Effect of Familial Mutations on the Interconversion of α-Helix to β-Sheet Structures in an Amyloid-Forming Peptide: Insight from Umbrella Sampling Simulations

Helix-to-sheet transition of the Aβ42 peptide revealed using an enhanced sampling strategy and Markov state model

The self-assembly of Aβ peptides into toxic oligomers and fibrils is the primary cause of Alzheimer's disease. Moreover, the conformational transition from helix to sheet is considered a crucial step in the aggregation of Aβ peptides. However, the structural details of this process still remain unclear due to the heterogeneity and transient nature of the Aβ peptides. In this study, we developed an enhanced sampling strategy that combines artificial neural networks (ANN) with metadynamics to explore the conformational space of the Aβ42 peptides. The strategy consists of two parts: applying ANN to optimize CVs and conducting metadynamics based on the resulting CVs to sample conformations. The results showed that this strategy achieved better sampling performance in terms of the distribution of sampled conformations. The sampling efficiency is increased by 10-fold compared to our previous Hamiltonian Exchange Molecular Dynamics (MD) and by 1000-fold compared to ordinary MD. Based on the sampled conformations, we constructed a Markov state model to understand the detailed transition process. The intermediate states in this process are identified, and the connecting paths are analyzed. The conformational transitions in D23-K28 and M35-V40 are proven to be crucial for aggregation. These results are helpful in clarifying the mechanism and process of Aβ42 peptide aggregation. D23-K28 and M35-V40 can be identified as potential targets for screening and designing inhibitors of Aβ peptide aggregation.

Specific interaction from different Aβ42 peptide fragments to α7nAChR-A study of molecular dynamics simulation

CONTEXT

Existing researches confirmed that β amyloid (Aβ) has a high affinity for the α7 nicotinic acetylcholine receptor (α7nAChR), associating closely to Alzheimer's disease. The majority of related studies focused on the experimental reports on the neuroprotective role of Aβ fragment (Aβx), however, with a lack of investigation into the most suitable binding region and mechanism of action between Aβ fragment and α7nAChR. In the study, we employed four Aβ1-42 fragments Aβx, Aβ1-16, Aβ10-16, Aβ12-28, and Aβ30-42, of which the first three were confirmed to play neuroprotective roles upon directly binding, to interact with α7nAChR.

METHODS

The protein-ligand docking server of CABS-DOCK was employed to obtain the α7nAChR-Aβx complexes. Only the top α7nAChR-Aβx complexes were used to perform all-atom GROMACS dynamics simulation in combination with Charmm36 force field, by which α7nAChR-Aβx interactions' dynamic behavior and specific locations of these different Aβx fragments were identified. MM-PBSA calculations were also done to estimate the binding free energies and the different contributions from the residues in the Aβx. Two distinct results for the first three and fourth Aβx fragments in binding site, strength, key residue, and orientation, account for why the fourth fails to play a neuroprotective role at the molecular level.

Caffeic acid for the prevention and treatment of Alzheimer's disease: The effect of lipid membranes on the inhibition of aggregation and disruption of Aβ fibrils

The onset of Alzheimer's disease (AD) is triggered by the aggregation of amyloid β (Aβ) peptides which leads to the formation of fibrils. Molecules that are able to inhibit fibrillation and/or disrupt fibrils have aroused interest for AD therapy. Fibrillation is a complex process highly dependent on the surrounding environment. One of the most relevant factors affecting Aβ aggregation is the presence of cellular membranes. Here, the ability of caffeic acid (CA) in preventing the Aβ_1-42 aggregation and disaggregating mature fibrils was evaluated in a membrane-like environment and in a bulk solution for comparison. To this end, liposomes were used as in vitro models of neuronal membranes. CA exhibited strong activity in inhibiting the fibrillation of Aβ_1-42 in the aqueous medium, which remained in the presence of liposomes. Furthermore, CA disrupted instantly preformed fibrils in the aqueous medium. However, the CA's disaggregating activity was disturbed by the presence of lipid membranes. Instead of being immediate, the CA's disaggregating activity increased over time. The moderate affinity of CA for the lipid bilayer may explain the distinct fibrils disaggregation profiles. These findings emphasize the therapeutic potential of CA in preventing and treating AD, thus justifying further investigations in animal models.

Influence of in vitro neuronal membranes on the anti-amyloidogenic activity of gallic acid: Implication for the therapy of Alzheimer's disease

Molecules inhibiting the amyloid beta (Aβ) peptide aggregation and/or disaggregating mature fibrils are a promising approach for the Alzheimer's disease (AD) therapy, as the Aβ fibrillation is one of the key triggers of the disease. Gallic acid (GA) is a phenolic acid with anti-amyloidogenic activity against Aβ in buffered solutions. However, there is still no evidence of these properties in vivo. Given the rate of failures of AD drug development, there is a huge demand of replicating the in vivo environment in in vitro studies, thus allowing to stop earlier the study of molecules with no effect in vivo. Thus, this study aims to evaluate the effect of in vitro neuronal membranes on the GA's ability in preventing Aβ_1-42 aggregation and disrupting preformed fibrils. To this end, liposomes were employed to mimic the cell membrane environment. The results reveal that the lipid membranes did not affect the GA's ability in inhibiting Aβ_1-42 fibrillation. However, in vitro neuronal membranes modulate the GA-induced Aβ fibrils disaggregation, which may be related with the moderate affinity of the compound for the lipid membrane. Even so, GA presented strong anti-amyloidogenic properties in the cell membrane-like environment. This work highlights the promising value of GA on preventing and treating AD, thus justifying its study in animal models.

Molecular dynamics study of conformation transition from helix to sheet of Aβ42 peptide

Aβ42 peptides can form helix and sheet structure under different conditions. The conformational conversion is closely associated with Aβ peptides aggregation and their neurotoxicity. But the transition from helix to sheet is not be clearly understood. In this study we performed microsecond timescale MD simulations of Aβ42 peptide to investigate the conformation transition from α-helix to β-sheet. Markov state model (MSM) was built to facilitate identification of crucial intermediate states and possible transition pathway. Based on the analysis, we found that the region Y10-A21 in the middle of Aβ42 peptide plays an initial role in this transition. MSM model revealed that the collapse of helical structure in this region might trigger the formation of sheet structure. Moreover, we further simulated the aggregation of Aβ42 peptides with different conformations. We found that the Aβ42 peptides forming sheet structure have higher aggregation potential compared with peptides with helix structure. These results demonstrate that we can prevent the aggregation of Aβ42 peptides by stabilizing the helix structure in the region of Y10-A21. In addition, this study provides new insight into better understanding the conformational transition and aggregation of Aβ42 peptides.

Vitamin B12 Inhibits Aβ Fibrillation and Disaggregates Preformed Fibrils in the Presence of Synthetic Neuronal Membranes

The aggregation of amyloid β (Aβ) peptide with subsequent formation of fibrils which deposit in senile plaques is considered one of the key triggers of Alzheimer's disease (AD). Molecules targeting the inhibition of Aβ fibrillation and/or the disruption of Aβ fibrils are thus promising approaches for the medical prevention and treatment of AD. However, amyloid formation is a complex process strongly influenced by the cellular environment, such as cell membranes, which may affect the effectiveness of therapeutic molecules. In this study, the effect of the vitamin B12 (VB12) on the formation and disaggregation of Aβ_1-42 fibrils was investigated in the presence of artificial neuronal membranes mimicked by liposomes. Evidence showed that VB12 slows down the Aβ fibrillization and reduces the content of fibrils in aqueous solution. Moreover, the vitamin exhibited a strong ability to disrupt preformed fibrils. However, the presence of lipid vesicles compromised the VB12's antiamyloidogenic properties due to the competitive interaction of the vitamin with the lipid membrane and the Aβ peptide. Even so, VB12 was effective in inhibiting the fibril formation and disaggregating fibrils in the lipid membrane environment. Thereby, these results indicate that VB12 could be a promising molecule both for the prevention and cure of AD, thus warranting its study in animal models.

Assessment of Amyloid Forming Tendency of Peptide Sequences from Amyloid Beta and Tau Proteins Using Force-Field, Semi-Empirical, and Density Functional Theory Calculations

A wide variety of neurodegenerative diseases are characterized by the accumulation of protein aggregates in intraneuronal or extraneuronal brain regions. In Alzheimer's disease (AD), the extracellular aggregates originate from amyloid-β proteins, while the intracellular aggregates are formed from microtubule-binding tau proteins. The amyloid forming peptide sequences in the amyloid-β peptides and tau proteins are responsible for aggregate formation. Experimental studies have until the date reported many of such amyloid forming peptide sequences in different proteins, however, there is still limited molecular level understanding about their tendency to form aggregates. In this study, we employed umbrella sampling simulations and subsequent electronic structure theory calculations in order to estimate the energy profiles for interconversion of the helix to β-sheet like secondary structures of sequences from amyloid-β protein (KLVFFA) and tau protein (QVEVKSEKLD and VQIVYKPVD). The study also included a poly-alanine sequence as a reference system. The calculated force-field based free energy profiles predicted a flat minimum for monomers of sequences from amyloid and tau proteins corresponding to an α-helix like secondary structure. For the parallel and anti-parallel dimer of KLVFFA, double well potentials were obtained with the minima corresponding to α-helix and β-sheet like secondary structures. A similar double well-like potential has been found for dimeric forms for the sequences from tau fibril. Complementary semi-empirical and density functional theory calculations displayed similar trends, validating the force-field based free energy profiles obtained for these systems.

An α-helix mimetic oligopyridylamide, ADH-31, modulates Aβ42 monomer aggregation and destabilizes protofibril structures: insights from molecular dynamics simulations

Alzheimer's disease (AD), an epidemic growing worldwide due to no effective medical aid available in the market, is a neurological disorder. AD is known to be directly associated with the toxicity of amyloid-β (Aβ) aggregates. In search of potent inhibitors of Aβ aggregation, Hamilton and co-workers reported an α-helix mimetic, ADH-31, which acts as a powerful antagonist of Aβ42 aggregation. To identify the key interactions between protein-ligand complexes and to gain insights into the inhibitory mechanism of ADH-31 against Aβ42 aggregation, molecular dynamics (MD) simulations were performed in the present study. The MD simulations highlighted that ADH-31 showed distinct binding capabilities with residues spanning from the N-terminal to the central hydrophobic core (CHC) region of Aβ42 and restricted the conformational transition of the helix-rich structure of Aβ42 into another form of secondary structures (coil/turn/β-sheet). Hydrophobic contacts, hydrogen bonding and π-π interaction contribute to the strong binding between ADH-31 and Aβ42 monomer. The Dictionary of Secondary Structure of Proteins (DSSP) analysis highlighted that the probability of helical content increases from 38.5% to 50.2% and the turn content reduces from 14.7% to 6.2% with almost complete loss of the β-sheet structure (4.5% to 0%) in the Aβ42 monomer + ADH-31 complex. The per-residue binding free energy analysis demonstrated that Arg5, Tyr10, His14, Gln15, Lys16, Val18, Phe19 and Lys28 residues of Aβ42 are responsible for the favourable binding free energy in Aβ42 monomer + ADH-31 complex, which is consistent with the 2D HSQC NMR of the Aβ42 monomer that depicted a change in the chemical shift of residues spanning from Glu11 to Phe20 in the presence of ADH-31. The MD simulations highlighted the prevention of sampling of amyloidogenic β-strand conformations in Aβ42 trimer in the presence of ADH-31 as well as the ability of ADH-31 to destabilize Aβ42 trimer and protofibril structures. The lower binding affinity between Aβ42 trimer chains in the presence of ADH-31 highlights the destabilization of the Aβ42 trimer structure. Overall, MD results highlighted that ADH-31 inhibited Aβ42 aggregation by constraining Aβ peptides into helical conformation and destabilized Aβ42 trimer as well as protofibril structures. The present study provides a theoretical insight into the atomic level details of the inhibitory mechanism of ADH-31 against Aβ42 aggregation as well as protofibril destabilization and could be implemented in the structure-based drug design of potent therapeutic agents for AD.

Impact of Mutations on the Conformational Transition from α-Helix to β-Sheet Structures in Arctic-Type Aβ40: Insights from Molecular Dynamics Simulations

The amyloid-β (Aβ) protein aggregation into toxic oligomers and fibrils has been recognized as a key player in the pathogenesis of Alzheimer's disease. Recent experiments reported that a double alanine mutation (L17A/F19A) in the central hydrophobic core (CHC) region of [G22]Aβ₄₀ (familial Arctic mutation) diminished the self-assembly propensity of [G22]Aβ₄₀. However, the molecular mechanism behind the decreased aggregation tendency of [A17/A19/G22]Aβ₄₀ is not well understood. Herein, we carried out molecular dynamics simulations to elucidate the structure and dynamics of [G22]Aβ₄₀ and [A17/A19/G22]Aβ₄₀. The results for the secondary structure analysis reveal a significantly increased amount of the helical content in the CHC and C-terminal region of [A17/A19/G22]Aβ₄₀ as compared to [G22]Aβ₄₀. The bending free-energy analysis of D23-K28 salt bridge suggests that the double alanine mutation in the CHC region of [G22]Aβ₄₀ has the potential to reduce the fibril formation rate by 0.57 times of [G22]Aβ₄₀. Unlike [G22]Aβ₄₀, [A17/A19/G22]Aβ₄₀ largely sampled helical conformation, as determined by the minimum energy conformations extracted from the free-energy landscape. The present study provided atomic level details into the experimentally observed diminished aggregation tendency of [A17/A19/G22]Aβ₄₀ as compared to [G22]Aβ₄₀.

How Does the Mono-Triazole Derivative Modulate Aβ42 Aggregation and Disrupt a Protofibril Structure: Insights from Molecular Dynamics Simulations

Clinical studies have identified that abnormal self-assembly of amyloid-β (Aβ) peptide into toxic fibrillar aggregates is associated with the pathology of Alzheimer's disease (AD). The most acceptable therapeutic approach to stop the progression of AD is to inhibit the formation of β-sheet-rich structures. Recently, we designed and evaluated a series of novel mono-triazole derivatives 4(a-x), where compound 4v was identified as the most potent inhibitor of Aβ₄₂ aggregation and disaggregates preformed Aβ₄₂ fibrils significantly. Moreover, 4v strongly averts the Cu²⁺-induced Aβ₄₂ aggregation and disaggregates the preformed Cu²⁺-induced Aβ₄₂ fibrils, halts the generation of reactive oxygen species, and shows neuroprotective effects in SH-SY5Y cells. However, the underlying molecular mechanism of inhibition of Aβ₄₂ aggregation by 4v and disaggregation of preformed Aβ₄₂ fibrils remains obscure. In this work, molecular dynamics (MD) simulations have been performed to explore the conformational ensemble of the Aβ₄₂ monomer and a pentameric protofibril structure of Aβ₄₂ in the presence of 4v. The MD simulations highlighted that 4v binds preferentially at the central hydrophobic core region of the Aβ₄₂ monomer and chains D and E of the Aβ₄₂ protofibril. The dictionary of secondary structure of proteins analysis indicated that 4v retards the conformational conversion of the helix-rich structure of the Aβ₄₂ monomer into the aggregation-prone β-sheet conformation. The binding free energy calculated by the molecular mechanics Poisson-Boltzmann surface area method revealed an energetically favorable process with ΔG _binding = -44.9 ± 3.3 kcal/mol for the Aβ₄₂ monomer-4v complex. The free energy landscape analysis highlighted that the Aβ₄₂ monomer-4v complex sampled conformations with significantly higher helical contents (35 and 49%) as compared to the Aβ₄₂ monomer alone (17%). Compound 4v displayed hydrogen bonding with Gly37 (chain E) and π-π interactions with Phe19 (chain D) of the Aβ₄₂ protofibril. Further, the per-residue binding free energy analysis also highlighted that Phe19 (chain D) and Gly37 (chain E) of the Aβ₄₂ protofibril showed the maximum contribution in the binding free energy. The decreased binding affinity and residue-residue contacts between chains D and E of the Aβ₄₂ protofibril in the presence of 4v indicate destabilization of the Aβ₄₂ protofibril structure. Overall, the structural information obtained through MD simulations indicated that 4v stabilizes the native helical conformation of the Aβ₄₂ monomer and persuades a destabilization in the protofibril structure of Aβ₄₂. The results of the study will be useful in the rational design of potent inhibitors against amyloid aggregation.

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.

Effect of Piedmont mutation (L34V) on the structure, dynamics, and aggregation of Alzheimer's Aβ40 peptide

The amyloid-β (Aβ) aggregation in the brain has been associated with the development of Alzheimer's disease (AD). The previous studies have reported that Piedmont mutation (L34V) increases the rate of Aβ₄₀ aggregation. However, the underlying molecular mechanism of the effect of L34V mutation on Aβ₄₀ structure, dynamics, and aggregation remains largely unclear. In the present study, molecular dynamics (MD) simulations were performed to elucidate the effect of L34V mutation on the structural changes and conformational dynamics of Aβ₄₀. The secondary structure analysis highlight that L34V mutation enhances Aβ₄₀ self-assembly due to the formation of aggregation-prone β-sheet structure at the C-terminus of Aβ₄₀ monomeric structure. The higher probability of Asp23-Lys28 salt bridge interaction in Aβ₄₀(L34V) leads to aggregation prone β-sheet conformations, which has the potential to increase the fibril formation rate. The free energy landscape (FEL) analysis depict a sampling of coil conformation in the free energy minima of Aβ₄₀, whereas the aggregation-prone β-sheet conformation was observed at the C-terminal region of Aβ₄₀(L34V) in the minimum energy conformations extracted from FEL of Aβ₄₀(L34V). MD simulations, in agreement with experiment, highlight that L34V mutation increases Aβ₄₀ aggregation as the sampling of the aggregation-prone β-sheet conformation substantially increased. Overall, MD simulations provided atomic level details into the increased fibril formation tendency upon L34V mutation and physical insights into the L34V-mediated conformational as well as structural changes in Aβ₄₀.

Interactions of a multifunctional di-triazole derivative with Alzheimer's Aβ42monomer and Aβ42protofibril: a systematic molecular dynamics study

The molecular dynamics simulations results highlighted that the multi-target-directed ligand6nstabilizes the native α-helix conformation of the Aβ₄₂monomer and induces a sizable destabilization in the Aβ₄₂protofibril structure.

Edaravone inhibits the conformational transition of amyloid-β42: insights from molecular dynamics simulations

Previous work has shown that edaravone inhibits fibrillogenesis of amyloid-β protein (Aβ). However, the detailed mechanism by which edaravone inhibits the conformational transition of the Aβ42 monomer is not known at the molecular level. Here, explicit-solvent molecular dynamics (MD) simulations were coupled with molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) method to address the issue. MD simulations confirmed that edaravone inhibits the conformational transition of the Aβ42 monomer in a dose-dependent manner. It was found that the direct interactions between edaravone and Aβ42 are responsible for its inhibiting effects. The analysis of binding free energy using the MM-PBSA method demonstrated that the nonpolar interactions provide favourable contributions (about -71.7 kcal/mol). Conversely, the polar interactions are unfavourable for the binding process. A total of 14 residues were identified as greatly contributing to the binding free energy between edaravone and the Aβ42 monomer. In addition, the intra-peptide hydrophobic interactions were weakened and the salt bridge D23-K28 was interrupted by edaravone. Therefore, the conformational transition was inhibited. Our studies provide molecular-level insights into how edaravone molecules inhibit the conformational transition of the Aβ42 monomer, which may be useful for designing amyloid inhibitors.Communicated by Ramaswamy H. Sarma.

Molecular Simulations Reveal Terminal Group Mediated Stabilization of Helical Conformers in Both Amyloid-β42 and α-Synuclein

The presence of partially structured helices in natively unfolded amyloid-β42 (Aβ42) and α-synuclein (αS) has been shown to accelerate fibrillation in the onset of Alzheimer's and Parkinson's disease, respectively. At the other extreme, folded stable helical conformers have also been reported to resist amyloid formation. Recent studies indicate that amyloidogenic aggregation can be impeded using small molecules that stabilize the α-helical monomers and switch off the neurotoxic pathway. We predict a common intrapeptide route to stabilization based on the plasticity of helical conformations of Aβ42 and αS as assessed through extensive atomistic molecular dynamics (MD) computer simulations (∼36 μs) across ten distinct protein force field and water model combinations. Computed free energies and interaction maps (not obtainable from experiments alone) show that flexible terminal groups (N-terminus of Aβ42 and C-terminus of αS) show a tendency to stabilize folded helical conformations in both peptides via primary hydrophobic interactions with central hydrophobic domains, and secondary salt bridges with other domains. These interactions confer aggregation resistance by decreasing the population of partially structured helices and are absent in control simulations of complete unfolding. Computed helical stability is also significantly reduced in terminal-deleted variants. The models suggest new strategies to tackle neurodegeneration by rationally re-engineering terminal groups to optimize their predicted ability to deactivate helical monomers.