid-β42 in water

Amyloid-β₄₂ (Aβ₄₂) is an intrinsically disordered peptide intimately related to the pathogenesis of several neurodegenerative diseases. Molecular dynamics (MD) simulations are extensively utilized in the characterization of the structures and conformational dynamics of intrinsically disordered proteins (IDPs) including Aβ₄₂, with AMBER and CHARMM parameters being commonly used in these studies. Recently, comparison of the effects of force field parameters on the Aβ₄₂ structures has started to gain significant attention. In this study, the structures of Aβ₄₂ are simulated using AMBER FF99SB and CHARMM22/CMAP parameters via replica exchange MD simulations utilizing a widely used clustering algorithm. These analyses show that the structural properties (extent and positioning of the elements of secondary and tertiary structure), radius of gyration values, number and position of salt bridges are extremely dependent on the chosen force field parameters notably with the usage of clustering algorithms. For example, predicted secondary structure elements, which are of the great importance for better understanding of the molecular mechanisms of neurodegenerative diseases, deviate enormously in models generated using currently available force field parameters for proteins. Based on the derived models, chemical shift values are calculated and compared to the experimentally determined data. This comparison revealed that although both force field parameters yield results in agreement with experiments, the obtained structural properties were rather different using a clustering algorithm. In other words, these results show that the predicted structures depend heavily on the force field parameters. Importantly, since none of the force field parameters currently utilized in MD studies were developed specifically taking into account the disordered nature of IDPs, these findings clearly indicate that new force field parameters have to be developed for IDPs considering their rapid flexibility and dynamics with high amplitude. Furthermore, molecular simulations of IDPs are typically conducted using one water volume. We show that the confined aqueous volume impacts the predicted structural properties of Aβ₄₂ in water. Although up to date, confined aqueous volume effects have been ignored in the MD simulations of IDPs in water, our data indicate that these effects have to be taken into account in predicting the structural and thermodynamic properties of disordered proteins in solution.

Protein Composition Determines the Effect of Crowding on the Properties of Disordered Proteins

Unlike dilute experimental conditions under which biological molecules are typically characterized, the cell interior is crowded by macromolecules, which affects both the thermodynamics and kinetics of in vivo processes. Although the excluded-volume effects of macromolecular crowding are expected to cause compaction of unfolded and disordered proteins, the extent of this effect is uncertain. We use a coarse-grained model to represent proteins with varying sequence content and directly observe changes in chain dimensions in the presence of purely repulsive spherical crowders. We find that the extent of crowding-induced compaction is dependent not only on crowder size and concentration, but also on the properties of the protein itself. In fact, we observe a nonmonotonic trend between the dimensions of the polypeptide chain in bulk and the degree of compaction: the most extended chains experience up to 24% compaction, the most compact chains show virtually no change, and intermediate chains compress by up to 40% in size at a 40% crowder volume fraction. Free-volume theory combined with an impenetrable ellipsoidal representation of the chains predicts the crowding effects only for collapsed protein chains. An additional scaling factor, which can be easily computed from protein-crowder potential of mean force, corrects for the penetrability of extended chains and is sufficient to capture the observed nonmonotonic trend in compaction.

Influence of Hyperglycemic Conditions on Self-Association of the Alzheimer's Amyloid β (Aβ1-42) Peptide

Clinical studies have identified a correlation between type-2 diabetes mellitus and cognitive decrements en route to the onset of Alzheimer's disease (AD). Recent studies have established that post-translational modifications of the amyloid β (Aβ) peptide occur under hyperglycemic conditions; particularly, the process of glycation exacerbates its neurotoxicity and accelerates AD progression. In view of the assertion that macromolecular crowding has an altering effect on protein self-assembly, it is crucial to characterize the effects of hyperglycemic conditions via crowding on Aβ self-assembly. Toward this purpose, fully atomistic molecular dynamics simulations were performed to study the effects of glucose crowding on Aβ dimerization, which is the smallest known neurotoxic species. The dimers formed in the glucose-crowded environment were found to have weaker associations as compared to that of those formed in water. Binding free energy calculations show that the reduced binding strength of the dimers can be mainly attributed to the overall weakening of the dispersion interactions correlated with substantial loss of interpeptide contacts in the hydrophobic patches of the Aβ units. Analysis to discern the differential solvation pattern in the glucose-crowded and pure water systems revealed that glucose molecules cluster around the protein, at a distance of 5-7 Å, which traps the water molecules in close association with the protein surface. This preferential exclusion of glucose molecules and resulting hydration of the Aβ peptides has a screening effect on the hydrophobic interactions, which in turn diminishes the binding strength of the resulting dimers. Our results imply that physical effects attributed to crowded hyperglycemic environments are incapable of solely promoting Aβ self-assembly, indicating that further mechanistic studies are required to provide insights into the self-assembly of post-translationally modified Aβ peptides, known to possess aggravated toxicity, under these conditions.

Hydrodynamic effects on β-amyloid (16-22) peptide aggregation

Computer simulations based on simplified representations are routinely used to explore the early steps of amyloid aggregation. However, when protein models with implicit solvent are employed, these simulations miss the effect of solvent induced correlations on the aggregation kinetics and lifetimes of metastable states. In this work, we apply the multi-scale Lattice Boltzmann Molecular Dynamics technique (LBMD) to investigate the initial aggregation phases of the amyloid Aβ16-22 peptide. LBMD includes naturally hydrodynamic interactions (HIs) via a kinetic on-lattice representation of the fluid kinetics. The peptides are represented by the flexible OPEP coarse-grained force field. First, we have tuned the essential parameters that control the coupling between the molecular and fluid evolutions in order to reproduce the experimental diffusivity of elementary species. The method is then deployed to investigate the effect of HIs on the aggregation of 100 and 1000 Aβ16-22 peptides. We show that HIs clearly impact the aggregation process and the fluctuations of the oligomer sizes by favouring the fusion and exchange dynamics of oligomers between aggregates. HIs also guide the growth of the leading largest cluster. For the 100 Aβ16-22 peptide system, the simulation of ∼300 ns allowed us to observe the transition from ellipsoidal assemblies to an elongated and slightly twisted aggregate involving almost the totality of the peptides. For the 1000 Aβ16-22 peptides, a system of unprecedented size at quasi-atomistic resolution, we were able to explore a branched disordered fibril-like structure that has never been described by other computer simulations, but has been observed experimentally.

Simulations of disordered proteins and systems with conformational heterogeneity

Intrinsically disordered proteins (IDPs) and protein regions can facilitate a wide variety of complex physiological processes such as binding, signaling, and formation of membraneless organelles. They can however also play pathological roles by aggregating into cytotoxic oligomers and fibrils. Characterizing the structure and function of disordered proteins is an onerous task, primarily because these proteins adopt transient structures, which are difficult to capture in experiments. Simulations have emerged as a powerful tool for interpreting and augmenting experimental measurements of IDPs. In this review we focus on computer simulations of disordered protein structures, functions, assemblies, and emerging questions that, taken together, give an overview of the field as it exists today.

Multiscale simulation of molecular processes in cellular environments

We describe the recent advances in studying biological systems via multiscale simulations. Our scheme is based on a coarse-grained representation of the macromolecules and a mesoscopic description of the solvent. The dual technique handles particles, the aqueous solvent and their mutual exchange of forces resulting in a stable and accurate methodology allowing biosystems of unprecedented size to be simulated.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.

Protein Aggregation and Molecular Crowding: Perspectives From Multiscale Simulations

Cells are extremely crowded environments, thus the use of diluted salted aqueous solutions containing a single protein is too simplistic to mimic the real situation. Macromolecular crowding might affect protein structure, folding, shape, conformational stability, binding of small molecules, enzymatic activity, interactions with cognate biomolecules, and pathological aggregation. The latter phenomenon typically leads to the formation of amyloid fibrils that are linked to several lethal neurodegenerative diseases, but that can also play a functional role in certain organisms. The majority of molecular simulations performed before the last few years were conducted in diluted solutions and were restricted both in the timescales and in the system dimensions by the available computational resources. In recent years, several computational solutions were developed to get close to physiological conditions. In this review we summarize the main computational techniques used to tackle the issue of protein aggregation both in a diluted and in a crowded environment.

Protein folding, binding, and droplet formation in cell-like conditions

The many bystander macromolecules in the crowded cellular environments present both steric repulsion and weak attraction to proteins undergoing folding or binding and hence impact the thermodynamic and kinetic properties of these processes. The weak but nonrandom binding with bystander macromolecules may facilitate subcellular localization and biological function. Weak binding also leads to the emergence of a protein-rich droplet phase, which has been implicated in regulating a variety of cellular functions. All these important problems can now be addressed by realistic modeling of intermolecular interactions. Configurational sampling of concentrated protein solutions is an ongoing challenge.

Assembly of Triblock Amphiphilic Peptides into One-Dimensional Aggregates and Network Formation

Peptide assembly plays a key role in both neurological diseases and development of novel biomaterials with well-defined nanostructures. Synthetic model peptides provide a unique platform to explore the role of intermolecular interactions in the assembly process. A triblock peptide architecture designed by the Hartgerink group is a versatile system which relies on Coulomb interactions, hydrogen bonding, and hydrophobicity to guide these peptides' assembly at three different length scales: β-sheets, double-wall ribbon-like aggregates, and finally a highly porous network structure which can support gels with ≤1% by weight peptide concentration. In this study, by using molecular dynamics simulations of a structure based implicit solvent coarse grained model, we analyzed this hierarchical assembly process. Parametrization of our CG model is based on multiple-state points from atomistic simulations, which enables this model to represent the conformational adaptability of the triblock peptide molecule based on the surrounding medium. Our results indicate that emergence of the double-wall β-sheet packing mechanism, proposed in light of the experimental evidence, strongly depends on the subtle balance of the intermolecular forces. We demonstrate that, even though backbone hydrogen bonding dominates the early nucleation stages, depending on the strength of the hydrophobic and Coulomb forces, alternative structures such as zero-dimensional aggregates with two β-sheets oriented orthogonally (which we refer to as a cross-packed structure) and β-sheets with misoriented hydrophobic side chains are also feasible. We discuss the implications of these competing structures for the three different length scales of assembly by systematically investigating the influence of density, counterion valency, and hydrophobicity.

N-terminal Prion Protein Peptides (PrP(120-144)) Form Parallel In-register β-Sheets via Multiple Nucleation-dependent Pathways

The prion diseases are a family of fatal neurodegenerative diseases associated with the misfolding and accumulation of normal prion protein (PrP^C) into its pathogenic scrapie form (PrP^Sc). Understanding the fundamentals of prion protein aggregation and the molecular architecture of PrP^Sc is key to unraveling the pathology of prion diseases. Our work investigates the early-stage aggregation of three prion protein peptides, corresponding to residues 120-144 of human (Hu), bank vole (BV), and Syrian hamster (SHa) prion protein, from disordered monomers to β-sheet-rich fibrillar structures. Using 12 μs discontinuous molecular dynamics simulations combined with the PRIME20 force field, we find that the Hu-, BV-, and SHaPrP(120-144) aggregate via multiple nucleation-dependent pathways to form U-shaped, S-shaped, and Ω-shaped protofilaments. The S-shaped HuPrP(120-144) protofilament is similar to the amyloid core structure of HuPrP(112-141) predicted by Zweckstetter. HuPrP(120-144) has a shorter aggregation lag phase than BVPrP(120-144) followed by SHaPrP(120-144), consistent with experimental findings. Two amino acid substitutions I138M and I139M retard the formation of parallel in-register β-sheet dimers during the nucleation stage by increasing side chain-side chain association and reducing side chain interaction specificity. On average, HuPrP(120-144) aggregates contain more parallel β-sheet content than those formed by BV- and SHaPrP(120-144). Deletion of the C-terminal residues 138-144 prevents formation of fibrillar structures in agreement with the experiment. This work sheds light on the amyloid core structures underlying prion strains and how I138M, I139M, and S143N affect prion protein aggregation kinetics.

Prediction of a stable associated liquid of short amyloidogenic peptides

Amyloid fibril formation is believed to be a nucleation-controlled process. Depending on the nature of peptide sequence, fibril nucleation can occur in one step, straight from a dilute solution, or in multiple steps via oligomers or disordered aggregates. What determines this process is poorly understood. Since the fibril formation kinetics is driven by thermodynamic forces, knowledge of the phase behavior is crucial. Here, we investigated the phase behavior of three short peptide sequences of varying side-chain hydrophobicity. Replica exchange molecular dynamics simulations of a mid-resolution model indicate that the weakly hydrophobic peptide forms fibrils directly from solution, whereas the most hydrophobic peptide forms a dense liquid phase before crystallizing into ordered fibrils at low temperatures. For the medium hydrophobic peptide we found evidence of a novel additional transition to a liquid phase consisting of clusters of aligned peptides, implying a three-step nucleation process. We tested the robustness of this prediction by applying Wertheim's theory and statistical associating fluid theory to a hard-sphere model dressed with isotropic and anisotropic attractions. We found that the ratio of interaction strengths strongly affects the phase behavior, and under certain conditions indeed gives rise to a stable polymerized liquid phase. The peptide clusters in the associated liquid tend to be slow and long-lived, which may give the oligomer droplet more time to act as a toxic oligomer, before turning into a fibril.

Effects of hydrophobic macromolecular crowders on amyloid β (16-22) aggregation

In Alzheimer's disease (AD), the amyloid β (Aβ) peptide aggregates in the brain to form progressively larger oligomers, fibrils, and plaques. The aggregation process is strongly influenced by the presence of other macromolecular species, called crowders, that can exert forces on the proteins. One very common attribute of macromolecular crowders is their hydrophobicity. We examined the effect of hydrophobic crowders on protein aggregation by using discontinuous molecular dynamics (DMD) simulations in combination with an intermediate resolution protein model, PRIME20. The systems considered contained 48 Aβ (16-22) peptides and crowders with diameters of 5 Å, 20 Å, and 40 Å, represented by hard spheres or spheres with square-well/square-shoulder interactions, at a crowder volume fraction of ϕ = 0.10. Results show that low levels of crowder hydrophobicity are capable of increasing the fibrillation lag time and high levels of crowder hydrophobicity can fully prevent the formation of fibrils. The types of structures that remain during the final stages of the simulations are summarized in a global phase diagram that shows fibril, disordered oligomer, or β-sheet phases in the space spanned by crowder size and crowder hydrophobicity. In particular, at high levels of hydrophobicity, simulations with 5 Å crowders result in only disordered oligomers and simulations with 40 Å crowders result in only β-sheets. The presence of hydrophobic crowders reduces the antiparallel β-sheet content of fibrils, whereas hard sphere crowders increase it. Finally, strong hydrophobic crowders alter the secondary structure of the Aβ (16-22) monomers, bending them into a shape that is incapable of forming ordered β-sheets or fibrils. These results qualitatively agree with previous theoretical and experimental work.