Folding Atomistic Proteins in Explicit Solvent Using Simulated Tempering

Effect of Main and Side Chains on the Folding Mechanism of the Trp-Cage Miniprotein

Proteins that do not fold into their functional native state have been linked to diseases. In this study, the influence of the main and side chains of individual amino acids on the folding of the tryptophan cage (Trp-cage), a designed 20-residue miniprotein, was analyzed. For this purpose, we calculated the solvation free energy (SFE) contributions of individual atoms by using the 3D-reference interaction site model with the atomic decomposition method. The mechanism by which the Trp-cage is stabilized during the folding process was examined by calculating the total energy, which is the sum of the conformational energy and SFE. The folding process of the Trp-cage resulted in a stable native state, with a total energy that was 62.4 kcal/mol lower than that of the unfolded state. The solvation entropy, which is considered to be responsible for the hydrophobic effect, contributed 31.3 kcal/mol to structural stabilization. In other words, the contribution of the solvation entropy accounted for approximately half of the total contribution to Trp-cage folding. The hydrophobic core centered on Trp6 contributed 15.6 kcal/mol to the total energy, whereas the solvation entropy contribution was 6.3 kcal/mol. The salt bridge formed by the hydrophilic side chains of Asp9 and Arg16 contributed 10.9 and 5.0 kcal/mol, respectively. This indicates that not only the hydrophobic core but also the salt bridge of the hydrophilic side chains gain solvation entropy and contribute to stabilizing the native structure of the Trp-cage.

Stable Cavitation Interferes with Aβ16-22 Oligomerization

Ultrasound and microbubbles are used for many medical applications nowadays. Scanning ultrasound can remove amyloid-β (Aβ) aggregates in the mouse brain and restores memory in an Alzheimer's disease mouse model. In vitro studies showed that amyloid fibrils are fragmented due to the ultrasound-induced bubble inertial cavitation, and ultrasonic pulses accelerate the depolymerization of Aβ fibrils into monomers at 1 μM of concentration. Under applied ultrasound, microbubbles can be in a stable oscillating state or unstable inertial cavitation state. The latter occurs when ultrasound causes a dramatic change of bubble sizes above a certain acoustic pressure. We have developed and implemented a nonequilibrium molecular dynamics simulation algorithm to the AMBER package, to facilitate the investigation of the molecular mechanism of Aβ oligomerization under stable cavitation. Our results indicated that stable cavitation not only inhibited oligomeric formation, but also prevented the formation of β-rich oligomers. The network analysis of state transitions revealed that stable cavitation altered the oligomerization pathways of Aβ_16-22 peptides. Our simulation tool may be applied to optimize the experimental conditions to achieve the best therapeutical effect.

Enhanced sampling without borders: on global biasing functions and how to reweight them

Molecular dynamics (MD) simulations are a powerful tool to follow the time evolution of biomolecular motions in atomistic resolution. However, the high computational demand of these simulations limits the timescales of motions that can be observed. To resolve this issue, so called enhanced sampling techniques are developed, which extend conventional MD algorithms to speed up the simulation process. Here, we focus on techniques that apply global biasing functions. We provide a broad overview of established enhanced sampling methods and promising new advances. As the ultimate goal is to retrieve unbiased information from biased ensembles, we also discuss benefits and limitations of common reweighting schemes. In addition to concisely summarizing critical assumptions and implications, we highlight the general application opportunities as well as uncertainties of global enhanced sampling.

Efficient sampling of high-dimensional free energy landscapes using adaptive reinforced dynamics

Enhanced sampling methods such as metadynamics and umbrella sampling have become essential tools for exploring the configuration space of molecules and materials. At the same time, they have long faced a number of issues such as the inefficiency when dealing with a large number of collective variables (CVs) or systems with high free energy barriers. Here we show that, with clustering and adaptive tuning techniques, the reinforced dynamics (RiD) scheme can be used to efficiently explore the configuration space and free energy landscapes with a large number of CVs or systems with high free energy barriers. We illustrate this by studying various representative and challenging examples. First we demonstrate the efficiency of adaptive RiD compared with other methods and construct the nine-dimensional (9D) free energy landscape of a peptoid trimer, which has energy barriers of more than 8 kcal mol-1. We then study the folding of the protein chignolin using 18 CVs. In this case, both the folding and unfolding rates are observed to be 4.30 μs-1. Finally, we propose a protein structure refinement protocol based on RiD. This protocol allows us to efficiently employ more than 100 CVs for exploring the landscape of protein structures and it gives rise to an overall improvement of 14.6 units over the initial global distance test-high accuracy (GDT-HA) score.

Computer Simulations Aimed at Exploring Protein Aggregation and Dissociation

Protein aggregation can lead to well-defined structures that are functional, but is also the cause of the death of neuron cells in many neurodegenerative diseases. The complexity of the molecular events involved in the aggregation kinetics of amyloid proteins and the transient and heterogeneous characters of all oligomers prevent high-resolution structural experiments. As a result, computer simulations have been used to determine the atomic structures of amyloid proteins at different association stages as well as to understand fibril dissociation. In this chapter, we first review the current computer simulation methods used for aggregation with some atomistic and coarse-grained results aimed at better characterizing the early formed oligomers and amyloid fibril formation. Then we present the applications of non-equilibrium molecular dynamics simulations to comprehend the dissociation of protein assemblies.

Effects of All-Atom Molecular Mechanics Force Fields on Amyloid Peptide Assembly: The Case of PHF6 Peptide of Tau Protein

Molecular dynamics (MD) simulations play a vital role in revealing the mechanism of amyloid aggregation that is crucial to the therapeutic agent development for Alzheimer's Disease. However, the accuracy of MD simulation results strongly depends on the force field employed. In our previous benchmark for 17 all-atom force fields on modeling of amyloid aggregation using the Aβ_16-22 dimer, we showed that AMBER14SB and CHARMM36m are suitable force fields for amyloid aggregation simulation, while GROMOS54a7 and OPLSAA are not good for the task. In this work, we continue assessing the applicability of atomistic force fields on amyloid aggregation using the VQIVYK (PHF6) peptide which is essential for tau-protein aggregation. Although, both Aβ_16-22 and PHF6 peptides formed fibrils in vitro, the PHF6 fibrils are parallel β-sheets, while the Aβ_16-22 fibrils are antiparallel β-sheets. We performed an all-atom large-scale MD simulation in explicit water on the PHF6 dimer and octa-peptides systems using five mainstream force fields, including AMBER99SB-disp, AMBER14SB, CHARMM36m, GROMOS54a7, and OPLSAA. The accumulated simulation time is 0.2 ms. Our result showed that the β-sheet structures of PHF6 peptides sampled by AMBER99SB-disp, AMBER14SB, GROMOS54a7, and OPLSAA are in favor of the antiparallel β-sheets, while the dominant type of β-sheet structures is parallel β-sheet by using CHARMM36m. Among the five force fields, CHARMM36m provides the strongest CH-π interaction that was observed in an NMR study. The comparison between our results and experimental observation indicates that CHARMM36m achieved the best performance on modeling the aggregation of PHF6 peptides. In summary, CHARMM36m is currently the most suitable force field for studying the aggregation of both amyloid-β and Tau through MD simulations.

Atazanavir, Alone or in Combination with Ritonavir, Inhibits SARS-CoV-2 Replication and Proinflammatory Cytokine Production

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is already responsible for far more deaths than previous pathogenic coronaviruses (CoVs) from 2002 and 2012. The identification of clinically approved drugs to be repurposed to combat 2019 CoV disease (COVID-19) would allow the rapid implementation of potentially life-saving procedures. The major protease (Mpro) of SARS-CoV-2 is considered a promising target, based on previous results from related CoVs with lopinavir (LPV), an HIV protease inhibitor. However, limited evidence exists for other clinically approved antiretroviral protease inhibitors. Extensive use of atazanavir (ATV) as antiretroviral and previous evidence suggesting its bioavailability within the respiratory tract prompted us to study this molecule against SARS-CoV-2. Our results show that ATV docks in the active site of SARS-CoV-2 Mpro with greater strength than LPV, blocking Mpro activity. We confirmed that ATV inhibits SARS-CoV-2 replication, alone or in combination with ritonavir (RTV) in Vero cells and a human pulmonary epithelial cell line. ATV/RTV also impaired virus-induced enhancement of interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-α) levels. Together, our data strongly suggest that ATV and ATV/RTV should be considered among the candidate repurposed drugs undergoing clinical trials in the fight against COVID-19.

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.

Predicting High-Concentration Interactions of Monoclonal Antibody Solutions: Comparison of Theoretical Approaches for Strongly Attractive Versus Repulsive Conditions

Nonspecific protein-protein interactions of a monoclonal antibody were quantified experimentally using light scattering from low to high protein concentrations (c₂) and compared with prior work for a different antibody that yielded qualitatively different behavior. The c₂ dependence of the excess Rayleigh ratio (R^ex) provided the osmotic second virial coefficient (B₂₂) at low c₂ and the static structure factor (S_q=0) at high c₂, as a function of solution pH, total ionic strength (TIS), and sucrose concentration. Net repulsive interactions were observed at pH 5, with weaker repulsions at higher TIS. Conversely, attractive electrostatic interactions were observed at pH 6.5, with weaker attractions at higher TIS. Refined coarse-grained models were used to fit model parameters using experimental B₂₂ versus TIS data. The parameters were used to predict high-c₂ R^ex values via Monte Carlo simulations and separately with Mayer-sampling calculations of higher-order virial coefficients. For both methods, predictions for repulsive to mildly attractive conditions were quantitatively accurate. However, only qualitatively accurate predictions were practical for strongly attractive conditions. An alternative, higher resolution model was used to show semiquantitatively and quantitatively accurate predictions of strong electrostatic attractions at low c₂ and low ionic strength.

Coarse-grained dynamic RNA titration simulations

Electrostatic interactions play a pivotal role in many biomolecular processes. The molecular organization and function in biological systems are largely determined by these interactions. Owing to the highly negative charge of RNA, the effect is expected to be more pronounced in this system. Moreover, RNA base pairing is dependent on the charge of the base, giving rise to alternative secondary and tertiary structures. The equilibrium between uncharged and charged bases is regulated by the solution pH, which is therefore a key environmental condition influencing the molecule's structure and behaviour. By means of constant-pH Monte Carlo simulations based on a fast proton titration scheme, coupled with the coarse-grained model HiRE-RNA, molecular dynamic simulations of RNA molecules at constant pH enable us to explore the RNA conformational plasticity at different pH values as well as to compute electrostatic properties as local pK _a values for each nucleotide.

Orientational and Folding Thermodynamics via Electric Dipole Moment Restraining

The projection of molecular processes onto a small set of relevant descriptors, the so-called reaction coordinates or collective variables (CVs), is a technique nowadays routinely employed by the biomolecular simulation community. In this work, we implemented two CVs to manipulate the orientation (i.e., angle) (μ⃗_a) and magnitude (|μ⃗|) of the electric dipole moment. In doing so, we studied the thermodynamics of water orientation under the application of external voltages and the folding of two polypeptides at zero-field conditions. The projection of the free-energy [potential of mean force (PMF)] along water orientation defined an upper limit of around 0.3 V for irrelevant thermodynamic effects. On the other hand, sufficiently strong μ⃗_a restraints applied on 12-alanine (Ala₁₂) triggered structural effects because of the alignment of local dipoles; for lower restraints, a full-body rotation is achieved. The manipulation of |μ⃗| produced strong perturbations on the secondary structure of Ala₁₂, promoting an enhanced sampling to its configurational space. Rigorous free-energy calculations in the form of 2-D PMFs for deca-alanine showed the utility of |μ⃗| as a reaction coordinate to study folding in small α helices. As a whole, we propose that the manipulation of both components of the dipole moment, μ⃗_a and |μ⃗|, provides thermodynamics insights into the structural conformation and stability of biomolecules. These new CVs are implemented in the Colvars module, available for NAMD and LAMMPS.

Amyloid-β(29-42) Dimeric Conformations in Membranes Rich in Omega-3 and Omega-6 Polyunsaturated Fatty Acids

The omega-3 and omega-6 polyunsaturated fatty acids are two important components of cell membranes in human brains. When incorporated into phospholipids, omega-3 slows the progression of Alzheimer's disease (AD), whereas omega-6 is linked to increased risk of AD. Little is known on the amyloid-β (Aβ) conformations in membranes rich in omega-3 and omega-6 phospholipids. Herein, the structural properties of the Aβ_29-42 dimer embedded in both fatty acid membranes were comparatively studied to a 1-palmitoyl-2-oleoyl- sn-glycero-3-phosphocholine (POPC) bilayer using all-atom molecular dynamics (MD) simulations. Starting from α-helix, both omega-6 and omega-3 membranes promote new orientations and conformations of the dimer, in agreement with the observed dependence of Aβ production upon addition of these two fatty acids. This conformational result is corroborated by atomistic MD simulations of the dimer of the 99 amino acid C-terminal fragment of amyloid precursor protein spanning the residues 15-55. Starting from β-sheet, omega-6 membrane promotes helical and disordered structures of Aβ_29-42 dimer, whereas omega-3 membrane preserves the β-sheet structures differing however from those observed in POPC. Remarkably, the mixture of the two fatty acids and POPC depicts another conformational ensemble of the Aβ_29-42 dimer. This finding demonstrates that variation in the abundance of the molecular phospholipids, which changes with age, modulates membrane-embedded Aβ oligomerization.

Effects of All-Atom Molecular Mechanics Force Fields on Amyloid Peptide Assembly: The Case of Aβ16-22 Dimer

We investigated the effects of 17 widely used atomistic molecular mechanics force fields (MMFFs) on the structures and kinetics of amyloid peptide assembly. To this end, we performed large-scale all-atom molecular dynamics simulations in explicit water on the dimer of the seven-residue fragment of the Alzheimer's amyloid-β peptide, Aβ16-22, for a total time of 0.34 ms. We compared the effects of these MMFFs by analyzing various global reaction coordinates, secondary structure contents, the fibril population, the in-register and out-of-register architectures, and the fibril formation time at 310 K. While the AMBER94, AMBER99, and AMBER12SB force fields do not predict any β-sheets, the seven force fields, AMBER96, GROMOS45a3, GROMOS53a5, GROMOS53a6, GROMOS43a1, GROMOS43a2, and GROMOS54a7, form β-sheets rapidly. In contrast, the following five force fields, AMBER99-ILDN, AMBER14SB, CHARMM22*, CHARMM36, and CHARMM36m, are the best candidates for studying amyloid peptide assembly, as they provide good balances in terms of structures and kinetics. We also investigated the assembly mechanisms of dimeric Aβ16-22 and found that the fibril formation rate is predominantly controlled by the total β-strand content.

Mechanistic insight into E22Q-mutation-induced antiparallel-to-parallel β-sheet transition of Aβ16−22fibrils: an all-atom simulation study

E22Q mutation of Aβ₁₆₋₂₂fibrils facilitates parallel β-sheet formation by enhancing Q22–Q22 hydrogen-bonding interaction and A21–A21, F20–F20, F19–F19 and V18–V18 hydrophobic interaction.

In Silico Structural Evaluation of Short Cationic Antimicrobial Peptides

Cationic peptides with antimicrobial properties are ubiquitous in nature and have been studied for many years in an attempt to design novel antibiotics. However, very few molecules are used in the clinic so far, sometimes due to their complexity but, mostly, as a consequence of the unfavorable pharmacokinetic profile associated with peptides. The aim of this work is to investigate cationic peptides in order to identify common structural features which could be useful for the design of small peptides or peptido-mimetics with improved drug-like properties and activity against Gram negative bacteria. Two sets of cationic peptides (AMPs) with known antimicrobial activity have been investigated. The first reference set comprised molecules with experimentally-known conformations available in the protein databank (PDB), and the second one was composed of short peptides active against Gram negative bacteria but with no significant structural information available. The predicted structures of the peptides from the first set were in excellent agreement with those experimentally-observed, which allowed analysis of the structural features of the second group using computationally-derived conformations. The peptide conformations, either experimentally available or predicted, were clustered in an “all vs. all” fashion and the most populated clusters were then analyzed. It was confirmed that these peptides tend to assume an amphipathic conformation regardless of the environment. It was also observed that positively-charged amino acid residues can often be found next to aromatic residues. Finally, a protocol was evaluated for the investigation of the behavior of short cationic peptides in the presence of a membrane-like environment such as dodecylphosphocholine (DPC) micelles. The results presented herein introduce a promising approach to inform the design of novel short peptides with a potential antimicrobial activity.

Optimal updating magnitude in adaptive flat-distribution sampling

We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.

Conformational Entropy as Collective Variable for Proteins

Many enhanced sampling methods rely on the identification of appropriate collective variables. For proteins, even small ones, finding appropriate descriptors has proven challenging. Here we suggest that the NMR S² order parameter can be used to this effect. We trace the validity of this statement to the suggested relation between S² and conformational entropy. Using the S² order parameter and a surrogate for the protein enthalpy in conjunction with metadynamics or variationally enhanced sampling, we are able to reversibly fold and unfold a small protein and draw its free energy at a fraction of the time that is needed in unbiased simulations. We also use S² in combination with the free energy flooding method to compute the unfolding rate of this peptide. We repeat this calculation at different temperatures to obtain the unfolding activation energy.

Multi-scale simulations of biological systems using the OPEP coarse-grained model

Biomolecules are complex machines that are optimized by evolution to properly fulfill or contribute to a variety of biochemical tasks in the cellular environment. Computer simulations based on quantum mechanics and atomistic force fields have been proven to be a powerful microscope for obtaining valuable insights into many biological, physical, and chemical processes. Many interesting phenomena involve, however, a time scale and a number of degrees of freedom, notably if crowding is considered, that cannot be explored at an atomistic resolution. To bridge the gap between reality and simulation, many different advanced computational techniques and coarse-grained (CG) models have been developed. Here, we report some applications of the CG OPEP protein model to amyloid fibril formation, the response of catch-bond proteins to two types of fluid flow, and interactive simulations to fold peptides with well-defined 3D structures or with intrinsic disorder.

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.

Computer Folding of RNA Tetraloops: Identification of Key Force Field Deficiencies

The computer-aided folding of biomolecules, particularly RNAs, is one of the most difficult challenges in computational structural biology. RNA tetraloops are fundamental RNA motifs playing key roles in RNA folding and RNA-RNA and RNA-protein interactions. Although state-of-the-art Molecular Dynamics (MD) force fields correctly describe the native state of these tetraloops as a stable free-energy basin on the microsecond time scale, enhanced sampling techniques reveal that the native state is not the global free energy minimum, suggesting yet unidentified significant imbalances in the force fields. Here, we tested our ability to fold the RNA tetraloops in various force fields and simulation settings. We employed three different enhanced sampling techniques, namely, temperature replica exchange MD (T-REMD), replica exchange with solute tempering (REST2), and well-tempered metadynamics (WT-MetaD). We aimed to separate problems caused by limited sampling from those due to force-field inaccuracies. We found that none of the contemporary force fields is able to correctly describe folding of the 5'-GAGA-3' tetraloop over a range of simulation conditions. We thus aimed to identify which terms of the force field are responsible for this poor description of TL folding. We showed that at least two different imbalances contribute to this behavior, namely, overstabilization of base-phosphate and/or sugar-phosphate interactions and underestimated stability of the hydrogen bonding interaction in base pairing. The first artifact stabilizes the unfolded ensemble, while the second one destabilizes the folded state. The former problem might be partially alleviated by reparametrization of the van der Waals parameters of the phosphate oxygens suggested by Case et al., while in order to overcome the latter effect we suggest local potentials to better capture hydrogen bonding interactions.

Predicting unfolding thermodynamics and stable intermediates for alanine-rich helical peptides with the aid of coarse-grained molecular simulation

This report focuses on the molecular-level processes and thermodynamics of unfolding of a series of helical peptides using a coarse-grained (CG) molecular model. The CG model was refined to capture thermodynamics and structural changes as a function of temperature for a set of published peptide sequences. Circular dichroism spectroscopy (CD) was used to experimentally monitor the temperature-dependent conformational changes and stability of published peptides and new sequences introduced here. The model predictions were quantitatively or semi-quantitatively accurate in all cases. The simulations and CD results showed that, as expected, in most cases the unfolding of helical peptides is well described by a simply 2-state model, and conformational stability increased with increased length of the helices. A notable exception in a 19-residue helix was when two Ala residues were each replaced with Phe. This stabilized a partly unfolded intermediate state via hydrophobic contacts, and also promoted aggregates at higher peptide concentrations.

A critical assessment of hidden markov model sub-optimal sampling strategies applied to the generation of peptide 3D models

Hidden Markov Model derived structural alphabets are a probabilistic framework in which the complete conformational space of a peptidic chain is described in terms of probability distributions that can be sampled to identify conformations of largest probabilities. Here, we assess how three strategies to sample sub-optimal conformations-Viterbi k-best, forward backtrack and a taboo sampling approach-can lead to the efficient generation of peptide conformations. We show that the diversity of sampling is essential to compensate biases introduced in the estimates of the probabilities, and we find that only the forward backtrack and a taboo sampling strategies can efficiently generate native or near-native models. Finally, we also find such approaches are as efficient as former protocols, while being one order of magnitude faster, opening the door to the large scale de novo modeling of peptides and mini-proteins. © 2016 Wiley Periodicals, Inc.

Impact of the A2V Mutation on the Heterozygous and Homozygous Aβ1-40 Dimer Structures from Atomistic Simulations

The A2V mutation was reported to protect from Alzheimer's disease in its heterozygous form and cause an early Alzheimer's disease type dementia in its homozygous form. Experiments showed that the aggregation rate follows the order A2V > WT (wild-type) > A2V-WT. To understand the impact of this mutation, we carried out replica exchange molecular dynamics simulations of Aβ1-40 WT-A2V and A2V-A2V dimers and compared to the WT dimer. Our atomistic simulations reveal that the mean secondary structure remains constant, but there are substantial differences in the intramolecular and intermolecular conformations upon single and double A2V mutation. Upon single mutation, the intrinsic disorder is reduced, the intermolecular potential energies are reduced, the population of intramolecular three-stranded β-sheets is increased, and the number of all α dimer topologies is decreased. Taken together, these results offer an explanation for the reduced aggregation rate of the Aβ1-40 A2V-WT peptides and the protective effect of A2V in heterozygotes.

Self-aggregation and coaggregation of the p53 core fragment with its aggregation gatekeeper variant

Recent studies suggested that p53 aggregation can lead to loss-of-function (LoF), dominant-negative (DN) and gain-of-function (GoF) effects, with adverse cancer consequences. The p53 aggregation-nucleating (251)ILTIITL(257) fragment is a key segment in wild-type p53 aggregation; however, an I254R mutation can prevent it. It was suggested that self-assembly of wild-type p53 and its cross-interaction with mutants differ from the classical amyloid nucleation-growth mechanism. Here, using replica exchange molecular dynamics (REMD) simulations, we studied the cross-interactions of this p53 core fragment and its aggregation rescue I254R mutant. We found that the core fragment displays strong aggregation propensity, whereas the gatekeeper I254R mutant tends to be disordered, consistent with experiments. Our cross-interaction results reveal that the wild-type p53 fragment promotes β-sheet formation of the I254R mutant by shifting the disordered mutant peptides into aggregating states. As a result, the system has similar oligomeric structures, inter-peptide interactions and free energy landscape as the wild type fragment does, revealing a prion-like process. We also found that in the cross-interaction system, the wild-type species has higher tendency to interact with the mutant than with itself. This phenomenon illustrates synergistic effects between the p53 (251)ILTIITL(257) fragment and the mutant resembling prion cross-species propagation, cautioning against exploiting it in drug discovery.

Enhanced, targeted sampling of high-dimensional free-energy landscapes using variationally enhanced sampling, with an application to chignolin

The capabilities of molecular simulations have been greatly extended by a number of widely used enhanced sampling methods that facilitate escaping from metastable states and crossing large barriers. Despite these developments there are still many problems which remain out of reach for these methods which has led to a vigorous effort in this area. One of the most important problems that remains unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily described by a small number of collective variables. In this work we demonstrate a new way to compute free-energy landscapes of high dimensionality based on the previously introduced variationally enhanced sampling, and we apply it to the miniprotein chignolin.

Structures of the Alzheimer's Wild-Type Aβ1-40 Dimer from Atomistic Simulations

We have studied the dimer of amyloid beta peptide Aβ of 40 residues by means of all-atom replica exchange molecular dynamics. The Aβ-dimers have been found to be the smallest toxic species in Alzheimer's disease, but their inherent flexibilities have precluded structural characterization by experimental methods. Though the 24-μs-scale simulation reveals a mean secondary structure of 18% β-strand and 10% α helix, we find transient configurations with an unstructured N-terminus and multiple β-hairpins spanning residues 17-21 and 30-36, but the antiparallel and perpendicular peptide orientations are preferred over the parallel organization. Short-lived conformational states also consist of all α topologies, and one compact peptide with β-sheet structure stabilized by a rather extended peptide with α-helical content. Overall, this first all-atom study provides insights into the equilibrium structure of the Aβ1-40 dimer in aqueous solution, opening a new avenue for a comprehensive understanding of the impact of pathogenic and protective mutations in early-stage Alzheimer's disease on a molecular level.