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Theoretische Biophysik, Institut für Molekulare Biotechnologie, Jena, Germany; and * School of Engineering and Science, International University Bremen, Germany
Correspondence: Address reprint requests to Martin Zacharias, School of Engineering and Science, International University Bremen, Campus Ring 1, D-28759 Bremen, Germany. Tel.: 49-421-200-3541; Fax: 49-421-200-3249; E-mail: m.zacharias{at}iu-bremen.de.
| ABSTRACT |
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| INTRODUCTION |
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23 kcal mol-1 it has been speculated that protein-RNA binding may provide sufficient energy to promote such a switch, and in turn can lead to a global change in the RNA geometry (Wu and Turner, 1996
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Systematic conformational searches have been employed in the current study to investigate structural preferences of tG:A mismatches. In this approach, only energy-minimized conformational substates have been considered. In a second approach, ensembles of tG:A conformations obtained from a molecular dynamics simulation in the presence of explicit solvent and ions have been analyzed using the same continuum solvent model and force field as used to evaluate conformations from the conformational search. The results of both approaches show qualitative agreement and are compatible with the experimentally observed conformational preference of tG:A mismatches. For the sheared tandem tG:A arrangement, two low energy subtopologies were found in both the substate analysis as well as the molecular dynamics simulations that differ in the hydrogen-bonding pattern, and that are also observed in experimental G:A mismatch-containing structures. The analysis of energetic contributions allows to elucidate the origin of the sequence context-dependence of the structural preference and offers some insight into interactions that stabilize the sheared and face-to-face tG:A topologies.
| METHODS |
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in = 1.0) and surrounding aqueous solvent (
w = 78.0) were calculated using the generalized Born (GB) model (Still et al., 1990
ij were calculated using the pairwise descreening approximation described by Hawkins et al. (1995
Surface area-dependent nonpolar solvation contributions (
ESASA) were evaluated from the accessible surface area (Shrake and Rupley, 1973
), with a surface area tension coefficient of
= 0.00542 kcal x mol-1 Å-2 (Sitkoff et al., 1994
). This term was only calculated for the final energy-minimized structures since it varies very little between different conformers of one topology (<
0.1 kcal x mol-1). The total energy of a conformer (
EtotPB or
EtotGB) is given as a sum of Coulomb (
ECoul), Lennard-Jones (
ELJ), valence and torsion angle (
ETA), electrostatic solvation (
EreGB,
ErePB or
ErePBsalt), and nonpolar solvation contributions (
ESASA).
RNA structures and conformational search
The experimentally determined RNA structures for the two self-complementary sequences (A: (rGCGGACGC)2) and (B: (rGGCGAGCC)2) were used as start structures for conformational searches. The experimental structure for sequence A indicates a face-to-face G:A pairing (Wu and Turner, 1996
; see Fig. 1). Based on its structure the JUMNA program was used to generate a face-to-face model for sequence B. Vice versa the structure for sequence B with an experimentally observed sheared G:A tandem mismatch (SantaLucia and Turner, 1993
) served as the template for a sheared model structure for sequence A. Systematic conformational searches were performed starting from the four structures. During the conformational search, various combinations of backbone torsion-angle window constraints were applied during constraint energy minimization for the mismatch nucleotides and adjacent nucleotides (other nucleotides were kept in A-form). For the three central dinucleotide steps, the torsion angles
were constraint to two windows (-70°; -50°) or (60°; 120°),
to (50°; 70°) or (170°; -170°), and
to (-70°; -50°) or (170°; -170°), and the
-torsion angles of the two central nucleotides (G and A) were constraint to either the C3'-endo (70°; 90°) or C2'-endo (140°; 160°) regimes, respectively, resulting in 2048 combinations (only symmetric constraints on both strands have been considered). All structures were subsequently relaxed by unconstraint energy minimization. For a subset of low energy conformers, the orientation of the central 2'-OH groups was systematically scanned to identify an optimal orientation. The 30 lowest energy structures from each search were collected and evaluated using the FDPB approach.
Molecular dynamics simulations
The lowest energy structures obtained from the four conformational searches served as start structures for molecular dynamics (MD) simulations. The MD simulations were performed with the sander module of the AMBER5 package (Pearlman et al., 1995
) in a periodic box including TIP3 water (Jorgensen et al., 1983
) and ions, with the PME method to account for long-range electrostatics in a periodic system and using the Cornell et al. (1995)
force field. Initial positions of sodium counterions and five additional sodium and chloride counterions were placed using the xleap module of the AMBER package. Approximately 2000 water molecules were added to fill the box. A 9-Å cutoff for the short-range nonbonded interactions was used in combination with the particle mesh Ewald option, using a grid spacing of
0.9 Å to account for long-range electrostatic interactions. After a heating and equilibration phase of the solvent and ions and subsequent heating of the whole system in 50-K steps (up to 300 K) within 0.1 ns, each system was equilibrated for 1.0 ns at 300 K followed by 3 ns data-gathering time. A set of 200 solute structures along the trajectories were postprocessed using the FDPB continuum solvent model described above (molecular mechanics Poisson-Boltzmann surface areaMM/PBSAmethod; see Srinivasan et al., 1998
, and Kollman et al., 2000
). For each solute structure in the trajectory file, the same molecular mechanical energy as for the above energy-minimized conformations consisting of bonded and nonbonded energy terms of the Cornell et al. (1995)
force field was calculated, supplemented with a polar and nonpolar solvation contribution. The solvation contributions were calculated in the same way and with the same parameters as used for the evaluation of conformers generated during the conformational search. Cartesian coordinate fluctuations for all heavy atoms were calculated after subtraction of overall translation and rotation.
| RESULTS |
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flip (a concerted change of the backbone torsion angle
and
from gauche and +gauche, respectively, toward a trans state) at the central G-A step. This same backbone feature was also found in the lowest energy ftf-tG:A-structure from the conformational search (see Tables 1 and 2). An
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flip can cause a slight increase in the distance between opposite strands compared to regular RNA allowing for more space to accommodate a large G:A pair compared to a regular Watson-Crick basepair. However, the second-lowest energy substate showed a backbone conformation typical for A-form RNA. Other low energy structures (not included in Table 1) differ from the lowest energy structure in additional
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flips at neighboring nucleotides and in different orientation of the 2'-OH group. In the case of the CGAG sequence context, the structure with an
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flip at the central A-G step was found to be almost isoenergetic with the fully A-form backbone geometry (Table 1). The optimal orientation of the 2'-OH group for each low energy substate was investigated separately. Both for the A-form flanking nucleotides as well as for the central tG:A (ftf) mismatches, three minimum energy orientations were found. These minima correspond to H2'-C2'-O2'-HO dihedral angles of
80°, 190°, and 310°, respectively, and closely match the orientations found in explicit solvent simulations of RNA (Auffinger and Westhof, 1997
80°) was generally the lowest energy orientation. This orientation is also the preferred orientation found in MD simulations of RNA (Auffinger and Westhof, 1997
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-torsion angle and decrease of the
-angle at the central step was also found in the calculated lowest energy substate (Table 2). The BII state at the central dinucleotide step was found in several low energy substates. A BII state can promote a slight decrease in the distance between opposite strands and therefore supports a sheared G:A pairing that requires a reduced distance between opposite strands. Additional backbone variations include
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flips at dinucleotide steps adjacent to the central step. For the 2'-OH group at the central dinucleotide step of the low energy sheared structures, only one optimal orientation (minimum) was found (the 2'-OH vector pointing approximately toward the O3' atom). Two subforms of G:A sheared basepairing arrangement were found (type I and II). These two subforms differ slightly in the distance and relative orientation of the guanine and adenine bases in the mismatch and hydrogen-bonding geometry (Fig. 3). In the type I two strong (short distance) hydrogen bonds are formed between the two G:A pairs. This form corresponds to the geometry found in the NMR structure of tG:A mismatches in the CGAG sequence context. In the subform II, only one short distance hydrogen bond is formed in the mismatches; however, in this case, a hydrogen bond between the N6H1 of the central adenine and the O1P of the central dinucleotide step was observed. This G:A mismatch geometry has also been found experimentally; for example, as a closing pair in the x-ray structure of GNRA tetraloops (see Fig. 3). The GB approach appears to generally slightly favor type II, whereas the FDPB approach predicts a lower calculated energy for conformers with type I sheared G:A geometry.
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Comparison of equivalent low energy substates in the sheared tG:A conformation for the two sequence contexts with any selected low energy substate from the ftf-tG:A set of conformations (or vice versa) reveals a stronger favorization of the sheared over the ftf form in the case of the CGAG compared to the GGAC sequence context. In the case of comparing the lowest energy substates that also show best agreement with experimentally available tG:A structures, the calculated favorization is
-7.6 kcal mol-1 in the CGAG context. For the GGAC sequence, the calculated energy difference between the corresponding lowest energy ftf and sheared tG:A-forms is
-3.8 kcal mol-1. The greater favorization of the sheared form in the CGAG case compared to the GGAC sequence context agrees with experiment. However, the calculation also predicts a lower energy of the sheared vs. face-to-face form in the GGAC context. This seems to contradict the experimental observation. It is important to note that conformational entropy contributions due to differences in the flexibility of the two tG:A mismatch forms are not included in the continuum solvent analysis. Results from MD simulations (see below) indicate a greater conformational flexibility of the face-to-face conformation, which makes a favorable entropic contribution to the stability of the face-to-face pairing geometry. Depending on the selected pair of substates, electrostatic contributions can either stabilize or destabilize the ftf form compared to the sheared substate. However, for a given pair of substates, the magnitude of the electrostatic energy difference tends to be larger for the GGAC than the CGAG context. Considering the calculated lowest energy substates that showed best agreement with available experimental structures (substate 1 for sheared and ftf forms in Table 1) as the dominant structural states, the electrostatic interactions overall stabilize the ftf form by 5 kcal mol-1 in the GGAC context, but by only 2 kcal mol-1 in the CGAG context.
For the comparison of lowest energy substates, the van der Waals and Coulomb contributions were further split into intrachain and interchain contributions (Table 3). Note that this is not possible for the reaction field term, which depends on shape and charge distribution of the entire molecule. The pattern of intra- and interstrand van der Waals contributions to the energy difference between ftf and sheared forms is relatively similar for both sequence contexts. Most of the van der Waals energy difference between sheared and face-to-face forms is due to interstrand (cross-stacking) contributions (partially compensated by intrastrand interactions) that significantly stabilize the sheared form. The interstrand base-base van der Waals interactions appear to favor the sheared form slightly more in the GGAC context than in the CGAG context. The Coulomb energy difference between the two forms overall strongly favors the ftf topology in both sequence contexts (see also Table 1). Interestingly, the calculated total interstrand Coulomb interaction more significantly favors the ftf form in the case of the GGAC context (-82.3 kcal mol-1) than in the CGAG context (-47.2 kcal mol-1). Note that these calculated total interaction energy differences include contributions not only from all nucleobases but also from the sugar-phosphate backbone interactions. The base-base charge interactions strongly stabilize the face-to-face form in the GGAC context (-10.5 kcal mol-1) whereas a calculated destabilization is found in the CGAC context (7.8 kcal mol-1). These results indicate that electrostatic base-base complementarity makes a significant contribution to the sequence context-dependence of the tG:A topology.
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1 ns (Fig. 4). No rearrangements of the initial tG:A topologies such as a transition from a ftf to a sheared topology or vice versa have been observed during the MD simulations. Nevertheless, for the sheared forms, transitions between type I and II tG:A arrangements (see Fig. 3) have been found during the simulation (with the type I arrangement more frequently sampled than type II, not shown). For both sequence contexts overall, slightly larger Cartesian coordinate fluctuations were observed in the case of the ftf-tG:A simulations (Fig. 5). To some degree, this is expected, since the sheared tG:A mismatches form an overall more compact structure. This result indicates a larger conformational freedom or conformational entropy of the ftf form compared to the sheared topology. Trajectory frames from the 2- to 4-ns interval of each MD simulation were analyzed with the FDPB continuum solvent model (Fig. 6). The continuum solvent analysis was performed with the same force field model and set of parameters as used to evaluate energy-minima from the conformational searches.
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13 kcal mol-1 over the sheared tG:A mismatch arrangement. With an internal dielectric constant,
in = 2, a smaller calculated preference was obtained. In this case the calculated preference for the sheared form in the CGAG sequence context was
-8.0 kcal mol-1 and a preference for the ftf form in the case of the GGAC sequence of
-4.0 kcal mol-1 was obtained. The result is in qualitative agreement with the experimental observation. However, the calculated energetic preference for each topology is larger than experimental estimates of 23 kcal mol-1. Interestingly, the calculations that assume an internal dielectric constant,
in = 2, are closer to experiment than the standard,
in = 1, calculations. Similar to the results on comparing minimized lowest energy substates, the trajectory analysis indicates the sheared form overall to be favored by van der Waals and polar and nonpolar solvation contributions, but disfavored by Coulomb interactions. The trajectory analysis predicts that differences in the total electrostatic contributions make a significant contribution to the sequence context-dependence of the relative stability of sheared vs. ftf tG:A mismatches. In the case of the CGAG context, electrostatic contributions overall slightly favor the sheared form, whereas in the case of the GGAC context, the ftf form is electrostatically favored over the sheared form.
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| DISCUSSION |
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As a basis for the present calculations, two NMR-derived RNA structures with identical base composition, but slightly different sequence, and the tG:A motif either in the sheared form (CGAG context, Santa-Lucia and Turner, 1993
) or the ftf form (GGAC context, Wu and Turner, 1996
), were chosen. This pair of structures is a very useful reference and basis for the present theoretical study, since both structures have been determined under similar conditions, using the same experimental method, and are composed of the same nucleotides. Other influences besides of the sequence context that may affect the relative stability of tG:A mismatch conformations such as solution or crystallization conditions and contacts to other RNA elements in folded RNAs can be excluded.
In the present study two different continuum solvent analysis methods have been applied to study the conformational preference of tandem guanine:adenine mismatches in RNA. In the systematic conformational analysis approach, energy-minimized substates for the motif have been generated by applying constraint energy minimization to systematically generate various backbone torsion-angle combinations defined by a set of window constraints followed by free minimization to reach the closest energy minimum substate. In the case of the MM/PBSA approach (Srinivasan et al., 1998
; Kollman et al., 2000
), ensembles of tG:A mismatch conformations have been generated using molecular dynamics simulations including ions and water explicitly followed by postprocessing the trajectories using the same force field and continuum solvent method as for the analysis of substates. Both approaches complement each other, in that the substates analysis method samples systematically a wider range of conformers, whereas the MM/PBSA approach yields more or less randomly sampled conformers close to one or a few substates. It needs to be stressed that a perfect agreement between substate analysis and trajectory analysis is not expected. In the former (and faster) approach, a greater variety of conformers can be sampled, but these are only represented as energy minima. In contrast, during molecular dynamics simulations, not only energy minima but conformers compatible with a thermodynamic ensemble in the presence of explicit solvent have been generated. However, even at the nanosecond timescale the simulated structures stay relatively close to one substate which is given by the starting structure. In the present study, the lowest energy substates that showed best agreement with available experimental structures were chosen as start conformations. An additional difference between the conformational searches using JUMNA (Lavery et al., 1995
) and the analysis of MD trajectories is that all bond lengths (and valence angles within nucleobases) are kept at their optimal values in the JUMNA approach (Lavery et al., 1995
). The reduced set of conformational variables allows a fast convergence of the energy-minimization calculations. In the MD simulations, bond lengths between heavy atoms were allowed to vary, and, in particular, atoms that belong to nucleobases can undergo more fluctuations.
Despite these differences, both approaches yielded qualitatively similar results on the energetic contributions that stabilize or destabilize sheared and face-to-face topologies of tG:A mismatches and on the experimentally observed sequence context effect. The analysis of energy-minimized substates yielded a more significant stabilization of the sheared form in the CGAG context but still predicted a lower energy for the sheared vs. ftf forms in the case of the GGAC context. However, the difference was smaller by
3 kcal mol-1 for the latter case. The MD simulations of the tG:A motif in the two sequence contexts showed an overall greater flexibility of the face-to-face topology that indicated an entropic favorization of the face-to-face topology not accounted for in the energetic evaluation of the substates. Accounting for such a contribution would overall shift the stability difference between the two topologies in favor of the face-to-face form in better agreement with the experimental observation. The MM/PBSA trajectory analysis yielded stability differences between the two tandem G:A forms that have a sign in agreement with experiment but are larger than experimental estimates (Wu and Turner, 1996
). Interestingly, we found that using a larger internal dielectric constant of
in = 2 still yields the correct sign, but also somewhat smaller energy differences between the two mismatch topologies in the two sequence contexts that are probably more realistic. It should be noted that the force field of Cornell et al. (1995)
has been designed for simulation studies using a dielectric constant
in = 1. Since for the present analysis method the explicit solvent from the simulation has been replaced by a continuum without reducing or changing the degrees of freedom of the solute molecule, the use of
in = 1 for the interior of the molecule is a consistent choice. However, it has been found in other applications of the MM/PBSA method, for example Wang et al. (2001)
, that a trajectory analysis with a larger dielectric constant often yields results in better agreement with experiment than with
in = 1.
The qualitative agreement between the conformational search approach and the MM/PBSA method allows to identify trends concerning the energetic origins for the stabilization of the two topologies. Both approaches predict a stabilization of the sheared topology due to van der Waals and nonpolar solvation contributions. This is to some degree expected, considering the more compact shape of the sheared tG:A arrangement. The MM/PBSA results, as well as comparison of lowest energy sheared and ftf substates, indicated that Coulomb interactions generally favor the face-to-face pairing, although the number of polar contacts such as hydrogen bonds is similar in both topologies (depending on the substate, even more hydrogen bonds are possible in the sheared topology). However, the less compact shape of the face-to-face topology (with an on average greater distance between opposite strands) results in an overall smaller Coulomb repulsion of the phosphate groups on opposite strands. In the sheared form, this is, in part, compensated by a more negative reaction field energy which stabilizes the sheared form. These trends are seen for both sequence contexts. A role of electrostatic contributions to stacking for the context effect has been suspected already by Wu and Turner (1996)
. For the lowest energy ftf and sheared conformations, electrostatic and van der Waals interactions were further split into inter- and intrastrand contributions. The calculated intra- and interstrand contributions to the van der Waals interactions of the RNA molecules were similar in both sequence contexts. The calculated van der Waals favorization of the sheared topology was found to be mostly due to interstrand interactions. The analysis showed further that the Coulomb part of the interstrand base-base interaction significantly favors the sheared arrangement in the CGAG context, whereas the same interaction favors the ftf arrangement in the GGAC context. This result is in line with the results of the MM/PBSA trajectory analysis that predicted an overall electrostatic favorization of the sheared form in the CGAG context and ftf form in the GGAC context. It indicates that electrostatic interactions make the most significant contribution to the sequence context effect on the conformational preference of tandem G:A mismatches. The two continuum solvent approaches applied to tandem G:A mismatches could also be useful to analyze and better understand conformational preferences of other nucleic acid motifs. It might also be possible to use the methodology to make predictions on sequence context effects and how conformational preferences might change upon changing the environment of the nucleic acid for, example, in complexes with proteins or organic ligands.
| ACKNOWLEDGEMENTS |
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This work was supported, in part, by a grant from the Deutsche Forschungsgemeinschaft (ZA 153/3-1) to M.Z.
| FOOTNOTES |
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Submitted on October 13, 2002; accepted for publication February 27, 2003.
| REFERENCES |
|---|
|
|
|---|
Ban, N., P. Nissen, J. Hansen, P. B. Moore, and T. A. Steitz. 2000. The complete atomic structure of the large ribosomal subunit at 2.4 Å resolution. Science. 289:905920.
Bondi, A. 1964. Van der Waals volumes and radii. J. Phys. Chem. 64:441451.
Cate, J. H., A. R. Gooding, E. Podell, K. Zhou, B. L. Golden, C. E. Kundrot, T. R. Cech, and J. A. Doudna. 1996a. Crystal structure of a group I ribozymes domain: principles of RNA packing. Science. 273:16781685.
Cate, J. H., A. R. Gooding, E. Podell, K. Zhou, B. L. Golden, A. A. Szewczak, C. E. Kundrot, T. R. Cech, and J. A. Doudna. 1996b. RNA tertiary structure mediation by adenosine platforms. Science. 273:16961699.
Cornell, W. D., P. Cieplak, C. I. Bayley, I. R. Gould, K. M. Merz, D. M. Ferguson, D. C. Spellmeyer, T. Fox, J. W. Caldwell, and P. A. Kollman. 1995. A second generation force field for simulation of proteins, nucleic acids and organic molecules. J. Am. Chem. Soc. 117:51795197.
Gautheret, D., D. Konings, and R. R. Gutell. 1994. A major family of motifs involving G:A mismatches in ribosomal RNA. J. Mol. Biol. 242:18.[Medline]
Gutell, R. R., N. Larsen, and C. R. Woese. 1994. Lessons from an evolving RNA: 16S and 23S rRNA structures from a comparative perspective. Microb. Rev. 58:1026.
Guzman, R. N., R. T. Turner, and M. F. Summers. 1998. Protein-RNA recognition. Biopolymers. 48:181195.[Medline]
Hawkins, G. D., C. J. Cramer, and D. G. Truhlar. 1995. Pairwise solute descreening of solute charges from a dielectric continuum. Chem. Phys. Lett. 246:122129.
Hawkins, G. D., C. J. Cramer, and D. G. Truhlar. 1996. Parametrized models of aqueous free energies of solvation based on pairwise descreening of solute atomic charges from a dielectric medium. J. Phys. Chem. 100:1982419839.
Heus, H. A., S. S. Wijmenga, H. Hoppe, and C. W. Hilbers. 1997. The detailed structure of tandem G:A mismatched basepair motifs in RNA duplexes is context-dependent. J. Mol. Biol. 271:147158.[Medline]
Jayaram, B., D. Sprous, and D. L. Beveridge. 1998. Solvation free energies of biomacromolecules: parameters for a modified generalized Born model consistent with the Amber force field. J. Phys. Chem. 102:95719576.
Jorgensen, W. L., J. Chandrasekhar, J. Madura, R. W. Impey, and M. L. Klein. 1983. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79:926935.
Kollman, P. A., I. Massova, C. Reyes, B. Kuhn, S. Huo, L. Chong, M. Lee, Y. Duan, W. Wang, O. Donini, P. Cieplak, J. Srinivasan, D. A. Case, and T. E. Cheatham 3rd. 2000. Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc. Chem. Res. 33:889897.[Medline]
Lavery, R., K. Zakrzewska, and H. Sklenar. 1995. JUMNA (junction minimization of nucleic acids). Comput. Phys. Com. 91:135158.
Madura, J. D., M. E. Davis, R. Wade, B. A. Luty, A. Ilin, A. Anosiewicz, M. K. Gilson, B. Bagheri, L. Ridgway-Scot, and J. A. McCammon. 1995. Electrostatics and diffusion of molecules in solution: simulations with University of Houston Brownian dynamics program. Comput. Phys. Commun. 91:5795.
Pearlman, D. A., D. A. Case, J. W. Caldwell, W. S. Ross, T. E. Cheatham, S. Debolt, D. Ferguson, G. Seibel, and P. A. Kollman. 1995. AMBER; a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules. Comput. Phys. Commun. 91:141.
Pley, H. W., D. S. Lindes, and D. B. McKay. 1994. Three-dimensional structure of a hammerhead ribozyme. Nature. 372:6874.[Medline]
SantaLucia, J., and D. H. Turner. 1993. Structure of (rGGCGAGCC)2 in solution from NMR and restraint molecular dynamics. Biochemistry. 32:1261212623.[Medline]
Schlünzen, F., A. Tocilj, R. Zarivach, J. Harms, M. Gluehmann, D. Janell, A. Bashan, A. Bartels, I. Agmon, F. Franceschi, and A. Yonath. 2000. Structure of functionally activated small ribosomal subunit at 3.3 Å resolution. Cell. 102:615623.[Medline]
Schlünzen, F., R. Zarivach, J. Harms, A. Bashan, A. Tocilj, R. Albrecht, A. Yonath, and F. Franceschi. 2001. Structural basis for the interaction of antibiotics with the peptidyl transferase centre in eubacteria. Nature. 413:814821.[Medline]
Sharp, K. A., and B. Honig. 1990. Calculating total electrostatic energies with the nonlinear Poisson-Boltzmann equation. J. Phys. Chem. 94:76847692.
Shrake, A., and J. A. Rupley. 1973. Environment and exposure to solvent of protein atoms: lysozyme and insulin. J. Mol. Biol. 79:351365.[Medline]
Sitkoff, D., K. A. Sharp, and B. Honig. 1994. Accurate calculation of hydration free energies using macroscopic solvent models. J. Phys. Chem. 98:19781988.
Srinivasan, J., J. Miller, P. A. Kollman, and D. A. Case. 1998. Continuum solvent studies of the stability of RNA hairpin loops and helices. J. Biomol. Struct. Dyn. 16:671682.[Medline]
Srinivasan, J., M. W. Trevathan, P. Beroza, and D. A. Case. 1999. Application of a pairwise generalized Born model to proteins and nucleic acids: inclusion of salt effects. Theor. Chem. Acc. 101:426434.
Still, W. C., A. Tempczyk, R. C. Hawley, and T. Hendrikson. 1990. Semianalytical treatment of solvation for molecular mechanics and dynamics. J. Am. Chem. Soc. 112:61276129.
Tsui, V., and D. A. Case. 2000. Molecular dynamics simulations of nucleic acids with a generalized Born solvation model. J. Am. Chem. Soc. 122:24892498.
Wang, W., W. A. Lim, A. Jakalian, J. Wang, J. Wang, R. Luo, C. Bayly, and P. A. Kollman. 2001. An analysis of the interactions between the Sem-5 SH3 domain and its ligands using molecular dynamics, free energy calculations, and sequence analysis. J. Am. Chem. Soc. 123:39863994.[Medline]
Williams, D. J., and K. B. Hall. 1999. Unrestrained stochastic dynamics simulations of the UUCG tetraloop using an implicit solvation model. Biophys. J. 76:31923205.
Williams, D. J., and K. B. Hall. 2000a. Experimental and theoretical studies of the effects of deoxyribose substitutions on the stability of the UUCG tetraloop. J. Mol. Biol. 297:251265.[Medline]
Williams, D. J., and K. B. Hall. 2000b. Experimental and computational studies of the G[UUCG]C RNA tetraloop. J. Mol. Biol. 297:10451061.[Medline]
Wimberley, B. T., D. E. Brodersen, W. M. J. Clemons, R. J. Morgan-Warren, A. P. Carter, C. Vonrhehein, T. Hartsch, and V. Ramakrishnan. 2000. Structure of the 30S ribosomal subunit. Nature. 407:327339.[Medline]
Wu, M., J. SantaLucia, and D. H. Turner. 1997. Solution structure of (rGGCAGGCC)2 by two-dimensional NMR and iterative relaxation matrix approach. Biochemistry. 36:44494460.[Medline]
Wu, M., and D. H. Turner. 1996. Solution structure of (rGCGACGC)2 by two-dimensional NMR and iterative relaxation matrix approach. Biochemistry. 35:96779689.[Medline]
Zacharias, M., and H. Sklenar. 1999. Conformational analysis of single-base bulges in A-form DNA and RNA using a hierarchical approach and energetic evaluation with a continuum solvent model. J. Mol. Biol. 289:261275.[Medline]
Zacharias, M. 2001. Conformational analysis of DNA-trinucleotide-hairpin-loop structures using a continuum solvent model. Biophys. J. 80:23502363.
Zhang, X., B. L. Gaffney, and R. A. Jones. 1998. 15N NMR of RNA fragments containing specifically labelled tandem G:A pairs. J. Am. Chem. Soc. 120:66256626.
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