Graphical abstract

Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D) and amyotrophic lateral sclerosis (ALS) research, respectively for over many years.While SOD1 is a globular protein with a well-defined 3D structure, the Aβ, tau and α-synuclein proteins belong to the class of intrinsically disordered proteins (IDPs). IDPs are also known to play a critical role in many cellular functions such as signal transduction, cell growth, binding with DNA and RNA, and transcription, and are implicated in the development of cardiovascular problems and cancers 29 . The IDPs involved in neurodegenerative diseases have a few aggregation-prone regions and overall all IDPs have a low mean hydrophobicity and a high mean net charge 30 .IDPs are structurally flexible and lack stable secondary structures in aqueous solution. When isolated, they behave as polymers in a good solvent and their radii of gyration are well described by the Flory scaling law. 31 The insolubility and high self-assembly propensity of IDPs implicated in degenerative diseases have prevented high-resolution structural determination by solution nuclear magnetic resolution (NMR) and X-ray diffraction experiments. Local information at all aggregation steps can be, however, obtained by chemical shifts, residual coupling constants, and J-couplings from NMR, exchange hydrogen/deuterium (H/D) NMR, Raman spectroscopy; and secondary structure from fast Fourier infrared spectroscopy (FTIR) or circular dichroism (CD). Long-range tertiary contacts can be deduced from paramagnetic relaxation enhancement (PRE) NMR spectroscopy and single molecule Förster resonance energy transfer (sm-FRET), and short-range distance contacts can be extracted by cross linked residues determined by mass spectrometry (MS). Low-resolution 3D information of monomers and oligomers can be obtained by ion-mobility mass-spectrometry data (IM/MS) providing cross-collision sections, dynamic light scattering (DLS), pulse field gradient NMR spectroscopy and fluorescence correlation spectroscopy (FCS) providing hydrodynamics radius, small-angle X-ray scattering (SAXS) and small-angle neutron scattering (SANS), atomic force microscopy (AFM) and transmission electron microscopy (TEM) providing height features of the aggregates, as reported by some o...

Nonfibrillar soluble oligomers, which are intermediates in the transition from monomers to amyloid fibrils, may be the toxic species in Alzheimer's disease. To monitor the early events that direct assembly of amyloidogenic peptides we probe the dynamics of formation of (A␤ 16 -22)n by adding a monomer to a preformed (A␤ 16 -22)n؊1 (n ‫؍‬ 4 -6) oligomer in which the peptides are arranged in an antiparallel ␤-sheet conformation. All atom molecular dynamics simulations in water and multiple long trajectories, for a cumulative time of 6.9 s, show that the oligomer grows by a two-stage dock-lock mechanism. The largest conformational change in the added disordered monomer occurs during the rapid (Ϸ50 ns) first dock stage in which the ␤-strand content of the monomer increases substantially from a low initial value. In the second slow-lock phase, the monomer rearranges to form in register antiparallel structures. Surprisingly, the mobile structured oligomers undergo large conformational changes in order to accommodate the added monomer. The time needed to incorporate the monomer into the fluid-like oligomer grows even when n ‫؍‬ 6, which suggests that the critical nucleus size must exceed six. Stable antiparallel structure formation exceeds hundreds of nanoseconds even though frequent interpeptide collisions occur at elevated monomer concentrations used in the simulations. The dock-lock mechanism should be a generic mechanism for growth of oligomers of amyloidogenic peptides.T here is intense interest in determining the structures, kinetics, and growth mechanisms of amyloid fibrils (1-8) because they are associated with a number of diseases such as Alzheimer's (9) and Parkinson's (6) disease as well as prion pathology (10). Recently, significant progress has been made in determining the structures of amyloid fibrils (1,(11)(12)(13). The structures of fibrils of a number of peptides including A␤ 1-40 and A␤ 1-42 that have been proposed using constraints obtained from solid state NMR (13) are also consistent with molecular dynamics simulations (14). In addition, a high resolution crystal structure of peptides extracted from N-terminal segments of Sup35 has been recently reported (15). These studies have confirmed that many peptides, which are unrelated by sequence, adopt the characteristic cross ␤-pattern in the fibril state.It is also important to understand the mechanisms of their formation starting from monomers because it is becoming increasingly clear that the nonfibrillar intermediates may be the toxic species in at least the Alzheimer's disease (9). Experimental characterization of the mechanism of formation of oligomers and their structures is difficult because of their diverse morphologies and rapid conformational fluctuations (16-19). Molecular dynamics (MD) simulations (14,16,20) can not only identify the interactions that drive the oligomer formation, but also can provide a molecular picture of the dynamics of the early events in the route to amyloid fibrils (16).In a previous study, we investigated the factor...

The aim of this work is to investigate the effects of molecular mechanics force fields on amyloid peptide assembly. To this end, we performed extensive replica exchange molecular dynamics (REMD) simulations on the monomer, dimer and trimer of the seven-residue fragment of the Alzheimer's amyloid-β peptide, Aβ(16-22), using the AMBER99, GROMOS96 and OPLS force fields. We compared the force fields by analysing the resulting global and local structures as well as the free energy landscapes at 300 K. We show that AMBER99 strongly favors helical structures for the monomer and does not predict any β-sheet structure for the dimer and trimer. In contrast, the dimer and trimer modeled by GROMOS96 form antiparallel β-sheet structures, while OPLS predicts diverse structures. Overall, the free energy landscapes obtained by three force fields are very different, and we also note a weak structural dependence of our results on temperature. The implications of this computational study on amyloid oligomerization, fibril growth and inhibition are also discussed.

The effects of beta-sheet breaker peptides KLVFF and LPFFD on the oligomerization of amyloid peptides were studied by all-atom simulations. It was found that LPFFD interferes the aggregation of Aβ(16-22) peptides to a greater extent than does KLVFF. Using the molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) method, we found that the former binds more strongly to Aβ(16-22). Therefore, by simulations, we have clarified the relationship between aggregation rates and binding affinity: the stronger the ligand binding, the slower the oligomerization process. The binding affinity of pentapeptides to full-length peptide Aβ(1-40) and its mature fibrils has been considered using the Autodock and MM-PBSA methods. The hydrophobic interaction between ligands and receptors plays a more important role for association than does hydrogen bonding. The influence of beta-sheet breaker peptides on the secondary structures of monomer Aβ(1-40) was studied in detail, and it turns out that, in their presence, the total beta-sheet content can be enhanced. However, the aggregation can be slowed because the beta-content is reduced in fibril-prone regions. Both pentapeptides strongly bind to monomer Aβ(1-40), as well as to mature fibrils, but KLVFF displays a lower binding affinity than LPFFD. Our findings are in accord with earlier experiments that both of these peptides can serve as prominent inhibitors. In addition, we predict that LPFFD inhibits/degrades the fibrillogenesis of full-length amyloid peptides better than KLVFF. This is probably related to a difference in their total hydrophobicities in that the higher the hydrophobicity, the lower the inhibitory capacity. The GROMOS96 43a1 force field with explicit water and the force field proposed by Morris et al. (Morris et al. J. Comput. Chem. 1998, 19, 1639 ) were employed for all-atom molecular dynamics simulations and Autodock experiments, respectively.

The 2019 novel coronavirus (SARS-CoV-2) epidemic, which was first reported in December 2019 in Wuhan, China, was declared a pandemic by the World Health Organization in March 2020. Genetically, SARS-CoV-2 is closely related to SARS-CoV, which caused a global epidemic with 8096 confirmed cases in more than 25 countries from 2002 to 2003. Given the significant morbidity and mortality rate, the current pandemic poses a danger to all of humanity, prompting us to understand the activity of SARS-CoV-2 at the atomic level. Experimental studies have revealed that spike proteins of both SARS-CoV-2 and SARS-CoV bind to angiotensin-converting enzyme 2 (ACE2) before entering the cell for replication. However, the binding affinities reported by different groups seem to contradict each other. Wrapp et al. ( Science 2020 , 367 , 1260–1263) showed that the spike protein of SARS-CoV-2 binds to the ACE2 peptidase domain (ACE2-PD) more strongly than does SARS-CoV, and this fact may be associated with a greater severity of the new virus. However, Walls et al. ( Cell 2020 , 181 , 281–292) reported that SARS-CoV-2 exhibits a higher binding affinity, but the difference between the two variants is relatively small. To understand the binding mechnism and experimental results, we investigated how the receptor binding domain (RBD) of SARS-CoV (SARS-CoV-RBD) and SARS-CoV-2 (SARS-CoV-2-RBD) interacts with a human ACE2-PD using molecular modeling. We applied a coarse-grained model to calculate the dissociation constant and found that SARS-CoV-2 displays a 2-fold higher binding affinity. Using steered all-atom molecular dynamics simulations, we demonstrate that, like a coarse-grained simulation, SARS-CoV-2-RBD was associated with ACE2-PD more strongly than was SARS-CoV-RBD, as evidenced by a higher rupture force and larger pulling work. We show that the binding affinity of both viruses to ACE2 is driven by electrostatic interactions.

We show, that the 2D XY-model with random phase shifts exhibits for low temperature and small disorder a phase with quasi-long-range order, and that the transition to the disordered phase is not reentrant. These results are obtained by heuristic arguments, an analytical renormalization group calculation, and a numerical Migdal-Kadanoff renormalization group treatment. Previous predictions of reentrance are found to fail due to an overestimation of the vortex pair density as a consequence of independent dipole approximations. At positions, where vortex pairs are energetically favored by disorder, their statistics becomes effectively fermionic. The results may have implications for a large number of related models.We reconsider in this paper the 2-dimensional XYmodelwith quenched random phase shifts A ij on the bonds, where i, j run over the sites of a square lattice. For simplicity we assume, that the A ij on different bonds are uncorrelated and gaussian distributed with mean zero and variance σ. Model (1) describes e.g. 2-dimensional XY-magnets with random Dzyaloshinskii-Moriya interaction [1]. Other realizations are given by Josephson-junction arrays with positional disorder [2] and model vortex glasses [3]. In particular, in the case of the so-called gauge glass model, one assumes A ij to be uniformly distributed between 0 and 2π. We expect, that our model with gaussian disorder is equivalent to the gauge glass model when σ → ∞.For vanishing A ij model (1) undergoes a Kosterlitz-Thouless (KT) transition, at which the spin-spin correlation exponent η jumps from 1/4 to zero [4].Weak disorder, σ ≪ 1, should not change much this picture. In the spin wave approximation one obtains η = 1 2π (T /J + σ), which remains now finite even at T = 0. The features of the KT-transition are essentially preserved, but the transition is shifted to lower temperatures and the jump of η at the transition is diminished [1]. The actual transition temperature T c (σ) ≤ T + (σ) depends on the bare value for the vortex core energy E c , here T ± = π 4 J[1±(1 − 8σ/π) 1/2 ]. In the limit E c → ∞,Strong disorder will suppress the quasi-long-range order of the KT phase [3].In particular, if Q = 1 2π A ij is of the order one, vortices are generated even at zero temperature. Here denotes the sum over the four bonds of an elementary plaquette. Rubinstein, Shraiman and Nelson (RSN) [1] extended the Coulomb gas description of the KT-transition [4]to the presence of randomly frozen dipoles arising from the random phase shifts. Surprisingly, they found a second (reentrant) transition at T re (σ) (≤ T − (σ)) to a disordered phase at low temperatures (see Fig. 1). T re (σ) bends towards higher temperatures for increasing disorder. The two lines T ± merge at σ c = π/8. For σ > σ c there is no ordered phase. The precise value of T re (σ) depends again on E c . Similar results were obtained in Ref. [2].Korshunov [5] has argued, that the intermediate phase in the range T re (σ) < T < T c (σ) with quasi-long-range order is probably not stable...

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