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Copyright © 2006, Biophysical Society B-DNA Under Stress: Over- and Untwisting of DNA during Molecular Dynamics Simulations School of Engineering and Science, International University Bremen, Bremen, Germany Address reprint requests to Martin Zacharias, Tel.: 49-421-200-3541; E-mail: m.zacharias/at/iu-bremen.de. Received April 13, 2006; Accepted June 23, 2006. This article has been cited by other articles in PMC.Abstract The twist flexibility of DNA is central to its many biological functions. Explicit solvent molecular dynamics simulations in combination with an umbrella sampling restraining potential have been employed to study induced twist deformations in DNA. Simulations allowed us to extract free energy profiles for twist deformations and were performed on six DNA dodecamer duplexes to cover all 10 possible DNA basepair steps. The shape of the free energy curves was similar for all duplexes. The calculated twist deformability was in good agreement with experiment and showed only modest variation for the complete duplexes. However, the response of the various basepair steps on twist stress was highly nonuniform. In particular, pyrimidine/purine steps were much more flexible than purine/purine steps followed by purine/pyrimidine steps. It was also possible to extract correlations of twist changes and other helical as well as global parameters of the DNA molecules. Twist deformations were found to significantly alter the local as well as global shape of the DNA modulating the accessibility for proteins and other ligands. Severe untwisting of DNA below an average of 25° per basepair step resulted in the onset of a global structural transition with a significantly smaller twist at one end of the DNA compared to the other. INTRODUCTION The conformational flexibility of DNA is central to its many biological functions including recognition by proteins during gene regulation, DNA repair, packaging in the cell, and transient melting during transcription and replication (1–6). Specific binding by proteins is not only determined by specific interactions between DNA and proteins but also by the sequence-dependent structure and deformability of the DNA helix (1–4,7–16). In vivo DNA is mostly found in circularly closed form including supercoiling that causes a mechanical stress (torque) on the DNA twist and can strongly affect recognition by proteins and influence transcription and replication fidelity (6,15). Therefore, better understanding of the sequence-dependence of the DNA twist flexibility is of particular interest. The total twist and to some degree also the twist elasticity of DNA can be measured using DNA ring-closure ligation (cyclization) experiments with DNA molecules of different length and including a helix phasing analysis (17–19). This technique has been used to study the twist flexibility of DNA fragments of various length and sequence in solution. Alternatively, time-resolved fluorescence polarization anisotropy (on DNA with intercalated ethidium-bromide) can also be used to measure torsional DNA flexibility near the equilibrium state (20,21). These studies indicate that the overall base composition has only a modest influence on the average twist flexibility of DNA. Recently, it has also become possible to study the elastic response of single DNA molecules upon application of external torques to un- or over-twisted DNA (22). Such experiments provide valuable insights into the physical and elastic properties of DNA molecules. However, only relatively long DNA molecules (>1 kbp) can be studied that can react on the external stress by local as well as global conformational changes (e.g., supercoiling that relaxes part of the twist-stress). Similar to the DNA ring closure experiments, an overall twist elasticity can be obtained—but with only modest insight provided into the conformational changes taking place at the molecular level. High-resolution experimental structures of isolated DNA molecules and complexes with organic ligands and proteins allow us to study the fine structure of DNA. Under the assumption that observed structural variations reflect the intrinsic deformability of B-DNA the analysis provides insights into the flexibility of DNA near the native state at atomic resolution including also DNA twist elasticity (3,4,7–15). Olson and co-workers (4) have extensively analyzed structural variations in available DNA oligonucleotide structures and complexes with proteins and were able to derive a sequence-dependent empirical energy function for the DNA helical elasticity. The approach also allows to investigate possible correlations between helical parameters that describe the flexibility of nucleic acids. However, it is not clear how well a set of crystal structures reflects the structural flexibility of DNA in solution. Alternatively, the progress in molecular mechanics force fields and simulation methodology has made it possible to investigate DNA helical flexibility using molecular dynamics (MD) simulations including surrounding water molecules and ions (reviewed in (23–26)). Such MD simulations of DNA result in stable structures close to the experimental DNA conformations on the nanosecond timescale and can be used to characterize the equilibrium fluctuations of helical parameters (27–31). Computational large-scale studies on many different DNA molecules have been used to study the sequence-dependence of DNA flexibility and are also helpful to improve the molecular mechanics force fields (32,33). However, unrestrained MD simulations may allow only a limited sampling of possible substates due to energy barriers. To better understand the molecular mechanism of elastic twist deformations in DNA, in the current study, MD simulations combined with a twistlike restraining potential and the umbrella sampling method were used. Simulations were performed on several 12-bp DNA oligo-nucleotides with different sequences and for a range of total twist angles of the central 9-bp steps. The simulations allowed us to calculate the total free energy change, to characterize the twist change of individual basepair steps and to analyze the change of other DNA helical parameters in response to external twist deformations. In addition, the onset of an untwisting transition starting from one end of a DNA helix was observed. MATERIALS AND METHODS Simulations were performed on six 12-bp B-DNA molecules (Table 1) with the general sequence (5′-CGCGNNNNCGCG)2 and six different central sequences (AATT, TATA, CGCG, GATC, CATG, CTAG). The central sequences cover each of the 10 possible basepair steps in DNA (AA, GG, GC, AG, TA, CG, CA, GC, AT, GT) at least once. Standard B-DNA start structures were generated using the Nucgen program of the AMBER8 package (34). Each system was neutralized by adding 22 K+ counter ions and solvated with ~4500 TIP3P water molecules (35) in a rectangular box using the xleap module of AMBER8. The simulation systems were subjected to energy minimization (1000 steps) using the Sander module. The PARM99 force field (36,37) was used for all simulations. During MD each DNA was initially harmonically restrained (25 kcal mol−1 Å−2) to the energy-minimized start coordinates and the system was heated up to 300 K in steps of 100 K followed by gradual removal of the positional restraints and 1-ns unrestraint equilibration of each system at 300 K. During MD the long-range electrostatic interactions were treated with the particle-mesh Ewald method (38) using a real-space cutoff distance of rcuttoff = 9 Å. The RATTLE algorithm (39) was used to constrain bond vibrations involving hydrogen atoms, which allowed a time step of 2 fs. To introduce the external twist stress, a modified version of the tornrg subroutine (which calculates the torsion-angle restraint energy in Sander) was used to harmonically restrain a twist angle between the second and eleventh basepair of each 12-bp duplex DNA. This twist angle (in the following termed τ) is formed by the distance vector between C1′ atoms of the 11th basepair projected onto the plane defined by the distance vector of C1′ atoms of the second basepair and the axis connecting the midpoints of the two pairs of C1′ atoms (see Fig. 1
RESULTS AND DISCUSSION Potential of mean force for DNA twist deformation Molecular dynamics umbrella sampling calculations including a twist-restraining potential were performed on six B-DNA oligonucleotides with different central basepairs (bp) and GC-rich flanking sequences (Table 1). The twist-restraining potential (Fig. 1 The range of twist values covered during the simulations was limited to an average 25–40° per bp step (Fig. 3
The optimal twist differs slightly between the six sequences (Table 1). As expected, the calculated free energy curves are not symmetric with respect to the twist minimum. Over-twisting of the DNA causes generally a stronger increase of the free energy compared to untwisting of the DNAs. The calculated PMFs can be approximated very well by a fourth-order polynomial (Table 1). The quadratic term which dominates for small twist deformations indicates a range of twist elastic constants between ~0.03 and ~0.07 kcal mol−1 deg−2. The calculated range of twist elastic constants is in very good agreement with available experimental data (18–21) and results of unrestrained DNA simulations that obtain effective force constants for twist deformations from twist distribution functions (29–31). It translates to a range of twist fluctuations per bp step (= sqrt (R T/ c), where R is the gas constant, T is the temperature, and c is the elastic constant) at room temperature of 3–5°. In terms of overall twist flexibility near the optimal twist, the central TATA sequence was the most flexible, followed by CATG, CTAG, and GATC (Table 1). The stiffest sequences, with respect to twist, are the DNAs with central AATT and central GCGC sequence. The overall modest variation of the effective twist flexibility among the various sequences agrees with the experimental observation based on DNA cyclization experiments (17–19) and time-resolved fluorescence polarization anisotropy (20,21). Twist flexibility of individual basepair steps Although the average twist flexibility/rigidity over a range of 10 basepairs (9-bp steps) showed only modest variation, the response of the individual bp steps on external twist stress is highly nonuniform (Figs. 4
Twist coupling to other helical parameters and nucleic acid backbone structure Besides twist, the helical parameters' slide and roll are the most variable in DNA (4,9–15). Also, the observed coupling between twist and slide or roll in known DNA structures is much stronger compared to the coupling to the helical parameters tilt and shift (4,9–12) and only the former are considered here. The extraction of correlations between helical parameters using available DNA oligonucleotide structures or unrestrained MD simulations requires large data sets to obtain statistically meaningful results. An advantage of the present simulation approach is that any average helical parameter and its dependence on twist can be directly extracted and plotted from simulations using different twist-restraining coordinates. The analysis of DNA crystal structures indicates a negative correlation between roll and twist (4) Such negative correlation was also found in the present study for every basepair step (Fig. 6 a As expected from the observed coupling of twist changes to other helical parameters—in particular, roll—the induced twist deformation also lead to an overall slight average bending of the DNAs (Fig. 7 a - and ζ-dihedral angles from t to −g and −g to t, respectively) were observed (~10% BII). This is slightly larger than what has been found in unrestrained simulations (~6% BII, (33)) and likely due to the fact that BI-BII transitions can affect the twist of DNA. However, no clear correlation between BII-state frequency and twist stress in the present twist range was observed (Fig. 9
Conformational changes upon extensive untwisting The purpose of this study was the analysis of free energy changes and DNA structural changes upon application of twist stress not too far from the equilibrium twist. The restriction was necessary because the present twist-coordinate is only appropriate in case of modest global conformational changes of the DNA. In addition, it was observed that the calculated free energy changes did not converge in the case of severe untwisting of DNA. Since, in this study, each DNA molecule consisted of self-complementary strands, it is expected that for fully reversible conformational deformations, the same behavior of identical basepair steps at symmetric positions in the structure should be observed. However, upon untwisting below an average applied twist of 25°, spontaneous untwisting transitions, starting from one end of the helix, were observed (Fig. 10
CONCLUSIONS Understanding DNA deformability in particular of the DNA-helical twist is of fundamental importance to understand processes like DNA recognition, packing, transcription, and replication. In this study, a molecular dynamics umbrella sampling approach was used to study systematically, on several different DNA molecules, the free energy change associated with an over- or untwisting of a segment of DNA. It was possible to extract the shape of the free energy curves versus applied twist restraint, and qualitatively similar curves for the six tested DNA molecules were observed. The approach goes beyond previous unrestrained simulations that do not allow us to directly extract the free energy change associated with DNA deformations. It also complements experimental single molecule studies (22) mostly performed on long DNAs that largely relax applied torsional stress through supercoiling and approaches that evaluate DNA flexibility indirectly from analyzing experimental DNA crystal structure (4–12). The current results are in very good agreement with available experimental data on the overall twist flexibility of DNA as well as on the local per-bp step flexibility and the coupling to other helical parameters. This result indicates that the structural variation seen in DNA crystal structures does indeed reflect to a significant degree the DNA flexibility in solution. The simulation study indicates that the strongly nonuniform local response to external twist stress can significantly alter the local arrangement of chemical groups recognized by ligands. In addition, twist stress can alter the overall shape of a DNA segment (Fig. 8 Acknowledgments This study was performed using the computational resources of the Computational Laboratories for Analysis, Modeling and Visualization at International University Bremen and supercomputer resources of the Environmental Molecular Science Laboratories at the Pacific Northwest National Laboratories, grant No. GC11-2002. S.K. is supported by the BIOlogical RECognition graduate program at International University Bremen and by a grant from the VolkswagenStiftung to M.Z. Notes Kai Kohlhoff's present address is Department of Chemistry, University of Cambridge, United Kingdom. References 1. Hagerman, P. J. 1990. Flexibility of DNA. Annu. Rev. Biochem. 59:755–781. [PubMed] 2. von Hippel, P. H., W. A. Rees, K. Rippe, and K. S. Wilson. 1996. Specificity mechanisms in the control of transcription. Biophys. Chem. 59:231–246. [PubMed] 3. Rhodes, D., J. W. Schwabe, L. Chapman, and L. Fairall. 1996. Before an understanding of protein-DNA recognition. Philos. Trans. R. Soc. Lond. B Biol. Sci. 351:501–509. [PubMed] 4. Olson, W. K., A. A. Gorin, X.-J. Lu, L. M. Hock, and V. B. Zhurkin. 1998. DNA sequence-dependent deformability deduced from protein-DNA crystal complexes. Proc. Natl. Acad. Sci. USA. 95:11163–11168. [PubMed] 5. Willenbrock, H., and D. W. Ussery. 2004. Chromatin architecture and gene expression in Escherichia coli. Genome Biol. 5:252. [PubMed] 6. Travers, A. A., and G. Muskhelishvili. 2005. Bacterial chromatin. Curr. Opin. Genet. Dev. 15:507–514. [PubMed] 7. Calladine, C. R. 1980. The principles of sequence-dependent flexure of DNA. J. Mol. Biol. 192:907–918. 8. Hunter, C. A. 1993. Sequence-dependent DNA structure. The role of base stacking interactions. J. Mol. Biol. 230:1025–1054. [PubMed] 9. Gorin, A. A., V. B. Zhurkin, and W. K. Olson. 1995. B-DNA twisting correlates with basepair morphology. J. Mol. Biol. 247:34–48. [PubMed] 10. El Hassan, M. A., and C. R. Calladine. 1995. The assessment of the geometry of dinucleotide steps in double-helical DNA: a new local calculation scheme. J. Mol. Biol. 251:648–664. [PubMed] 11. El Hassan, M. A., and C. R. Calladine. 1997. Conformational characteristics of DNA: empirical classifications and a hypothesis for the conformational behaviors of dinucleotide steps. Philos. Trans. R. Soc. Lond. A. 355:43–100. 12. Packer, M. J., M. P. Dauncey, and C. A. Hunter. 2000. Sequence-dependent DNA structure: tetranucleotide conformational maps. J. Mol. Biol. 295:85–103. [PubMed] 13. Travers, A. A., and J. M. T. Thompson. 2004. An introduction to the mechanics of DNA. Philos. Trans. R. Soc. Lond. A. 362:1265–1279. 14. Olson, W. K., D. Swigon, and B. D. Coleman. 2004. Implications of the dependence of the elastic properties of DNA on nucleotide sequence. Philos. Trans. R. Soc. Lond. A. 362:1403–1422. 15. Travers, A. A. 2004. The structural basis of DNA flexibility. Philos. Trans. R. Soc. Lond. A. 362:1423–1438. 16. Deremble, C., and R. Lavery. 2005. Macromolecular recognition. Curr. Opin. Struct. Biol. 15:171–175. [PubMed] 17. Hagerman, P. J. 1985. Analysis of ring-closure probabilities of isotropic worm-like chains: application to DNA. Biopolymers. 24:1881–1897. [PubMed] 18. Crothers, D. M., J. Drak, J. D. Kahn, and S. D. Levene. 1992. DNA bending, flexibility, and helical repeat by cyclization kinetics. Methods Enzymol. 212:3–29. [PubMed] 19. Kahn, J. D., E. Yun, and D. M. Crothers. 1994. Detection of localized DNA flexibility. Nature. 368:163–166. [PubMed] 20. Shibata, J. H., B. S. Fujimoto, and J. M. Schurr. 1985. Rotational dynamics of DNA from 10−10 to 10−5 seconds: comparison of theory with optical experiments. Biopolymers. 24:1909–1930. [PubMed] 21. Fujimoto, B. S., and J. M. Schurr. 1990. Dependence of the torsional rigidity of DNA on base composition. Nature. 344:175–178. [PubMed] 22. Bustamante, C., Z. Bryant, and S. B. Smith. 2003. Ten years of tension: single-molecule DNA mechanics. Nature. 421:423–426. [PubMed] 23. Cheatham III, T. E., and M. A. Young. 2001. Molecular dynamics simulation of nucleic acids: successes, limitations, and promise. Biopolymers. 56:232–256. 24. Giudice, E., and R. Lavery. 2002. Simulations of nucleic acids and their complexes. Acc. Chem. Res. 35:350–357. [PubMed] 25. MacKerell, A. D. 2004. Empirical force fields for biological macromolecules: overview and issues. J. Comput. Chem. 25:1584–1604. [PubMed] 26. Cheatham, T. E. 2004. Simulation and modeling of nucleic acid structure, dynamics and interactions. Curr. Opin. Struct. Biol. 14:360–367. [PubMed] 27. Flatters, D., and R. Lavery. 1998. Sequence-dependent dynamics of TATA-box binding sites. Biophys. J. 75:372–381. [PubMed] 28. Foloppe, N., and A. D. MacKerell. 2000. All-atom empirical force field for nucleic acids. 1. Parameter optimization based on small molecule and condensed phase macromolecular target data. J. Comput. Chem. 21:86–104. 29. Lankas, F. 2003. DNA sequence-dependent deformability-insights from computer simulations. Biopolymers. 73:327–339. 30. Lankas, F., J. Sponer, J. Langowski, and T. E. Cheatham. 2003. DNA deformability at the basepair level. J. Am. Chem. Soc. 126:4124–4125. 31. Lankas, F., J. Sponer, J. Langowski, and T. E. Cheatham. 2004. DNA basepair step deformability inferred from molecular dynamics simulations. Biophys. J. 85:2872–2883. 32. Beveridge, D. L., G. Barreiro, K. S. Byun, D. A. Case, T. E. Cheatham 3rd, S. B. Dixit, E. Giudice, F. Lankas, R. Lavery, J. H. Maddocks, R. Osman, E. Seibert, H. Sklenar, G. Stoll, K. M. Thayer, P. Varnai, and M. A. Young. 2004. Molecular dynamics simulations of the 136 unique tetranucleotide sequences of DNA oligonucleotides. I. Research design and results on d(CpG) steps. Biophys. J. 87:3799–3813. [PubMed] 33. Dixit, S. B., D. L. Beveridge, D. A. Case, T. E. Cheatham III, E. Giudice, F. Lankas, R. Lavery, J. H. Maddocks, R. Osman, H. Sklenar, K. M. Thayer, and P. Varnai. 2005. Molecular dynamics simulations of the 136 unique tetranucleotide sequences of DNA oligonucleotides. II. Sequence context effects on the dynamical structures of the 10 unique dinucleotide steps. Biophys. J. 89:3721–3740. [PubMed] 34. Case, D. A., D. A. Pearlman, J. W. Caldwell, T. E. Cheatham III, W. S. Ross, C. L. Simmerling, T. A. Darden, K. M. Merz, R. V. Stanton, A. L. Cheng, J. J. Vincent, M. Crowley, V. Tsui, R. J. Radmer, Y. Duan, J. Pitera, I. Massova, G. L. Seibel, U. C. Singh, P. K. Weiner, and P. A. Kollman. 2003. AMBER 8. University of California, San Francisco, CA. 35. Jorgensen, W., J. Chandrasekhar, J. Madura, R. Impey, and M. Klein. 1983. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79:926–935. 36. Cheatham III, T. E., P. Cieplak, and P. A. Kollman. 1999. A modified version of the Cornell et al. force field with improved sugar pucker phases and helical repeat. J. Biomol. Struct. Dyn. 16:845–862. [PubMed] 37. Duan, Y., C. Wu, S. Chowdhury, M. C. Lee, G. Xiong, W. Zhang, R. Yang, P. Cieplak, R. Luo, T. Lee, J. Caldwell, J. Wang, and P. Kollman. 2003. A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J. Comput. Chem. 24:1999–2012. [PubMed] 38. Darden, T. A., D. M. York, and L. Pedersen. 1993. Particle mesh Ewald: an NlogN method for Ewald sums in large systems. J. Chem. Phys. 98:10089–10092. 39. Miyamoto, S., and P. A. Kollman. 1992. SETTLE: an analytical version of the SHAKE and RATTLE algorithm for rigid water models. J. Comput. Chem. 13:952–962. 40. Lavery, R., and H. Sklenar. 1988. The definition of generalized helicoidal parameters and of axis curvature for irregular nucleic acids. J. Biomol. Struct. Dyn. 6:63–91. [PubMed] 41. Lavery, R., and H. Sklenar. 1988. Defining the structure of irregular nucleic acids: conventions and principles. J. Biomol. Struct. Dyn. 6:655–667. 42. Kumar, S., D. Bouzida, R. H. Swendsen, P. A. Kollman, and J. M. Rosenberg. 1992. The weighted histogram analysis method for free-energy calculations on biomolecules. I. The method. J. Comput. Chem. 13:1011–1021. 43. Grossfield, A. 2003. Http://dasher.wustl.edu/alan. 44. 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. 117:5179–5197. 45. Zacharias, M., and H. Sklenar. 2000. Conformational deformability of RNA: a harmonic mode analysis. Biophys. J. 78:2528–2542. [PubMed] 46. Zacharias, M. 2000. Comparison of molecular dynamics and harmonic mode calculations on RNA. Biopolymers. 54:547–560. [PubMed] 47. Barone, F., F. Lankas, N. Spackova, J. Sponer, P. Karran, M. Bignami, and F. Mazzei. 2005. Structural and dynamic effects of single 7-hydro-8-oxoguanine bases located in a frameshift target DNA sequence. Biophys. Chem. 118:31–41. [PubMed] |
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Annu Rev Biochem. 1990; 59():755-81.
[Annu Rev Biochem. 1990]Curr Opin Genet Dev. 2005 Oct; 15(5):507-14.
[Curr Opin Genet Dev. 2005]Proc Natl Acad Sci U S A. 1998 Sep 15; 95(19):11163-8.
[Proc Natl Acad Sci U S A. 1998]Curr Opin Struct Biol. 2005 Apr; 15(2):171-5.
[Curr Opin Struct Biol. 2005]Biopolymers. 1985 Oct; 24(10):1881-97.
[Biopolymers. 1985]Philos Trans R Soc Lond B Biol Sci. 1996 Apr 29; 351(1339):501-9.
[Philos Trans R Soc Lond B Biol Sci. 1996]Proc Natl Acad Sci U S A. 1998 Sep 15; 95(19):11163-8.
[Proc Natl Acad Sci U S A. 1998]Curr Opin Struct Biol. 2004 Jun; 14(3):360-7.
[Curr Opin Struct Biol. 2004]Biophys J. 1998 Jul; 75(1):372-81.
[Biophys J. 1998]Biophys J. 2004 Dec; 87(6):3799-813.
[Biophys J. 2004]Biophys J. 2005 Dec; 89(6):3721-40.
[Biophys J. 2005]J Biomol Struct Dyn. 1999 Feb; 16(4):845-62.
[J Biomol Struct Dyn. 1999]J Comput Chem. 2003 Dec; 24(16):1999-2012.
[J Comput Chem. 2003]J Biomol Struct Dyn. 1988 Aug; 6(1):63-91.
[J Biomol Struct Dyn. 1988]J Biomol Struct Dyn. 1988 Aug; 6(1):63-91.
[J Biomol Struct Dyn. 1988]J Biomol Struct Dyn. 1999 Feb; 16(4):845-62.
[J Biomol Struct Dyn. 1999]J Comput Chem. 2003 Dec; 24(16):1999-2012.
[J Comput Chem. 2003]Biophys J. 2004 Dec; 87(6):3799-813.
[Biophys J. 2004]Biophys J. 2005 Dec; 89(6):3721-40.
[Biophys J. 2005]Methods Enzymol. 1992; 212():3-29.
[Methods Enzymol. 1992]Nature. 1990 Mar 8; 344(6262):175-7.
[Nature. 1990]Biopolymers. 1985 Oct; 24(10):1881-97.
[Biopolymers. 1985]Nature. 1994 Mar 10; 368(6467):163-6.
[Nature. 1994]Biopolymers. 1985 Oct; 24(10):1909-30.
[Biopolymers. 1985]Biophys J. 2005 Dec; 89(6):3721-40.
[Biophys J. 2005]Nature. 1990 Mar 8; 344(6262):175-7.
[Nature. 1990]Biophys J. 2000 May; 78(5):2528-42.
[Biophys J. 2000]Biopolymers. 2000 Dec; 54(7):547-60.
[Biopolymers. 2000]Proc Natl Acad Sci U S A. 1998 Sep 15; 95(19):11163-8.
[Proc Natl Acad Sci U S A. 1998]J Mol Biol. 1995 Mar 17; 247(1):34-48.
[J Mol Biol. 1995]J Mol Biol. 2000 Jan 7; 295(1):85-103.
[J Mol Biol. 2000]Biophys Chem. 2005 Oct 22; 118(1):31-41.
[Biophys Chem. 2005]Biophys J. 2005 Dec; 89(6):3721-40.
[Biophys J. 2005]Nature. 2003 Jan 23; 421(6921):423-7.
[Nature. 2003]Proc Natl Acad Sci U S A. 1998 Sep 15; 95(19):11163-8.
[Proc Natl Acad Sci U S A. 1998]J Mol Biol. 2000 Jan 7; 295(1):85-103.
[J Mol Biol. 2000]J Biomol Struct Dyn. 1988 Aug; 6(1):63-91.
[J Biomol Struct Dyn. 1988]J Biomol Struct Dyn. 1988 Aug; 6(1):63-91.
[J Biomol Struct Dyn. 1988]J Biomol Struct Dyn. 1988 Aug; 6(1):63-91.
[J Biomol Struct Dyn. 1988]