Are long-range structural correlations behind the aggregration phenomena of polyglutamine diseases?

Reviewing the Structure-Function Paradigm in Polyglutamine Disorders: A Synergistic Perspective on Theoretical and Experimental Approaches

Polyglutamine (polyQ) disorders are a group of neurodegenerative diseases characterized by the excessive expansion of CAG (cytosine, adenine, guanine) repeats within host proteins. The quest to unravel the complex diseases mechanism has led researchers to adopt both theoretical and experimental methods, each offering unique insights into the underlying pathogenesis. This review emphasizes the significance of combining multiple approaches in the study of polyQ disorders, focusing on the structure-function correlations and the relevance of polyQ-related protein dynamics in neurodegeneration. By integrating computational/theoretical predictions with experimental observations, one can establish robust structure-function correlations, aiding in the identification of key molecular targets for therapeutic interventions. PolyQ proteins' dynamics, influenced by their length and interactions with other molecular partners, play a pivotal role in the polyQ-related pathogenic cascade. Moreover, conformational dynamics of polyQ proteins can trigger aggregation, leading to toxic assembles that hinder proper cellular homeostasis. Understanding these intricacies offers new avenues for therapeutic strategies by fine-tuning polyQ kinetics, in order to prevent and control disease progression. Last but not least, this review highlights the importance of integrating multidisciplinary efforts to advancing research in this field, bringing us closer to the ultimate goal of finding effective treatments against polyQ disorders.

Pathologic polyglutamine aggregation begins with a self-poisoning polymer crystal

A long-standing goal of amyloid research has been to characterize the structural basis of the rate-determining nucleating event. However, the ephemeral nature of nucleation has made this goal unachievable with existing biochemistry, structural biology, and computational approaches. Here, we addressed that limitation for polyglutamine (polyQ), a polypeptide sequence that causes Huntington's and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. To identify essential features of the polyQ amyloid nucleus, we used a direct intracellular reporter of self-association to quantify frequencies of amyloid appearance as a function of concentration, conformational templates, and rational polyQ sequence permutations. We found that nucleation of pathologically expanded polyQ involves segments of three glutamine (Q) residues at every other position. We demonstrate using molecular simulations that this pattern encodes a four-stranded steric zipper with interdigitated Q side chains. Once formed, the zipper poisoned its own growth by engaging naive polypeptides on orthogonal faces, in a fashion characteristic of polymer crystals with intramolecular nuclei. We further show that self-poisoning can be exploited to block amyloid formation, by genetically oligomerizing polyQ prior to nucleation. By uncovering the physical nature of the rate-limiting event for polyQ aggregation in cells, our findings elucidate the molecular etiology of polyQ diseases.

Pathologic polyglutamine aggregation begins with a self-poisoning polymer crystal

A long-standing goal of amyloid research has been to characterize the structural basis of the rate-determining nucleating event. However, the ephemeral nature of nucleation has made this goal unachievable with existing biochemistry, structural biology, and computational approaches. Here, we addressed that limitation for polyglutamine (polyQ), a polypeptide sequence that causes Huntington's and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. To identify essential features of the polyQ amyloid nucleus, we used a direct intracellular reporter of self-association to quantify frequencies of amyloid appearance as a function of concentration, conformational templates, and rational polyQ sequence permutations. We found that nucleation of pathologically expanded polyQ involves segments of three glutamine (Q) residues at every other position. We demonstrate using molecular simulations that this pattern encodes a four-stranded steric zipper with interdigitated Q side chains. Once formed, the zipper poisoned its own growth by engaging naive polypeptides on orthogonal faces, in a fashion characteristic of polymer crystals with intramolecular nuclei. We further show that self-poisoning can be exploited to block amyloid formation, by genetically oligomerizing polyQ prior to nucleation. By uncovering the physical nature of the rate-limiting event for polyQ aggregation in cells, our findings elucidate the molecular etiology of polyQ diseases.

Increasing the Sampling Efficiency of Protein Conformational Change by Combining a Modified Replica Exchange Molecular Dynamics and Normal Mode Analysis

Understanding conformational change at an atomic level is significant when determining a protein functional mechanism. Replica exchange molecular dynamics (REMD) is a widely used enhanced sampling method to explore protein conformational space. However, REMD with an explicit solvent model requires huge computational resources, immensely limiting its application. In this study, a variation of parallel tempering metadynamics (PTMetaD) with the omission of solvent-solvent interactions in exchange attempts and the use of low-frequency modes calculated by normal-mode analysis (NMA) as collective variables (CVs), namely ossPTMetaD, is proposed with the aim to accelerate MD simulations simultaneously in temperature and geometrical spaces. For testing the performance of ossPTMetaD, five protein systems with diverse biological functions and motion patterns were selected, including large-scale domain motion (AdK), flap movement (HIV-1 protease and BACE1), and DFG-motif flip in kinases (p38α and c-Abl). The simulation results showed that ossPTMetaD requires much fewer numbers of replicas than temperature REMD (T-REMD) with a reduction of ∼70% to achieve a similar exchange ratio. Although it does not obey the detailed balance condition, ossPTMetaD provides consistent results with T-REMD and experimental data. The high accessibility of the large conformational change of protein systems by ossPTMetaD, especially in simulating the very challenging DFG-motif flip of protein kinases, demonstrated its high efficiency and robustness in the characterization of the large-scale protein conformational change pathway and associated free energy profile.

Structure and Dynamics of DNA and RNA Double Helices of CAG and GAC Trinucleotide Repeats

CAG trinucleotide repeats are known to cause 10 late-onset progressive neurodegenerative disorders as the repeats expand beyond a threshold, whereas GAC repeats are associated with skeletal dysplasias and expand from the normal five to a maximum of seven repeats. The TR secondary structure is believed to play a role in CAG expansions. We have carried out free energy and molecular dynamics studies to determine the preferred conformations of the A-A noncanonical pairs in (CAG)_n and (GAC)_n trinucleotide repeats (n = 1, 4) and the consequent changes in the overall structure of the RNA and DNA duplexes. We find that the global free energy minimum corresponds to A-A pairs stacked inside the core of the helix with anti-anti conformations in RNA and (high-anti)-(high-anti) conformations in DNA. The next minimum corresponds to anti-syn conformations, whereas syn-syn conformations are higher in energy. Transition rates of the A-A conformations are higher for RNA than DNA. Mechanisms for these various transitions are identified. Additional structural and dynamical aspects of the helical conformations are explored, with a focus on contrasting CAG and GAC duplexes. The neutralizing ion distribution around the noncanonical pairs is described.

Conformational Heterogeneity of the HIV Envelope Glycan Shield

To better understand the conformational properties of the glycan shield covering the surface of the HIV gp120/gp41 envelope (Env) trimer, and how the glycan shield impacts the accessibility of the underlying protein surface, we performed enhanced sampling molecular dynamics (MD) simulations of a model glycosylated HIV Env protein and related systems. Our simulation studies revealed a conformationally heterogeneous glycan shield with a network of glycan-glycan interactions more extensive than those observed to date. We found that partial preorganization of the glycans potentially favors binding by established broadly neutralizing antibodies; omission of several specific glycans could increase the accessibility of other glycans or regions of the protein surface to antibody or CD4 receptor binding; the number of glycans that can potentially interact with known antibodies is larger than that observed in experimental studies; and specific glycan conformations can maximize or minimize interactions with individual antibodies. More broadly, the enhanced sampling MD simulations described here provide a valuable tool to guide the engineering of specific Env glycoforms for HIV vaccine design.

Molecular dynamics analysis of the aggregation propensity of polyglutamine segments

Protein misfolding and aggregation is a pathogenic feature shared among at least ten polyglutamine (polyQ) neurodegenerative diseases. While solvent-solution interaction is a key factor driving protein folding and aggregation, the solvation properties of expanded polyQ tracts are not well understood. By using GPU-enabled all-atom molecular dynamics simulations of polyQ monomers in an explicit solvent environment, this study shows that solvent-polyQ interaction propensity decreases as the lengths of polyQ tract increases. This study finds a predominance in long-distance interactions between residues far apart in polyQ sequences with longer polyQ segments, that leads to significant conformational differences. This study also indicates that large loops, comprised of parallel β-structures, appear in long polyQ tracts and present new aggregation building blocks with aggregation driven by long-distance intra-polyQ interactions. Finally, consistent with previous observations using coarse-grain simulations, this study demonstrates that there is a gain in the aggregation propensity with increased polyQ length, and that this gain is correlated with decreasing ability of solvent-polyQ interaction. These results suggest the modulation of solvent-polyQ interactions as a possible therapeutic strategy for treating polyQ diseases.

Enhanced conformational sampling using replica exchange with concurrent solute scaling and hamiltonian biasing realized in one dimension

Replica exchange (REX) is a powerful computational tool for overcoming the quasi-ergodic sampling problem of complex molecular systems. Recently, several multidimensional extensions of this method have been developed to realize exchanges in both temperature and biasing potential space or the use of multiple biasing potentials to improve sampling efficiency. However, increased computational cost due to the multidimensionality of exchanges becomes challenging for use on complex systems under explicit solvent conditions. In this study, we develop a one-dimensional (1D) REX algorithm to concurrently combine the advantages of overall enhanced sampling from Hamiltonian solute scaling and the specific enhancement of collective variables using Hamiltonian biasing potentials. In the present Hamiltonian replica exchange method, termed HREST-BP, Hamiltonian solute scaling is applied to the solute subsystem, and its interactions with the environment to enhance overall conformational transitions and biasing potentials are added along selected collective variables associated with specific conformational transitions, thereby balancing the sampling of different hierarchical degrees of freedom. The two enhanced sampling approaches are implemented concurrently allowing for the use of a small number of replicas (e.g., 6 to 8) in 1D, thus greatly reducing the computational cost in complex system simulations. The present method is applied to conformational sampling of two nitrogen-linked glycans (N-glycans) found on the HIV gp120 envelope protein. Considering the general importance of the conformational sampling problem, HREST-BP represents an efficient procedure for the study of complex saccharides, and, more generally, the method is anticipated to be of general utility for the conformational sampling in a wide range of macromolecular systems.

Amyloid Properties of Asparagine and Glutamine in Prion-like Proteins

Sequences rich in glutamine (Q) and asparagine (N) are intrinsically disordered in monomeric form, but can aggregate into highly ordered amyloids, as seen in Q/N-rich prion domains (PrDs). Amyloids are fibrillar protein aggregates rich in β-sheet structures that can self-propagate through protein-conformational chain reactions. Here, we present a comprehensive theoretical study of N/Q-rich peptides, including sequences found in the yeast Sup35 PrD, in parallel and antiparallel β-sheet aggregates, and probe via fully atomistic molecular dynamics simulations all their possible steric-zipper interfaces in order to determine their protofibril structure and their relative stability. Our results show that polyglutamine aggregates are more stable than polyasparagine aggregates. Enthalpic contributions to the free energy favor the formation of polyQ protofibrils, while entropic contributions favor the formation of polyN protofibrils. The considerably larger phase space that disordered polyQ must sample on its way to aggregation probably is at the root of the associated slower kinetics observed experimentally. When other amino acids are present, such as in the Sup35 PrD, their shorter side chains favor steric-zipper formation for N but not Q, as they preclude the in-register association of the long Q side chains.

Structural determinants of polyglutamine protofibrils and crystallites

Nine inherited neurodegenerative diseases are associated with the expansion of the CAG codon. Once the translated polyglutamine expansion becomes longer than ~36 residues, it triggers the formation of intraneural protein aggregates that often display the signature of cross-β amyloid fibrils. Here, we use fully atomistic molecular dynamics simulations to probe the structural stability and conformational dynamics of both previously proposed and new polyglutamine aggregate models. We test the relative stability of parallel and antiparallel β sheets, and characterize possible steric interfaces between neighboring sheets and the effects of different alignments of the side-chain carboxamide dipoles. Results indicate that (i) different initial oligomer structures converge to crystals consistent with available diffraction data, after undergoing cooperative side-chain rotational transitions and quarter-stagger displacements on a microsecond time scale, (ii) structures previously deemed stable on a hundred nanosecond time scale are unstable over the microsecond time scale, and (iii) conversely, structures previously deemed unstable did not account for the correct side-chain packing and once the correct symmetry is considered the structures become stable for over a microsecond, due to tightly interdigitated side chains, which lock into highly regular polar zippers with inter-side-chain and backbone-side-chain hydrogen bonds. With these insights, we built Q40 monomeric models with different combinations of arc and hairpin turns and tested them for stability. The stable monomers were further probed as a function of repeat length. Our results are consistent with the aggregation threshold. These results explain and reconcile previously reported experimental and model discrepancies about polyglutamine aggregate structures.

Secondary structure assignment for conformationally irregular peptides: comparison between DSSP, STRIDE and KAKSI

Secondary structure assignment codes were built to explore the regularities associated with the periodic motifs of proteins, such as those in backbone dihedral angles or in hydrogen bonds between backbone atoms. Precise structure assignment is challenging because real-life secondary structures are susceptible to bending, twist, fraying and other deformations that can distance them from their geometrical prototypes. Although results from codes such as DSSP and STRIDE converge in well-ordered structures, the agreement between the secondary structure assignments is known to deteriorate as the conformations become more distorted. Conformationally irregular peptides therefore offer a great opportunity to explore the differences between these codes. This is especially important for unfolded proteins and intrinsically disordered proteins, which are known to exhibit residual and/or transient secondary structure whose characterization is challenging. In this work, we have carried out Molecular Dynamics simulations of (relatively) disordered peptides, specifically gp41659-671 (ELLELDKWASLWN), the homopeptide polyasparagine (N18), and polyasparagine dimers. We have analyzed the resulting conformations with DSSP and STRIDE, based on hydrogen-bond patterns (and dihedral angles for STRIDE), and KAKSI, based on α-Carbon distances; and carefully characterized the differences in structural assignments. The full-sequence Segment Overlap (SOV) scores, that quantify the agreement between two secondary structure assignments, vary from 70% for gp41659-671 (STRIDE as reference) to 49% for N18 (DSSP as reference). Major differences are observed in turns, in the distinction between α and 310 helices, and in short parallel-sheet segments.

Computational Recipe for Efficient Description of Large-Scale Conformational Changes in Biomolecular Systems

Characterizing large-scale structural transitions in biomolecular systems poses major technical challenges to both experimental and computational approaches. On the computational side, efficient sampling of the configuration space along the transition pathway remains the most daunting challenge. Recognizing this issue, we introduce a knowledge-based computational approach toward describing large-scale conformational transitions using (i) nonequilibrium, driven simulations combined with work measurements and (ii) free energy calculations using empirically optimized biasing protocols. The first part is based on designing mechanistically relevant, system-specific reaction coordinates whose usefulness and applicability in inducing the transition of interest are examined using knowledge-based, qualitative assessments along with nonequilirbrium work measurements which provide an empirical framework for optimizing the biasing protocol. The second part employs the optimized biasing protocol resulting from the first part to initiate free energy calculations and characterize the transition quantitatively. Using a biasing protocol fine-tuned to a particular transition not only improves the accuracy of the resulting free energies but also speeds up the convergence. The efficiency of the sampling will be assessed by employing dimensionality reduction techniques to help detect possible flaws and provide potential improvements in the design of the biasing protocol. Structural transition of a membrane transporter will be used as an example to illustrate the workings of the proposed approach.

Driven Metadynamics: Reconstructing Equilibrium Free Energies from Driven Adaptive-Bias Simulations

We present a novel free-energy calculation method that constructively integrates two distinct classes of nonequilibrium sampling techniques, namely, driven (e.g., steered molecular dynamics) and adaptive-bias (e.g., metadynamics) methods. By employing nonequilibrium work relations, we design a biasing protocol with an explicitly time- and history-dependent bias that uses on-the-fly work measurements to gradually flatten the free-energy surface. The asymptotic convergence of the method is discussed, and several relations are derived for free-energy reconstruction and error estimation. Isomerization reaction of an atomistic polyproline peptide model is used to numerically illustrate the superior efficiency and faster convergence of the method compared with its adaptive-bias and driven components in isolation.

Reaction path ensemble of the B-Z-DNA transition: a comprehensive atomistic study

Since its discovery in 1979, left-handed Z-DNA has evolved from an in vitro curiosity to a challenging DNA structure with crucial roles in gene expression, regulation and recombination. A fundamental question that has puzzled researchers for decades is how the transition from B-DNA, the prevalent right-handed form of DNA, to Z-DNA is accomplished. Due to the complexity of the B–Z-DNA transition, experimental and computational studies have resulted in several different, apparently contradictory models. Here, we use molecular dynamics simulations coupled with state-of-the-art enhanced sampling techniques operating through non-conventional reaction coordinates, to investigate the B–Z-DNA transition at the atomic level. Our results show a complex free energy landscape, where several phenomena such as over-stretching, unpeeling, base pair extrusion and base pair flipping are observed resulting in interconversions between different DNA conformations such as B-DNA, Z-DNA and S-DNA. In particular, different minimum free energy paths allow for the coexistence of different mechanisms (such as zipper and stretch–collapse mechanisms) that previously had been proposed as independent, disconnected models. We find that the B–Z-DNA transition—in absence of other molecular partners—can encompass more than one mechanism of comparable free energy, and is therefore better described in terms of a reaction path ensemble.