Atomic-resolution Simulations Research Articles

3D feasibility of 2D RNA-RNA interaction paths by stepwise folding simulations.

The structure of an RNA, and even more so its interactions with other RNAs, provide valuable information about its function. Secondary structure-based tools for RNA-RNA interaction predictions provide a quick way to identify possible interaction targets and structures. However, these tools ignore the effect of steric hindrance on the tertiary (3D) structure level, and do not consider whether a suitable folding pathway exists to form the interaction. As a consequence, these tools often predict interactions that are unrealistically long and could be formed (in three dimensions) only by going through highly entangled intermediates. Here, we present a computational pipeline to assess whether a proposed secondary (2D) structure interaction is sterically feasible and reachable along a plausible folding pathway. To this end, we simulate the folding of a series of 3D structures along a given 2D folding path. To avoid the complexity of large-scale atomic resolution simulations, our pipeline uses coarse-grained 3D modeling and breaks up the folding path into small steps, each corresponding to the extension of the interaction by 1 or 2 bp. We apply our pipeline to analyze RNA-RNA interaction formation for three selected RNA-RNA complexes. We find that kissing hairpins, in contrast to interactions in the exterior loop, are difficult to extend and tend to get stuck at an interaction length of 6 bp. Our tool, including source code, documentation, and sample data, is available at www.github.com/irenekb/RRI-3D.

Peptide framework for screening the effects of amino acids on assembly.

Discovery of peptide domains with unique intermolecular interactions is essential for engineering peptide-based materials. Rather than attempting a brute-force approach, we instead identify a previously unexplored strategy for discovery and study of intermolecular interactions: “co-assembly of oppositely charged peptide” (CoOP), a framework that “encourages” peptide assembly by mixing two oppositely charged hexapeptides. We used an integrated computational and experimental approach, probed the free energy of association and probability of amino acid contacts during co-assembly with atomic-resolution simulations, and correlated them to the physical properties of the aggregates. We introduce CoOP with three examples: dialanine, ditryptophan, and diisoleucine. Our results indicated that the opposite charges initiate the assembly, and the subsequent stability is enhanced by the presence of an undisturbed hydrophobic core. CoOP represents a unique, simple, and elegant framework that can be used to identify the structure-property relationships of self-assembling peptide-based materials.

Atomic-Resolution Simulations Show Two Sequential Fusion Peptide Mechanisms in Influenza Membrane Fusion

Influenza viral membrane fusion is mediated by the hemagglutinin protein, and membrane-inserted fusion peptides are critical to the success of this process. However, the field lacks a mechanistic understanding of how fusion peptides act to cause fusion that can fully explain experimental phenotypes of fusion peptide mutants. We have performed the first atomic-resolution simulations of influenza membrane fusion, which demonstrate lipid tail protrusion and membrane bending as two sequential activities of the fusion peptides that are critical to fusion. Each of these is supported by previous experimental data and mechanistic hypotheses, but our simulations now place these, in sequence, as co-existing mechanistic requirements for fusion. A striking new finding is that the membrane-bending activity of fusion peptides is dependent on their N-terminal protonation state, which can in turn control the helical kink or hairpin that modulates fusion activity. These simulations thus provide a unified model for influenza membrane fusion capable of explaining how N-terminal fusion peptide mutations exert their effects. Furthermore, our model by which fusion peptides promote lipid tail protrusion and then membrane bending as sequential requirements may be generalized to explain the fusion behavior of other enveloped viruses.

Computer Simulations Predict High Structural Heterogeneity of Functional State of NMDA Receptors

N-methyl-D-aspartate receptors (NMDARs)—i.e., transmembrane proteins expressed in neurons—play a central role in the molecular mechanisms of learning and memory formation. It is unclear how the known atomic structures of NMDARs determined by x-ray crystallography and electron cryomicroscopy (18 published Protein Data Bank entries) relate to the functional states of NMDARs inferred from electrophysiological recordings (multiple closed, open, preopen, etc. states). We address this problem by using molecular dynamics simulations at atomic resolution, a method successfully applied in the past to much smaller biomolecules. Our simulations predict that several conformations of NMDARs with experimentally determined geometries, including four “nonactive” electron cryomicroscopy structures, rapidly interconvert on submicrosecond timescales and therefore may correspond to the same functional state of the receptor (specifically, one of the closed states). This conclusion is not trivial because these conformational transitions involve changes in certain interatomic distances as large as tens of Å. The simulations also predict differences in the conformational dynamics of the apo and holo (i.e., agonist and coagonist bound) forms of the receptor on the microsecond timescale. To our knowledge, five new conformations of NMDARs, with geometries joining various features from different known experimental structures, are also predicted by the model. The main limitation of this work stems from its limited sampling (30 μs of aggregate length of molecular dynamics trajectories). Though this level significantly exceeds the sampling in previous simulations of parts of NMDARs, it is still much lower than the sampling recently achieved for smaller biomolecules (up to a few milliseconds), thus precluding, in particular, the observation of transitions between different functional states of NMDARs. Despite this limitation, such computational predictions may guide further experimental studies on the structure, dynamics, and function of NMDARs, for example by suggesting optimal locations of spectroscopic probes. Overall, atomic resolution simulations provide, to our knowledge, a novel perspective on the structure and dynamics of NMDARs, complementing information obtained by experimental methods.

Simulations and Experiments Show a Mechanistic Role for Influenza Fusion Peptides in Membrane Bending and Fusion Stoichiometry

Membrane fusion by influenza virus is exquisitely sensitive to the N-terminal residues of the membrane-inserted fusion peptide. Just how single-residue substitutions at the N-terminus of this peptide can cause large changes in fusion phenotype and viral infectivity has remained a puzzle in the field. Here, we use a combination of atomic-resolution simulations of viral membrane fusion and fluorescence microscopy to probe the role of the fusion peptide N-terminus in controlling fusion behavior. Surprisingly, we find that the formation of highly curved fusion intermediates is highly sensitive to the N-terminus in simulations, and the fusion behavior of both mutant virus and hemagglutinin-expressing cells also suggests a difference in protein stoichiometry required for fusion between wild-type and mutant fusion peptides. Together, these data suggest mechanistic roles for the fusion peptide N-terminus that can be directly connected to fusion behavior and infectious outcomes, helping explain how these seemingly subtle changes to a membrane-inserted peptide can alter the behavior of the entire viral fusion machinery.

A fast image simulation algorithm for scanning transmission electron microscopy

Image simulation for scanning transmission electron microscopy at atomic resolution for samples with realistic dimensions can require very large computation times using existing simulation algorithms. We present a new algorithm named PRISM that combines features of the two most commonly used algorithms, namely the Bloch wave and multislice methods. PRISM uses a Fourier interpolation factor f that has typical values of 4–20 for atomic resolution simulations. We show that in many cases PRISM can provide a speedup that scales with f4 compared to multislice simulations, with a negligible loss of accuracy. We demonstrate the usefulness of this method with large-scale scanning transmission electron microscopy image simulations of a crystalline nanoparticle on an amorphous carbon substrate.

Characterizing the Conformational Landscape of Flavivirus Fusion Peptides via Simulation and Experiment.

Conformational changes in the envelope proteins of flaviviruses help to expose the highly conserved fusion peptide (FP), a region which is critical to membrane fusion and host cell infection, and which represents a significant target for antiviral drugs and antibodies. In principle, extended timescale atomic-resolution simulations may be used to characterize the dynamics of such peptides. However, the resultant accuracy is critically dependent upon both the underlying force field and sufficient conformational sampling. In the present study, we report a comprehensive comparison of three simulation methods and four force fields comprising a total of more than 40 μs of sampling. Additionally, we describe the conformational landscape of the FP fold across all flavivirus family members. All investigated methods sampled conformations close to available X-ray structures, but exhibited differently populated ensembles. The best force field / sampling combination was sufficiently accurate to predict that the solvated peptide fold is less ordered than in the crystallographic state, which was subsequently confirmed via circular dichroism and spectrofluorometric measurements. Finally, the conformational landscape of a mutant incapable of membrane fusion was significantly shallower than wild-type variants, suggesting that dynamics should be considered when therapeutically targeting FP epitopes.

DNA sequence-dependent ionic currents in ultra-small solid-state nanopores.

Measurements of ionic currents through nanopores partially blocked by DNA have emerged as a powerful method for characterization of the DNA nucleotide sequence. Although the effect of the nucleotide sequence on the nanopore blockade current has been experimentally demonstrated, prediction and interpretation of such measurements remain a formidable challenge. Using atomic resolution computational approaches, here we show how the sequence, molecular conformation, and pore geometry affect the blockade ionic current in model solid-state nanopores. We demonstrate that the blockade current from a DNA molecule is determined by the chemical identities and conformations of at least three consecutive nucleotides. We find the blockade currents produced by the nucleotide triplets to vary considerably with their nucleotide sequences despite having nearly identical molecular conformations. Encouragingly, we find blockade current differences as large as 25% for single-base substitutions in ultra small (1.6 nm × 1.1 nm cross section; 2 nm length) solid-state nanopores. Despite the complex dependence of the blockade current on the sequence and conformation of the DNA triplets, we find that, under many conditions, the number of thymine bases is positively correlated with the current, whereas the number of purine bases and the presence of both purines and pyrimidines in the triplet are negatively correlated with the current. Based on these observations, we construct a simple theoretical model that relates the ion current to the base content of a solid-state nanopore. Furthermore, we show that compact conformations of DNA in narrow pores provide the greatest signal-to-noise ratio for single base detection, whereas reduction of the nanopore length increases the ionic current noise. Thus, the sequence dependence of the nanopore blockade current can be theoretically rationalized, although the predictions will likely need to be customized for each nanopore type.

Insights into the Transport of Aqueous Quaternary Ammonium Cations: A Combined Experimental and Computational Study

This study focuses on understanding the relative effects of ammonium substituent groups (we primarily consider tetramethylammonium, benzyltrimethylammonium, and tetraethylammonium cations) and anion species (OH(-), HCO3(-), CO3(2-), Cl(-), and F(-)) on ion transport by combining experimental and computational approaches. We characterize transport experimentally using ionic conductivity and self-diffusion coefficients measured from NMR. These experimental results are interpreted using simulation methods to describe the transport of these cations and anions considering the effects of the counterion. It is particularly noteworthy that we directly probe cation and anion diffusion with pulsed gradient stimulated echo NMR and molecular dynamics simulations, corroborating these methods and providing a direct link between atomic-resolution simulations and macroscale experiments. By pairing diffusion measurements and simulations with residence times, we were able to understand the interplay between short-time and long-time dynamics with ionic conductivity. With experiment, we determined that solutions of benzyltrimethylammonium hydroxide have the highest ionic conductivity (0.26 S/cm at 65 °C), which appears to be due to differences for the ions in long-time diffusion and short-time water caging. We also examined the effect of CO2 on ionic conductivity in ammonium hydroxide solutions. CO2 readily reacts with OH(-) to form HCO(-)3 and is found to lower the solution ionic conductivity by almost 50%.

Computational studies of molecular machines: the ribosome

The past decade has produced an avalanche of experimental data on the structure and dynamics of the ribosome. Groundbreaking studies in structural biology and kinetics have placed important constraints on ribosome structural dynamics. However, a gulf remains between static structures and time dependent data. In particular, X-ray crystallography and cryo-EM studies produce static models of the ribosome in various states, but lack dynamic information. Single molecule studies produce information on the rates of transitions between these states but do not have high-resolution spatial information. Computational studies have aided in bridging this gap by providing atomic resolution simulations of structural fluctuations and transitions between configurations.

Structure and Dynamics of the Membrane-Bound Cytochrome P450 2C9

The microsomal, membrane-bound, human cytochrome P450 (CYP) 2C9 is a liver-specific monooxygenase essential for drug metabolism. CYPs require electron transfer from the membrane-bound CYP reductase (CPR) for catalysis. The structural details and functional relevance of the CYP-membrane interaction are not understood. From multiple coarse grained molecular simulations started with arbitrary configurations of protein-membrane complexes, we found two predominant orientations of CYP2C9 in the membrane, both consistent with experiments and conserved in atomic-resolution simulations. The dynamics of membrane-bound and soluble CYP2C9 revealed correlations between opening and closing of different tunnels from the enzyme's buried active site. The membrane facilitated the opening of a tunnel leading into it by stabilizing the open state of an internal aromatic gate. Other tunnels opened selectively in the simulations of product-bound CYP2C9. We propose that the membrane promotes binding of liposoluble substrates by stabilizing protein conformations with an open access tunnel and provide evidence for selective substrate access and product release routes in mammalian CYPs. The models derived here are suitable for extension to incorporate other CYPs for oligomerization studies or the CYP reductase for studies of the electron transfer mechanism, whereas the modeling procedure is generally applicable to study proteins anchored in the bilayer by a single transmembrane helix.

Molecular Mechanism of Selective Recruitment of Syk Kinases by the Membrane Antigen-Receptor Complex

ZAP-70 and Syk are essential tyrosine kinases in intracellular immunological signaling. Both contain an inhibitory SH2 domain tandem, which assembles onto the catalytic domain. Upon binding to doubly phosphorylated ITAM motifs on activated antigen receptors, the arrangement of the SH2 domains changes. From available structures, this event is not obviously conducive to dissociation of the autoinhibited complex, yet it ultimately translates into kinase activation through a mechanism not yet understood. We present a comprehensive theoretical study of this molecular mechanism, using atomic resolution simulations and free-energy calculations, totaling >10 μs of simulation time. Through these, we dissect the microscopic mechanism coupling stepwise ITAM engagement and SH2 tandem structural change and reveal key differences between ZAP-70 and Syk. Importantly, we show that a subtle conformational bias in the inter-SH2 connector causes ITAM to bind preferentially to kinase-dissociated tandems. We thus propose that phosphorylated antigen receptors selectively recruit kinases that are uninhibited and that the resulting population shift in the membrane vicinity sustains signal transduction.

Water Ordering at Membrane Interfaces Controls Fusion Dynamics

Membrane interfaces are critical to many cellular functions, yet the vast array of molecular components involved make the fundamental physics of interaction difficult to define. Water has been shown to play an important role in the dynamics of small biological systems, for example when trapped in hydrophobic regions, but the molecular details of water have generally been thought dispensable when considering large membrane interfaces. Nevertheless, spectroscopic data indicate that water has distinct, ordered behavior near membrane surfaces. While coarse-grained simulations have achieved success recently in aiding understanding the dynamics of membrane assemblies, it is natural to ask, does the missing chemical nature of water play an important role? We have therefore performed atomic-resolution simulations of vesicle fusion to understand the role of chemical detail, particularly the molecular structure of water, in membrane fusion and at membrane interfaces more generally. These membrane interfaces present a form of hydrophilic confinement, yielding surprising, non-bulk-like water behavior.

First-passage-time analysis of atomic-resolution simulations of the ionic transport in a bacterial porin

We have studied the dynamics of chloride and potassium ions in the interior of the Outer membrane porin F (OmpF) under the influence of an external electric field. From the results of extensive all-atom molecular dynamics (MD) simulations of the system, we computed several first-passage-time (FPT) quantities to characterize the dynamics of the ions in the interior of the channel. Such FPT quantities obtained from MD simulations demonstrate that it is not possible to describe the dynamics of chloride and potassium ions inside the whole channel with a single constant diffusion coefficient. However, we showed that a valid, statistically rigorous description in terms of a constant diffusion coefficient D and an effective deterministic force F(eff) can be obtained after appropriate subdivision of the channel in different regions suggested by the x-ray structure. These results have important implications for popular simplified descriptions of channels based on the one-dimensional Poisson-Nernst-Planck equations. Also, the effect of entropic barriers on the diffusion of the ions is identified and briefly discussed.

A first Passage Time Analysis of Atomic-Resolution Simulations of the Ionic Transport in a Bacterial Porin

We have studied the dynamics of chloride and potassium ions in the interior of the OmpF porin under the influence of an external electric field. From the results of extensive all-atom molecular dynamics simulations of the system we computed several first passage time (FPT) quantities to characterize the dynamics of the ions in the interior of the channel. Such FPT quantities obtained from MD simulations demonstrate that it is not possible to describe the dynamics of chloride and potassium ions inside the whole channel with a single constant diffusion coefficient. However, we showed that a valid, statistically rigorous, description in terms of a constant diffusion coefficient D and an effective deterministic force Feff can be obtained after appropriate subdivison of the channel in different regions suggested by the X-ray structure. These results have important implications for popular simplified descriptions of channels based on the 1D Poisson-Nernst-Planck (PNP) equations. Also, the effect of entropic barriers on the diffusion of the ions is identified and briefly discussed.

Atomic-Resolution Simulations Predict a Transition State for Vesicle Fusion Defined by Contact of a Few Lipid Tails

Membrane fusion is essential to both cellular vesicle trafficking and infection by enveloped viruses. While the fusion protein assemblies that catalyze fusion are readily identifiable, the specific activities of the proteins involved and nature of the membrane changes they induce remain unknown. Here, we use many atomic-resolution simulations of vesicle fusion to examine the molecular mechanisms for fusion in detail. We employ committor analysis for these million-atom vesicle fusion simulations to identify a transition state for fusion stalk formation. In our simulations, this transition state occurs when the bulk properties of each lipid bilayer remain in a lamellar state but a few hydrophobic tails bulge into the hydrophilic interface layer and make contact to nucleate a stalk. Additional simulations of influenza fusion peptides in lipid bilayers show that the peptides promote similar local protrusion of lipid tails. Comparing these two sets of simulations, we obtain a common set of structural changes between the transition state for stalk formation and the local environment of peptides known to catalyze fusion. Our results thus suggest that the specific molecular properties of individual lipids are highly important to vesicle fusion and yield an explicit structural model that could help explain the mechanism of catalysis by fusion proteins.

Protein dynamics simulations from nanoseconds to microseconds

There have been a number of advances in atomic resolution simulations of biomolecules during the past few years. These have arisen partly from improvements to computer power and partly from algorithmic improvements. There have also been advances in measuring time-dependent fluctuations in proteins using NMR spectroscopy, revealing the importance of fluctuations in the microsecond to millisecond time range. Progress has also been made in measuring how far the simulations are able to represent the accessible phase space that is available to the protein in its native state, in solution, at room temperature. Another area of development is the simulation of protein unfolding at atomic resolution.