Symmetric K+ and Mg2+ Ion-binding Sites in the 5S rRNA Loop E Inferred from Molecular Dynamics Simulations

Some experimental results for the thermodynamics of RNA folding cannot be explained by simple pairwise hydrogen-bonding models. Such effects include the stabilities of isoguanosineisocytidine (iG-iC) base pairs and of various 2 × 2 nucleotide internal loops. Presumably, these results can be explained by base stacking effects, which can be partitioned into Coulombic and overlap effects. We review experimental measurements that provide benchmarks for testing the approximations and theories used for modeling nucleic acids. Quantitative agreement between experiment and theory will indicate understanding of the interactions determining RNA stability and structure.An understanding of the physical-chemical interactions underlying RNA folding would allow predictions of structure and perhaps function from sequence. The large number of atoms in an RNA molecule necessitates the use of approximate methods, rather than the rigorous equations of quantum mechanics. Many approaches are possible, including coarsegrained potentials (1), which use residue-centered force fields; molecular mechanics, which uses atom-centered force fields such as AMBER (2), CHARMM (3, 4), and GROMOS (5, 6); approximate quantum mechanics, which considers interactions of electrons and nuclei (7,8); and QM/MM, which combines quantum mechanics with molecular mechanics (9-16). Depending on the property to be predicted, the size of the RNA, and the domain of interest, different approaches will provide acceptable approximations.The secondary structure of RNA can sometimes be deduced by sequence comparison, which relies on the Watson-Crick rules for base pairing and the assumption that secondary structures are more conserved than sequences for function (17). Often, however, there are not enough sequences to determine a definitive secondary structure. For these cases, freeenergy minimization with a nearest neighbor model is the most popular method for predicting secondary structures (18-38). In this method, possible secondary structure motifs are assigned free-energy parameters, and these values are added to predict the total free energy of forming a secondary structure. The structure with the lowest free energy is assumed to dominate in solution. Rigorously, however, the concentrations of the various possible structures are predicted to be weighted by a Boltzmann factor, exp(−ΔG°/RT), where ΔG° is the free energy change for folding, R is the gas constant, 1.987 cal K −1 mol −1 , and T is the temperature in kelvins. Understanding intermolecular interactions such as hydrogen bonding, stacking, and so forth would allow accurate prediction of ΔG° and therefore secondary structure for an RNA. † This work was supported by NIH Grant GM22939 (D.H.T. Watson-Crick base pairs are the most common and most extensively studied motif in RNA structures. Configurations with the same base compositions but different permutations of base pairs generally have different free energies. For example, the duplexes (5′CGCG3′) 2 and (5′GGCC3′) 2 both have four GC base pairs, bu...

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“…Some ions, such as Mg 2+ and K + , stabilize tertiary structures better than other ions (45,47,70,71). Such stabilization is not well-understood.…”

Section: Theorymentioning

confidence: 99%

RNA Challenges for Computational Chemists

Yildirim

Turner

2005

Biochemistry

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“…While there are no metal ions resolved crystallographically around G895 NH1, G902 NH1, G903 NH1, and U904 NH3, these protons are positioned deeply within the highly negatively charged major (deep) groove adjacent to the loop E motif, which is expected to be a particularly strong metal ion binding site ( Fig. 6A,D ;Correll et al 1997;Serra et al 2002;Auffinger et al 2004;Reblova et al 2004). We therefore propose that Mg 2+ either binds near the tandem G894-U905/G895-U904 wobble pairs in solution and not in the crystal or, alternatively, that binding is transient under both sets of conditions (possibly explaining why no NOE with Co(NH 3 ) 6 3+ hexammine protons was observed) so that the metal ion occupancy at this site is too low to produce an assignable signal in crystallographic electron density maps.…”

Section: Wwwrnajournalorg 1695mentioning

confidence: 99%

Solution probing of metal ion binding by helix 27 fromEscherichia coli16S rRNA

Lambert

Hoerter

Pereira

et al. 2005

RNA

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Helix (H)27 from Escherichia coli 16S ribosomal (r)RNA is centrally located within the small (30S) ribosomal subunit, immediately adjacent to the decoding center. Bacterial 30S subunit crystal structures depicting Mg 2+ binding sites resolve two magnesium ions within the vicinity of H27: one in the major groove of the G886-U911 wobble pair, and one within the GCAA tetraloop. Binding of such metal cations is generally thought to be crucial for RNA folding and function. To ask how metal ion-RNA interactions in crystals compare with those in solution, we have characterized, using solution NMR spectroscopy, Tb 3+ footprinting and time-resolved fluorescence resonance energy transfer (tr-FRET), location, and modes of metal ion binding in an isolated H27. NMR and Tb 3+ footprinting data indicate that solution secondary structure and Mg 2+ binding are generally consistent with the ribosomal crystal structures. However, our analyses also suggest that H27 is dynamic in solution and that metal ions localize within the narrow major groove formed by the juxtaposition of the loop E motif with the tandem G894-U905 and G895-U904 wobble pairs. In addition, tr-FRET studies provide evidence that Mg 2+ uptake by the H27 construct results in a global lengthening of the helix. We propose that only a subset of H27-metal ion interactions has been captured in the crystal structures of the 30S ribosomal subunit, and that small-scale structural dynamics afforded by solution conditions may contribute to these differences. Our studies thus highlight an example for differences between RNA-metal ion interactions observed in solution and in crystals.

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“…[3][4][5][6][7][8][9][10][22][23][24][25][26][27][28][29][30][31][32] The AMBER force fields have also been successful in studies of RNA molecules, including those that exhibit a wide range of non-Watson-Crick base pairings, tertiary interactions, and complex backbone topologies. [33][34][35][36][37][38][39][40][41][42][43] These studies have also emphasized the importance of NAs' sugar-phosphate backbone flexibility, which is delimited by six main-chain torsion angles (designated as R through ), in addition to the five internal sugar torsions (denoted as τ 0 through τ 4 , which can be succinctly described by the puckering and the phase angle 44 ), and the glycosidic angle 45 (see Figure 1). Free duplex B-DNA frequently populates two distinct backbone conformational substates, referred to as B I and B II .…”

Section: Introductionmentioning

confidence: 99%

Geometrical and Electronic Structure Variability of the Sugar−phosphate Backbone in Nucleic Acids

Svozil¹,

Šponer²,

Marchán³

et al. 2008

J. Phys. Chem. B

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The anionic sugar-phosphate backbone of nucleic acids substantially contributes to their structural flexibility. To model nucleic acid structure and dynamics correctly, the potentially sampled substates of the sugar-phosphate backbone must be properly described. However, because of the complexity of the electronic distribution in the nucleic acid backbone, its representation by classical force fields is very challenging. In this work, the three-dimensional potential energy surfaces with two independent variables corresponding to rotations around the R and γ backbone torsions are studied by means of high-level ab initio methods (B3LYP/ 6-31+G*, MP2/6-31+G*, and MP2 complete basis set limit levels). [3817][3818][3819][3820][3821][3822][3823][3824][3825][3826][3827][3828][3829] force fields to describe the various R/γ conformations of the DNA backbone accurately is assessed by comparing the results with those of ab initio quantum chemical calculations. Two model systems differing in structural complexity were used to describe the R/γ energetics. The simpler one, SPM, consisting of a sugar and methyl group linked through a phosphodiester bond was used to determine higher-order correlation effects covered by the CCSD(T) method. The second, more complex model system, SPSOM, includes two deoxyribose residues (without the bases) connected via a phosphodiester bond. It has been shown by means of a natural bond orbital analysis that the SPSOM model provides a more realistic representation of the hyperconjugation network along the C5′-O5′-P-O3′-C3′ linkage. However, we have also shown that quantum mechanical investigations of this model system are nontrivial because of the complexity of the SPSOM conformational space. A comparison of the ab initio data with the ff99 potential energy surface clearly reveals an incorrect ff99 force-field description in the regions where the γ torsion is in the trans conformation. An explanation is proposed for why the R/γ flips are eliminated so successfully when the parmbsc0 force-field modification is used.

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Symmetric K+ and Mg2+ Ion-binding Sites in the 5S rRNA Loop E Inferred from Molecular Dynamics Simulations

Cited by 91 publications

References 74 publications

RNA Challenges for Computational Chemists

RNA Challenges for Computational Chemists

Solution probing of metal ion binding by helix 27 fromEscherichia coli16S rRNA

Geometrical and Electronic Structure Variability of the Sugar−phosphate Backbone in Nucleic Acids

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