Computer simulation study of amyloid fibril formation by palindromic sequences in prion peptides

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

Evolution of π-Peptide Self-Assembly: From Understanding to Prediction and Control

Supramolecular materials derived from the self-assembly of engineered molecules continue to garner tremendous scientific and technological interest. Recent innovations include the realization of nano- and mesoscale particles (0D), rods and fibrils (1D), sheets (2D), and even extended lattices (3D). Our research groups have focused attention over the past 15 years on one particular class of supramolecular materials derived from oligopeptides with embedded π-electron units, where the oligopeptides can be viewed as substituents or side chains to direct the assembly of the central π-electron cores. Upon assembly, the π-systems are driven into close cofacial architectures that facilitate a variety of energy migration processes within the nanomaterial volume, including exciton transport, voltage transmission, and photoinduced electron transfer. Like many practitioners of supramolecular materials science, many of our initial molecular designs were designed with substantial inspiration from biologically occurring self-assembly coupled with input from chemical intuition and molecular modeling and simulation. In this feature article, we summarize our current understanding of the π-peptide self-assembly process as documented through our body of publications in this area. We address fundamental spectroscopic and computational tools used to extract information regarding the internal structures and energetics of the π-peptide assemblies, and we address the current state of the art in terms of recent applications of data science tools in conjunction with high-throughput computational screening and experimental assays to guide the efficient traversal of the π-peptide molecular design space. The abstract image details our integrated program of chemical synthesis, spectroscopic and functional characterization, multiscale simulation, and machine learning which has advanced the understanding and control of the assembly of synthetic π-conjugated peptides into supramolecular nanostructures with energy and biomedical applications.

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.

Interactions between Curcumin Derivatives and Amyloid-β Fibrils: Insights from Molecular Dynamics Simulations

The aggregation of amyloid-β (Aβ) peptides into senile plaques is a hallmark of Alzheimer's disease (AD) and is hypothesized to be the primary cause of AD related neurodegeneration. Previous studies have shown the ability of curcumin to both inhibit the aggregation of Aβ peptides into oligomers or fibrils and reduce amyloids in vivo. Despite the promise of curcumin and its derivatives to serve as diagnostic, preventative, and potentially therapeutic AD molecules, the mechanism by which curcumin and its derivatives bind to and inhibit Aβ fibrils' formation remains elusive. Here, we investigated curcumin and a set of curcumin derivatives in complex with a hexamer peptide model of the Aβ1-42 fibril using nearly exhaustive docking, followed by multi-ns molecular dynamics simulations, to provide atomistic-detail insights into the molecules' binding and inhibitory properties. In the vast majority of the simulations, curcumin and its derivatives remain firmly bound in complex with the fibril through primarily three different principle binding modes, in which the molecules interact with residue domain 17LVFFA21, in line with previous experiments. In a small subset of these simulations, the molecules partly dissociate the outermost peptide of the Aβ1-42 fibril by disrupting β-sheets within the residue domain 12VHHQKLVFF20. A comparison between binding modes leading or not leading to partial dissociation of the outermost peptide suggests that the latter is attributed to a few subtle key structural and energetic interaction-based differences. Interestingly, partial dissociation appears to be either an outcome of high affinity interactions or a cause leading to high affinity interactions between the molecules and the fibril, which could partly serve as a compensation for the energy loss in the fibril due to partial dissociation. In conjunction with this, we suggest a potential inhibition mechanism of Αβ1-42 aggregation by the molecules, where the partially dissociated 16KLVFF20 domain of the outermost peptide could either remain unstructured or wrap around to form intramolecular interactions with the same peptide's 29GAIIG33 domain, while the molecules could additionally act as a patch against the external edge of the second outermost peptide's 16KLVFF20 domain. Thereby, individually or concurrently, these could prohibit fibril elongation.

Theoretical and computational advances in protein misfolding

Misfolded proteins escape the cellular quality control mechanism and fail to fold properly or remain correctly folded leading to a loss in their functional specificity. Thus misfolding of proteins cause a large number of very different diseases ranging from errors in metabolism to various types of complex neurodegenerative diseases. A theoretical and computational perspective of protein misfolding is presented with a special emphasis on its salient features, mechanism and consequences. These insights quantitatively analyze different determinants of misfolding, that may be applied to design disease specific molecular targets.

Easily readable palindromic sequence-defined polymers built by cascade thiol-maleimide Michael couplings

The rational combination of cascade thiol-maleimide Michael couplings (CTMMC) with iterative exponential chain growth was demonstrated as an efficient way to synthesize palindromic sequence-defined polymers.

Disordered peptide chains in an α-C-based coarse-grained model

We construct a one-bead-per-residue coarse-grained dynamical model to describe intrinsically disordered proteins at significantly longer timescales than in the all-atom models. In this model, inter-residue contacts form and disappear during the course of the time evolution. The contacts may arise between the sidechains, the backbones or the sidechains and backbones of the interacting residues. The model yields results that are consistent with many all-atom and experimental data on these systems. We demonstrate that the geometrical properties of various homopeptides differ substantially in this model. In particular, the average radius of gyration scales with the sequence length in a residue-dependent manner.

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.

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.

Mechanism of Initiation, Association, and Formation of Amyloid Fibrils Modeled with the N-Terminal Peptide Fragment, IKYLEFIS, of Myoglobin G-Helix

Some peptides and proteins undergo self-aggregation under certain conditions, leading to amyloid fibrils formation, which is related to many disease conditions. It is important to understand such amyloid fibrils formation to provide mechanistic detail that governs the process. A predominantly α-helical myoglobin has been reported recently to readily form amyloid fibrils at a higher temperature, similar to its G-helix segment. Here, we have investigated the mechanism of amyloid fibrils formation by performing multiple long molecular dynamics simulations (27 μs) on the N-terminal segment of the G-helix of myoglobin. These simulations resulted in the formation of a single-layered tetrameric β-sheet with mixed parallel and antiparallel β-strands and this is the most common event irrespective of many different starting structures. Formation of the single-layered tetrameric β-sheet takes place following three distinctive pathways. The process of fibril initiation is dependent on temperature. Further, this study provides mechanistic insights into the formation of multilayered fibrilar structure, which could be applicable to a wider variety of peptides or proteins to understand the amyloidogenesis.

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

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

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

The size of assembled Aβ_17-42 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.

Structural Conversion of Aβ17-42 Peptides from Disordered Oligomers to U-Shape Protofilaments via Multiple Kinetic Pathways

Discovering the mechanisms by which proteins aggregate into fibrils is an essential first step in understanding the molecular level processes underlying neurodegenerative diseases such as Alzheimer's and Parkinson's. The goal of this work is to provide insights into the structural changes that characterize the kinetic pathways by which amyloid-β peptides convert from monomers to oligomers to fibrils. By applying discontinuous molecular dynamics simulations to PRIME20, a force field designed to capture the chemical and physical aspects of protein aggregation, we have been able to trace out the entire aggregation process for a system containing 8 Aβ17-42 peptides. We uncovered two fibrillization mechanisms that govern the structural conversion of Aβ17-42 peptides from disordered oligomers into protofilaments. The first mechanism is monomeric conversion templated by a U-shape oligomeric nucleus into U-shape protofilament. The second mechanism involves a long-lived and on-pathway metastable oligomer with S-shape chains, having a C-terminal turn, en route to the final U-shape protofilament. Oligomers with this C-terminal turn have been regarded in recent experiments as a major contributing element to cell toxicity in Alzheimer's disease. The internal structures of the U-shape protofilaments from our PRIME20/DMD simulation agree well with those from solid state NMR experiments. The approach presented here offers a simple molecular-level framework to describe protein aggregation in general and to visualize the kinetic evolution of a putative toxic element in Alzheimer's disease in particular.

Effects of the A117V mutation on the folding and aggregation of palindromic sequences (PrP113–120) in prion: insights from replica exchange molecular dynamics simulations

The A117V mutation enhances the aggregation propensity of the palindromic sequences in prion protein.

Impact of sequence on the molecular assembly of short amyloid peptides

The goal of this work is to understand how the sequence of a protein affects the likelihood that it will form an amyloid fibril and the kinetics along the fibrillization pathway. The focus is on very short fragments of amyloid proteins since these play a role in the fibrillization of the parent protein and can form fibrils themselves. Discontinuous molecular dynamics simulations using the PRIME20 force field were performed of the aggregation of 48-peptide systems containing SNQNNF (PrP (170-175)), SSTSAA (RNaseA(15-20)), MVGGVV (Aβ(35-40)), GGVVIA (Aβ(37-42)), and MVGGVVIA (Aβ(35-42)). In our simulations SNQQNF, SSTTSAA, and MVGGVV form large numbers of fibrillar structures spontaneously (as in experiment). GGVVIA forms β-sheets that do not stack into fibrils (unlike experiment). The combination sequence MVGGVVIA forms less fibrils than MVGGVV, hindered by the presence of the hydrophobic residues at the C-terminal. Analysis of the simulation kinetics and energetics reveals why MVGGVV forms fibrils and GGVVIA does not, and why adding I and A to MVGGVVIA reduces fibrillization and enhances amorphous aggregation into oligomeric structures. The latter helps explain why Aβ(1-42) assembles into more complex oligomers than Aβ(1-40), a consequence of which is that it is more strongly associated with Alzheimer's disease.

β-hairpin-mediated formation of structurally distinct multimers of neurotoxic prion peptides

Protein misfolding disorders are associated with conformational changes in specific proteins, leading to the formation of potentially neurotoxic amyloid fibrils. During pathogenesis of prion disease, the prion protein misfolds into β-sheet rich, protease-resistant isoforms. A key, hydrophobic domain within the prion protein, comprising residues 109-122, recapitulates many properties of the full protein, such as helix-to-sheet structural transition, formation of fibrils and cytotoxicity of the misfolded isoform. Using all-atom, molecular simulations, it is demonstrated that the monomeric 109-122 peptide has a preference for α-helical conformations, but that this peptide can also form β-hairpin structures resulting from turns around specific glycine residues of the peptide. Altering a single amino acid within the 109-122 peptide (A117V, associated with familial prion disease) increases the prevalence of β-hairpin formation and these observations are replicated in a longer peptide, comprising residues 106-126. Multi-molecule simulations of aggregation yield different assemblies of peptide molecules composed of conformationally-distinct monomer units. Small molecular assemblies, consistent with oligomers, comprise peptide monomers in a β-hairpin-like conformation and in many simulations appear to exist only transiently. Conversely, larger assemblies are comprised of extended peptides in predominately antiparallel β-sheets and are stable relative to the length of the simulations. These larger assemblies are consistent with amyloid fibrils, show cross-β structure and can form through elongation of monomer units within pre-existing oligomers. In some simulations, assemblies containing both β-hairpin and linear peptides are evident. Thus, in this work oligomers are on pathway to fibril formation and a preference for β-hairpin structure should enhance oligomer formation whilst inhibiting maturation into fibrils. These simulations provide an important new atomic-level model for the formation of oligomers and fibrils of the prion protein and suggest that stabilization of β-hairpin structure may enhance cellular toxicity by altering the balance between oligomeric and fibrillar protein assemblies.

Molecular dynamics studies on 3D structures of the hydrophobic region PrP(109-136)

Prion diseases, traditionally referred to as transmissible spongiform encephalopathies, are invariably fatal and highly infectious neurodegenerative diseases that affect a wide variety of mammalian species, manifesting as scrapie in sheep, bovine spongiform encephalopathy (or 'mad-cow' disease) in cattle, and Creutzfeldt-Jakob disease, Gerstmann-Strussler-Scheinker syndrome, fatal familial insomnia (FFI), and Kulu in humans, etc. These neurodegenerative diseases are caused by the conversion from a soluble normal cellular prion protein (PrP(C)) into insoluble abnormally folded infectious prions (PrP(Sc)). The hydrophobic region PrP(109-136) controls the formation of diseased prions: the normal PrP(113-120) AGAAAAGA palindrome is an inhibitor/blocker of prion diseases and the highly conserved glycine-xxx-glycine motif PrP(119-131) can inhibit the formation of infectious prion proteins in cells. This article gives detailed reviews on the PrP(109-136) region and presents the studies of its three-dimensional structures and structural dynamics.

Influence of temperature on formation of perfect tau fragment fibrils using PRIME20/DMD simulations

We investigate the fibrillization process for amyloid tau fragment peptides (VQIVYK) by applying the discontinuous molecular dynamics method to a system of 48 VQIVYK peptides modeled using a new protein model/force field, PRIME20. The aim of the article is to ascertain which factors are most important in determining whether or not a peptide system forms perfect coherent fibrillar structures. Two different directional criteria are used to determine when a hydrogen bond occurs: the original H-bond constraints and a parallel preference H-bond constraint that imparts a slight bias towards the formation of parallel versus antiparallel strands in a β-sheet. Under the original H-bond constraints, the resulting fibrillar structures contain a mixture of parallel and antiparallel pairs of strands within each β-sheet over the whole fibrillization temperature range. Under the parallel preference H-bond constraints, the β-sheets within the fibrillar structures are more likely to be parallel and indeed become perfectly parallel, consistent with X-ray crystallography, at a high temperature slightly below the fibrillization temperature. The high temperature environment encourages the formation of perfect fibril structures by providing enough time and space for peptides to rearrange during the aggregation process. There are two different kinetic mechanisms, template assembly with monomer addition at high temperature and merging/rearrangement without monomer addition at low temperature, which lead to significant differences in the final fibrillar structure. This suggests that the diverse fibril morphologies generally observed in vitro depend more on environmental conditions than has heretofore been appreciated.

Effects of different force fields and temperatures on the structural character of Abeta (12-28) peptide in aqueous solution

The aim of this work is to investigate the effects of different force fields and temperatures on the structural character of Aβ (12-28) peptide in aqueous solution. Moreover, the structural character of Aβ (12-28) peptide is compared with other amyloid peptides (such as H1 and α-syn12 peptide). The two independent temperature replica exchange molecular dynamics (T-REMD) simulations were completed by using two different models (OPLS-AA/TIP4P and GROMOS 43A1/SPC). We compared the models by analyzing the distributions of backbone dihedral angles, the secondary structure propensity, the free energy surface and the formation of β-hairpin. The results show that the mostly populated conformation state is random coil for both models. The population of β-hairpin is below 8 percent for both models. However, the peptide modeled by GROMOS 43A1 form β-hairpin with turn located at residues F19-E22, while the peptide modeled by OPLS-AA form β-hairpin with turn located at residues L17-F20.