Discontinuous Molecular Dynamics Simulations Research Articles

Effect of sequence pattern on conformation of DOPA-Peptide conjugate aggregates: a discontinuous molecular dynamics simulation study

ABSTRACT Underwater adhesives are critical for many applications, including marine coatings, sealants, and medical devices. Research on natural underwater adhesives has shown that L-3,4-dihydroxyphenylalanine (DOPA) and amyloid nanostructures are vital to their adhesive abilities. The fusion of DOPA-containing chains and amyloid-forming peptides creates a new space for designing underwater adhesives capable of multi-surface adhesion. One critical question for this design is the interplay between the DOPA and amyloid-forming peptide regions. Here we investigate the effect of the sequence pattern of DOPA-containing chains on the aggregation conformation of conjugates. Discontinuous molecular dynamics simulations were performed for fourteen DOPA-amyloid conjugates with different sequence patterns along the DOPA-containing portion. The amyloid-forming portion is represented by KLVFFAE from the Aβ42 peptide. The structural properties of the DOPA-amyloid conjugates are characterised by the percentages of ordered secondary structures and residue-residue contact maps. The results showed that certain patterns of DOPA and glycine in the DOPA-containing tail allowed the KLVFFAE portions of the conjugates to form distinct ordered β-sheets, and the DOPA-containing portion and the KLVFFAE portion of the conjugates to remain separated both within the same chain and amongst different chains. Among the designs, the most promising sequences are KLVFFAE-G-YYGYYGYY (where Y represents DOPA) and KLVFFAE-G-YYYYGGGG.

Graphic contrastive learning analyses of discontinuous molecular dynamics simulations: Study of protein folding upon adsorption

A comprehensive understanding of the interfacial behaviors of biomolecules holds great significance in the development of biomaterials and biosensing technologies. In this work, we used discontinuous molecular dynamics (DMD) simulations and graphic contrastive learning analysis to study the adsorption of ubiquitin protein on a graphene surface. Our high-throughput DMD simulations can explore the whole protein adsorption process including the protein structural evolution with sufficient accuracy. Contrastive learning was employed to train a protein contact map feature extractor aiming at generating contact map feature vectors. Subsequently, these features were grouped using the k-means clustering algorithm to identify the protein structural transition stages throughout the adsorption process. The machine learning analysis can illustrate the dynamics of protein structural changes, including the pathway and the rate-limiting step. Our study indicated that the protein–graphene surface hydrophobic interactions and the π–π stacking were crucial to the seven-stage adsorption process. Upon adsorption, the secondary structure and tertiary structure of ubiquitin disintegrated. The unfolding stages obtained by contrastive learning-based algorithm were not only consistent with the detailed analyses of protein structures but also provided more hidden information about the transition states and pathway of protein adsorption process and structural dynamics. Our combination of efficient DMD simulations and machine learning analysis could be a valuable approach to studying the interfacial behaviors of biomolecules.

Sequence patterns and signatures: Computational and experimental discovery of amyloid-forming peptides.

Screening amino acid sequence space via experiments to discover peptides that self-assemble into amyloid fibrils is challenging. We have developed a computational peptide assembly design (PepAD) algorithm that enables the discovery of amyloid-forming peptides. Discontinuous molecular dynamics (DMD) simulation with the PRIME20 force field combined with the FoldAmyloid tool is used to examine the fibrilization kinetics of PepAD-generated peptides. PepAD screening of ∼10,000 7-mer peptides resulted in twelve top-scoring peptides with two distinct hydration properties. Our studies revealed that eight of the twelve in silico discovered peptides spontaneously form amyloid fibrils in the DMD simulations and that all eight have at least five residues that the FoldAmyloid tool classifies as being aggregation-prone. Based on these observations, we re-examined the PepAD-generated peptides in the sequence pool returned by PepAD and extracted five sequence patterns as well as associated sequence signatures for the 7-mer amyloid-forming peptides. Experimental results from Fourier transform infrared spectroscopy (FTIR), thioflavin T (ThT) fluorescence, circular dichroism (CD), and transmission electron microscopy (TEM) indicate that all the peptides predicted to assemble in silico assemble into antiparallel β-sheet nanofibers in a concentration-dependent manner. This is the first attempt to use a computational approach to search for amyloid-forming peptides based on customized settings. Our efforts facilitate the identification of β-sheet-based self-assembling peptides, and contribute insights towards answering a fundamental scientific question: "What does it take, sequence-wise, for a peptide to self-assemble?".

Graph Clustering Analyses of Discontinuous Molecular Dynamics Simulations: Study of Lysozyme Adsorption on a Graphene Surface.

Understanding the interfacial behaviors of biomolecules is crucial to applications in biomaterials and nanoparticle-based biosensing technologies. In this work, we utilized autoencoder-based graph clustering to analyze discontinuous molecular dynamics (DMD) simulations of lysozyme adsorption on a graphene surface. Our high-throughput DMD simulations integrated with a Go̅-like protein-surface interaction model makes it possible to explore protein adsorption at a large temporal scale with sufficient accuracy. The graph autoencoder extracts a low-dimensional feature vector from a contact map. The sequence of the extracted feature vectors is then clustered, and thus the evolution of the protein molecule structure in the absorption process is segmented into stages. Our study demonstrated that the residue-surface hydrophobic interactions and the π-π stacking interactions play key roles in the five-stage adsorption. Upon adsorption, the tertiary structure of lysozyme collapsed, and the secondary structure was also affected. The folding stages obtained by autoencoder-based graph clustering were consistent with detailed analyses of the protein structure. The combination of machine learning analysis and efficient DMD simulations developed in this work could be an important tool to study biomolecules' interfacial behaviors.

Discontinuous Molecular Dynamics Simulations of Biomolecule Interfacial Behavior: Study of Ovispirin-1 Adsorption on a Graphene Surface.

Fundamental understanding of biomolecular interfacial behavior, such as protein adsorption at the microscopic scale, is critical to broad applications in biomaterials, nanomedicine, and nanoparticle-based biosensing techniques. The goal of achieving both computational efficiency and accuracy presents a major challenge for simulation studies at both atomistic and molecular scales. In this work, we developed a unique, accurate, high-throughput simulation method which, by integrating discontinuous molecular dynamics (DMD) simulations with the Go-like protein-surface interaction model, not only solves the dynamics efficiently, but also describes precisely the protein intramolecular and intermolecular interactions at the atomistic scale and the protein-surface interactions at the coarse-grained scale. Using our simulation method and in-house developed software, we performed a systematic study of α-helical ovispirin-1 peptide adsorption on a graphene surface, and our study focused on the effect of surface hydrophobic interactions and π-π stacking on protein adsorption. Our DMD simulations were consistent with full-atom molecular dynamics simulations and showed that a single ovispirin-1 peptide lay down on the flat graphene surface with randomized secondary structure due to strong protein-surface interactions. Peptide aggregates were formed with an internal hydrophobic core driven by strong interactions of hydrophobic residues in the bulk environment. However, upon adsorption, the hydrophobic graphene surface can break the hydrophobic core by denaturing individual peptide structures, leading to disassembling the aggregate structure and further randomizing the ovispirin-1 peptide's secondary structures.

Insight into the Mechanism of Internalization of the Cell-Penetrating Carrier Peptide Pep-1 by Conformational Analysis.

Different secondary structures of the pep-1 protein were blamed for transmembrane internalization process of drugs and drug deliveries. But which structure will be important for transmembrane delivery was still not clear. In this study, interactions between pep-1 and cell membranes were studied. Pep-1 in the buffer (Pep-1) and pep-1 on graphene (PDS/G) or they on graphene oxide (PDS/GO) were composed as the transmembrane delivery system to study the different secondary structure of pep-1 that influence for their transmembrane delivery. The curves of chirascan circular dichroism (CD) and all-atom discontinuous molecular dynamics (DMD) simulations illuminate that, in a buffer environment, most pep-1 formed 3-10 helix structures. Meanwhile, when Pep-1 composed graphene slice and formed PDS/G, 3-10 helix and alpha-helix structures can be found in small quantities. When they on graphene oxide and formed PDS/GO, coil or type II beta-turn structure can be found from most of the pep-1 and 3-10 helix structure disappeared. By using sum-frequency generation (SFG) vibrational spectroscopy, we found that pep-1 with 3-10 helix structures in buffer solutions damaged the lipid bilayer violently. PDS/G with less 3-10 helix structures will change the orientation of lipid bilayer effectively but slightly. Pep-1 with coil or type II Beta-turn in PDS/GO cannot influence the structure of lipid bilayers. Hemolysis experiments also proved that when pep-1 composed as PDS/G, they will change the orientation of the plasma membrane of red blood cells effectively but slightly. When they attach on the GO and formed PDS/GO, the plasma membrane of red blood cells cannot be influenced. In conclusion, 3-10 helix structures will be positively correlated with disturbance of membranes. These results will be effectively guided the clinic application of pep-1 as a transporter of the drug delivery system.

Development of a coarse-grained lipid model, LIME 2.0, for DSPE using multistate iterative Boltzmann inversion and discontinuous molecular dynamics simulations

We suggest an improved version of the intermediate resolution implicit solvent model for lipids, LIME, that was previously developed for use with discontinuous molecular dynamics (DMD) simulations. LIME gets its geometrical and energy parameters between bonded and nonbonded pairs of coarse-grained (CG) sites from atomistic simulations. The improved model, LIME 2.0, uses multiple square wells rather than the single square well used in original LIME to obtain intermolecular interactions that more faithfully mimic those from atomistic simulations. The multi-state iterative Boltzmann inversion (MS-IBI) scheme is used to determine the interaction parameters. This means that a single set of interaction parameters between coarse-grained sites can be used to represent the lipid bilayers at different temperatures. The physical properties of CG DSPE lipid bilayer are calculated using CG simulations and compared to atomistic simulations results to verify the improved model. The phase transition temperature of the lipid bilayer is measured accurately and the lipid translocation phenomenon, “flip-flop” is observed through CG simulation. These results suggest that CG parameterization using multiple square-wells and the MS-IBI scheme is well suited to the study of lipid bilayers across a range of temperatures with DMD simulations.

Anatomy of a selectively coassembled β-sheet peptide nanofiber

Peptide self-assembly, wherein molecule A associates with other A molecules to form fibrillar β-sheet structures, is common in nature and widely used to fabricate synthetic biomaterials. Selective coassembly of peptide pairs A and B with complementary partial charges is gaining interest due to its potential for expanding the form and function of biomaterials that can be realized. It has been hypothesized that charge-complementary peptides organize into alternating ABAB-type arrangements within assembled β-sheets, but no direct molecular-level evidence exists to support this interpretation. We report a computational and experimental approach to characterize molecular-level organization of the established peptide pair, CATCH. Discontinuous molecular dynamics simulations predict that CATCH(+) and CATCH(-) peptides coassemble but do not self-assemble. Two-layer β-sheet amyloid structures predominate, but off-pathway β-barrel oligomers are also predicted. At low concentration, transmission electron microscopy and dynamic light scattering identified nonfibrillar ∼20-nm oligomers, while at high concentrations elongated fibers predominated. Thioflavin T fluorimetry estimates rapid and near-stoichiometric coassembly of CATCH(+) and CATCH(-) at concentrations ≥100 μM. Natural abundance 13C NMR and isotope-edited Fourier transform infrared spectroscopy indicate that CATCH(+) and CATCH(-) coassemble into two-component nanofibers instead of self-sorting. However, 13C-13C dipolar recoupling solid-state NMR measurements also identify nonnegligible AA and BB interactions among a majority of AB pairs. Collectively, these results demonstrate that strictly alternating arrangements of β-strands predominate in coassembled CATCH structures, but deviations from perfect alternation occur. Off-pathway β-barrel oligomers are also suggested to occur in coassembled β-strand peptide systems.

SDMD: An open source program for discontinuous molecular dynamics simulation of protein folding and aggregation

Discontinuous molecular dynamics (DMD) is an extremely fast alternative to the conventional molecular dynamics that uses continuous force fields. It simulates the force field applied to particles by discontinuous steplike functions of inter-particle distance. Thus, particles move at constant velocities until their distance is equal to the point at which there is a discontinuity, at which time the simulator calculates the interactions by solving simultaneously the equations governing conservation of momentum and energy. In this way, longer-time simulations can be carried out. Here, we introduce sDMD, an open source simulation package based on DMD technique coupled with a high-resolution all-atom molecular model, and describe the model of proteins, the algorithms for approximating the interactions, and the general design principles used in the simulator. We also demonstrate the implementation of the package, as well as two illustrative examples. Program summaryProgram title: sDMDProgram files doi:http://dx.doi.org/10.17632/h6b8hphw3n.1Licensing provisions: MIT LicenseProgramming language: C/C++Nature of problem: Molecular dynamics simulations of large protein/peptide systems for long time scales with high resolution.Solution method: sDMD is implemented based on discontinuous molecular dynamics, a fast alternative to the conventional molecular dynamics, which is able to perform ab initio simulations of protein/peptide folding and aggregation.Additional comments including restrictions and unusual features: OpenGL is required to enable the instant visualization feature.

Molecular dynamics study of structure, folding, and aggregation of poly-glycine-alanine (Poly-GA).

Poly-glycine-alanine (poly-GA) proteins are widely believed to be one of the main toxic dipeptide repeat molecules associated with amyotrophic lateral sclerosis (ALS) and frontotemporal dementia diseases. Using discontinuous molecular dynamics simulation and an all-atom model of the proteins, we study folding, stability, and aggregation of poly-GA. The results demonstrate that poly-GA is an aggregation-prone protein that, after a long enough time, forms β-sheet-rich aggregates that match recent experiment data and that two unique helical structures are formed very frequently, namely, β-helix and double-helix. The details of the two structures are analyzed. The analysis indicates that such helical structures are stable and share the characteristics of both α-helices and β-sheets. Molecular simulations indicate that identical phenomena also occur in the aggregation of poly-glycine-arginine (poly-GR). Therefore, we hypothesize that proteins of type (GX)n in which X may be any non-glycine amino acid and n is the repeat length may share the same folding structures of β-helix and double-helix and that it is the glycine in the repeat that contributes the most to this characteristic. Molecular dynamics simulation with continuous interaction potentials and explicit water molecules as the solvent supports the hypothesis. To our knowledge, this is the first molecular dynamics simulation of the phenomena involving poly-GA and poly-GR proteins.

Computational Study of DNA-Cross-Linked Hydrogel Formation for Drug Delivery Applications

We present the results of discontinuous molecular dynamics (DMD) simulations aimed at understanding the formation of DNA-mediated hydrogels and assessing their drug loading ability. Poly(ethylene glycol) (PEG) precursors of four and six arms that are covalently functionalized on all ends with oligonucleotides are cross-linked by a single oligonucleotide whose sequence is complementary to the oligonucleotide conjugated to the precursor. We show that the precursors with large molecular weight and many arms are advantageous in forming a three-dimensional percolated network. Analysis of the percolated networks shows that the pore diameter distribution becomes narrower as the precursor concentration, the number of arms, and the molecular weight increase. The pore throat diameter, the size of the largest molecule that can travel through the hydrogel networks without being trapped, is determined. The percolated network slows the movement of molecules inside the pores. Molecules larger than the pore throat diameter have more restrictions on their movement in the percolated network than those with smaller sizes.

Continuous version of a square-well potential of variable range and its application in molecular dynamics simulations

ABSTRACTIn this work, we present a simple mathematical expression for a continuous version of the square-well (SW) discontinuous potential of variable range (). This expression can be useful in theoretical statistical mechanics methods and specially in conventional molecular dynamics (MD) simulations. To illustrate the latter point, the continuous version of some SW potentials of variable range were selected and studied with continuous MD. SW single state thermodynamic and structural properties (vapour, liquid and solid), vapour–liquid phase diagrams and surface tensions accurately reproduce available simulation data obtained by Monte Carlo and discontinuous MD simulation methods. This expression can be easily implemented in popular simulation packages (GROMACS, NAMD, CHARMM, DLPOLY, EXPResSo, HOOMD, TINKER, ls1 mardyn, etc.) that can be useful to study more complex systems. Besides we also present a continuous version for the square-shoulder potential.

Development of a simple coarse-grained DNA model for analysis of oligonucleotide complex formation

In this paper, we develop a coarse-grained nucleotide model for the purpose of simulating large-scale aptamer-based hydrogel network formation in future research. In the model, each nucleotide is represented by a single interaction site containing sugar, phosphate and base. Discontinuous molecular dynamics (DMD) simulations are performed to simulate formation and denaturation of oligonucleotide duplexes as a function of temperature. The simulated melting temperatures of oligonucleotide duplexes are calculated in simulations of systems with different sequences, lengths and concentrations of oligonucleotides, and compared to data from the OligoAnalyzer tool. The denaturation of oligonucleotide triplexes containing a hybridised structure of three different oligonucleotides is analysed using both simulations and experiments. The nucleotide model is found to be a good predictor of the oligonucleotide’s hybridised state for both duplexes and triplexes. This coarse-grained model has wide ranging applications in the development or optimisation of DNA-based technologies including DNA origami, DNA-enabled hydrogels and DNA-based biosensors.

Simulations and Experiments Delineate Amyloid Fibrilization by Peptides Derived from Glaucoma-Associated Myocilin.

Mutant myocilin aggregation is associated with inherited open angle glaucoma, a prevalent optic neuropathy leading to blindness. Comprehension of mutant myocilin aggregation is of fundamental importance to glaucoma pathogenesis and ties glaucoma to amyloid diseases such as Alzheimer's. Here, we probe the aggregation properties of peptides derived from the myocilin olfactomedin domain. Peptides P1 (residues 326-337) and P3 (residues 426-442) were identified previously to form amyloids. Coarse-grained discontinuous molecular dynamics simulations using the PRIME20 force field (DMD/PRIME20) predict that P1 and P3 are aggregation-prone; P1 consistently forms fibrillar aggregates with parallel in-register β-sheets, whereas P3 forms β-sheet-containing aggregates without distinct order. Natural abundance 13C solid-state NMR spectra validate that aggregated P1 exhibits amyloid signatures and is more homogeneous than aggregated P3. DMD/PRIME20 simulations provide a viable method to predict peptide aggregation propensities and aggregate structure/order which cannot be accessed by bioinformatics or readily attained experimentally.

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.

Fibrillation of A-Beta Peptides in Presence of Phenolic Inhibitors: Coarse-Grained Simulations

Alzheimer's Disease (AD) is a neurodegenerative disease that causes dementia, nervous system degradation, and death. Currently there are no therapeutic agents available for the treatment of AD despite great efforts by the research community. Many small phenolic compounds have been shown in experiment to be effective at preventing the formation of Aβ fibrils. In this work we use discontinuous molecular dynamics (DMD) simulations to learn how four naturally-occurring phenolic compounds, resveratrol, vanillin, curcumin, and epigallocatechin-3-gallate (EGCG), bind to Aβ(17-36) monomers and affect oligomerization and fibrillation. We use a coarse-grained model/force field for inhibitors which has geometric and energetic parameters that are compatible with the coarse-grained protein model PRIME20. Preliminary results show that the U-shaped protofibril structure formed by Aβ(17-36) is similar to the corresponding part of the Aβ(1-42) fibril model, based on solid state NMR data. The order of peak heights in the peptide-inhibitor radial distribution function shows that the strength of the inhibitor binding affinity is resveratrol > curcumin and EGCG > vanillin. Simulations of 8 Aβ(17-36) peptides aggregating in the presence of 30 inhibitors show that EGCG, resveratrol and curcumin inhibit Aβ(17-36) fibril formation while vanillin only retards the lag phase. Instead of forming an ordered β sheet structure (as occurs in the absence of inhibitors), the peptides remain random coils and form complexes with the inhibitors, binding mainly to the hydrophobic residues near the peptide termini. The relative ability to inhibit Aβ(17-36) fibrillation is EGCG > resveratrol > curcumin > vanillin, consistent with experimental findings on full length Aβ(1-42) aggregation. Our simulations provide molecule-level insights into the mechanisms by which small molecules inhibit Aβ aggregation.

Aggregation of amphipathic peptides at an aqueous–organic interface using coarse-grained simulations

The effect of an aqueous/organic interface on the folding and aggregation of amphipathic peptides is examined by applying discontinuous molecular dynamics (DMD) simulations combined with an intermediate resolution protein model, PRIME20, to a peptide/interface system. The systems contain 48 (KLLK)4 peptides in random coil or α-helical conformations interacting with both strong and weak interfaces. In the absence of an interface, most of the oligomers form helical bundles, a small fraction of which convert to β-sheets when the temperature is above the folding transition. Adding a weak interface decreases oligomer formation above the folding temperature and increases it below. Little monolayer formation is observed at the weak interface; instead reversible adsorption increases the local peptide concentration near the interface, promoting helical bundle formation in the aqueous phase below the folding temperature and β-sheet formation above the folding temperature. Introducing a strong interface leads to irreversible adsorption, promoting formation of helical monolayers below the folding temperature and mixed β-sheet/amorphous monolayers above the folding temperature. The (KLLK)4 peptide is more likely to adsorb to the interface when it is in an α-helical conformation, as opposed to a random coil, because of its larger hydrophobic moment.

Nanoparticle-induced assembly of hydrophobically modified chitosan

Hydrophobically modified chitosan (HMC) self-assembles in solution to form gels, making it suitable for applications in oil dispersion, hydrogel design and wound dressing. The self-assembly of HMC is driven by the association of hydrophobic moieties that are attached to chitosan monomers along the polymer chain. We present the results of discontinuous molecular dynamics simulations aimed at understanding how the length and density of the hydrophobic modification chains attached to HMC affect self-assembly and the structure of the resulting network. Long modification chains are required to promote the formation of a stable network in solution at a modification density of 5%; the networks form more readily at a modification density of 10%. The pore size distribution of the resulting HMC network is relatively independent of the modification chain length and density. Insertion of different sized hydrophobic nanoparticles into HMC has a significant impact on network formation, with the particles acting as junction points that promote the association of several HMC chains. The networks form faster in the presence of many small nanoparticles than in the presence of few large nanoparticles. We conclude that HMC could be a viable candidate to form hydrogels in solution.

Amyloid Beta Aggregation in the Presence of Naturally-Derived Inhibitors

Alzheimer's Disease (AD) is a neurodegenerative disease that causes dementia, nervous system degradation, and death. Currently there are no therapeutic agents available for the treatment of AD despite great efforts by the research community. Many small phenolic compounds have been shown in experiment to be effective at preventing the formation of Aβ fibrils. In this work we use discontinuous molecular dynamics (DMD) simulations to learn how four naturally-occurring phenolic compounds, resveratrol, vanillin, curcumin, and epigallocatechin-3-gallate (EGCG), bind to Aβ(17-36) monomers and affect oligomerization and fibrillation. We use a coarse-grained model/force field for inhibitors which has geometric and energetic parameters that are compatible with the coarse-grained protein model PRIME20. Preliminary results show that the U-shaped protofibril structure formed by Aβ(17-36) is similar to the corresponding part of the Aβ(1-42) fibril model, based on solid state NMR data. The order of peak heights in the peptide-inhibitor radial distribution function shows that the strength of the inhibitor binding affinity is resveratrol > curcumin and EGCG > vanillin. Simulations of 8 Aβ(17-36) peptides aggregating in the presence of 30 inhibitors show that EGCG, resveratrol and curcumin inhibit Aβ(17-36) fibril formation while vanillin only retards the lag phase. Instead of forming an ordered β sheet structure (as occurs in the absence of inhibitors), the peptides remain random coils and form complexes with the inhibitors, binding mainly to the hydrophobic residues near the peptide termini. The relative ability to inhibit Aβ(17-36) fibrillation is EGCG > resveratrol > curcumin > vanillin, consistent with experimental findings on full length Aβ(1-42) aggregation. Our simulations provide molecule-level insights into the mechanisms by which small molecules inhibit Aβ aggregation.

Polymorphism of fibrillar structures depending on the size of assembled Aβ17-42 peptides.

The size of assembled Aβ17-42 peptides can determine polymorphism during oligomerization and fibrillization, but the mechanism of this effect is unknown. Starting from separate random monomers, various fibrillar oligomers with distinct structural characteristics were identified using discontinuous molecular dynamics simulations based on a coarse-grained protein model. From the structures observed in the simulations, two characteristic oligomer sizes emerged, trimer and paranuclei, which generated distinct structural patterns during fibrillization. A majority of the simulations for trimers and tetramers formed non-fibrillar oligomers, which primarily progress to off-pathway oligomers. Pentamers and hexamers were significantly converted into U-shape fibrillar structures, meaning that these oligomers, called paranuclei, might be potent on-pathway intermediates in fibril formation. Fibrillar oligomers larger than hexamers generated substantial polymorphism in which hybrid structures were readily formed and homogeneous fibrillar structures appeared infrequently.