65 research outputs found

    A systematic molecular dynamics study of nearest-neighbor effects on base pair and base pair step conformations and fluctuations in B-DNA

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    It is well recognized that base sequence exerts a significant influence on the properties of DNA and plays a significant role in protein–DNA interactions vital for cellular processes. Understanding and predicting base sequence effects requires an extensive structural and dynamic dataset which is currently unavailable from experiment. A consortium of laboratories was consequently formed to obtain this information using molecular simulations. This article describes results providing information not only on all 10 unique base pair steps, but also on all possible nearest-neighbor effects on these steps. These results are derived from simulations of 50–100 ns on 39 different DNA oligomers in explicit solvent and using a physiological salt concentration. We demonstrate that the simulations are converged in terms of helical and backbone parameters. The results show that nearest-neighbor effects on base pair steps are very significant, implying that dinucleotide models are insufficient for predicting sequence-dependent behavior. Flanking base sequences can notably lead to base pair step parameters in dynamic equilibrium between two conformational sub-states. Although this study only provides limited data on next-nearest-neighbor effects, we suggest that such effects should be analyzed before attempting to predict the sequence-dependent behavior of DNA

    Molecular dynamics simulations suggest that RNA three-way junctions can act as flexible RNA structural elements in the ribosome

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    We present extensive explicit solvent molecular dynamics analysis of three RNA three-way junctions (3WJs) from the large ribosomal subunit: the 3WJ formed by Helices 90–92 (H90–H92) of 23S rRNA; the 3WJ formed by H42–H44 organizing the GTPase associated center (GAC) of 23S rRNA; and the 3WJ of 5S rRNA. H92 near the peptidyl transferase center binds the 3′-CCA end of amino-acylated tRNA. The GAC binds protein factors and stimulates GTP hydrolysis driving protein synthesis. The 5S rRNA binds the central protuberance and A-site finger (ASF) involved in bridges with the 30S subunit. The simulations reveal that all three 3WJs possess significant anisotropic hinge-like flexibility between their stacked stems and dynamics within the compact regions of their adjacent stems. The A-site 3WJ dynamics may facilitate accommodation of tRNA, while the 5S 3WJ flexibility appears to be essential for coordinated movements of ASF and 5S rRNA. The GAC 3WJ may support large-scale dynamics of the L7/L12-stalk region. The simulations reveal that H42–H44 rRNA segments are not fully relaxed and in the X-ray structures they are bent towards the large subunit. The bending may be related to L10 binding and is distributed between the 3WJ and the H42–H97 contact

    Mechanism of MicroRNA-Target Interaction: Molecular Dynamics Simulations and Thermodynamics Analysis

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    MicroRNAs (miRNAs) are endogenously produced ∼21-nt riboregulators that associate with Argonaute (Ago) proteins to direct mRNA cleavage or repress the translation of complementary RNAs. Capturing the molecular mechanisms of miRNA interacting with its target will not only reinforce the understanding of underlying RNA interference but also fuel the design of more effective small-interfering RNA strands. To address this, in the present work the RNA-bound (Ago-miRNA, Ago-miRNA-target) and RNA-free Ago forms were analyzed by performing both molecular dynamics simulations and thermodynamic analysis. Based on the principal component analysis results of the simulation trajectories as well as the correlation analysis in fluctuations of residues, we discover that: 1) three important (PAZ, Mid and PIWI) domains exist in Argonaute which define the global dynamics of the protein; 2) the interdomain correlated movements are so crucial for the interaction of Ago-RNAs that they not only facilitate the relaxation of the interactions between residues surrounding the RNA binding channel but also induce certain conformational changes; and 3) it is just these conformational changes that expand the cavity of the active site and open putative pathways for both the substrate uptake and product release. In addition, by thermodynamic analysis we also discover that for both the guide RNA 5′-end recognition and the facilitated site-specific cleavage of the target, the presence of two metal ions (of Mg2+) plays a predominant role, and this conclusion is consistent with the observed enzyme catalytic cleavage activity in the ternary complex (Ago-miRNA-mRNA). Our results find that it is the set of arginine amino acids concentrated in the nucleotide-binding channel in Ago, instead of the conventionally-deemed seed base-paring, that makes greater contributions in stabilizing the binding of the nucleic acids to Ago

    Determination of Alkali and Halide Monovalent Ion Parameters for Use in Explicitly Solvated Biomolecular Simulations

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    Alkali (Li+, Na+, K+, Rb+, and Cs+) and halide (F−, Cl−, Br−, and I−) ions play an important role in many biological phenomena, roles that range from stabilization of biomolecular structure, to influence on biomolecular dynamics, to key physiological influence on homeostasis and signaling. To properly model ionic interaction and stability in atomistic simulations of biomolecular structure, dynamics, folding, catalysis, and function, an accurate model or representation of the monovalent ions is critically necessary. A good model needs to simultaneously reproduce many properties of ions, including their structure, dynamics, solvation, and moreover both the interactions of these ions with each other in the crystal and in solution and the interactions of ions with other molecules. At present, the best force fields for biomolecules employ a simple additive, nonpolarizable, and pairwise potential for atomic interaction. In this work, we describe our efforts to build better models of the monovalent ions within the pairwise Coulombic and 6-12 Lennard-Jones framework, where the models are tuned to balance crystal and solution properties in Ewald simulations with specific choices of well-known water models. Although it has been clearly demonstrated that truly accurate treatments of ions will require inclusion of nonadditivity and polarizability (particularly with the anions) and ultimately even a quantum mechanical treatment, our goal was to simply push the limits of the additive treatments to see if a balanced model could be created. The applied methodology is general and can be extended to other ions and to polarizable force-field models. Our starting point centered on observations from long simulations of biomolecules in salt solution with the AMBER force fields where salt crystals formed well below their solubility limit. The likely cause of the artifact in the AMBER parameters relates to the naive mixing of the Smith and Dang chloride parameters with AMBER-adapted Åqvist cation parameters. To provide a more appropriate balance, we reoptimized the parameters of the Lennard-Jones potential for the ions and specific choices of water models. To validate and optimize the parameters, we calculated hydration free energies of the solvated ions and also lattice energies (LE) and lattice constants (LC) of alkali halide salt crystals. This is the first effort that systematically scans across the Lennard-Jones space (well depth and radius) while balancing ion properties like LE and LC across all pair combinations of the alkali ions and halide ions. The optimization across the entire monovalent series avoids systematic deviations. The ion parameters developed, optimized, and characterized were targeted for use with some of the most commonly used rigid and nonpolarizable water models, specifically TIP3P, TIP4PEW, and SPC/E. In addition to well reproducing the solution and crystal properties, the new ion parameters well reproduce binding energies of the ions to water and the radii of the first hydration shells

    Critical infrastructure and disaster risk reduction planning under socioeconomic and climate change uncertainty

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    Planning of infrastructure and disaster risk mitigation measures is carried out under significant uncertainties. In particular, the effects of climate and anthropogenic change are associated with large uncertainty, but most extreme events are poorly understood even under stationary conditions. To address these uncertainties, the designers/decision makers can follow different strategies, such as conservative designs, flexible (adaptable) designs or delaying the decisions to later times when more information is available. The optimal adaptation strategy depends on multiple factors such as system type, regulatory framework, the degree and type of uncertainty and the amount of learning that is possible in the future. Based on quantitative Bayesian decision models, we derive general recommendations on optimal design approaches. Our results show, for example, that flexible systems are especially beneficial in cases where uncertainty is high and where the learning effect in the near future is expected to be significant. They are typically less advantageous in the context of a risk-based decision framework (where the aim is to find a balance between the residual risk and cost) than in a rule-based regulatory framework (where safety requirements are prescribed, e.g. that flood protection must be designed against a 100-year event). In the former case, it is often more effective to add safety margins, which is a no-regret strategy
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