Analysis of the conformational dependence of mass-metric tensor determinants in serial polymers with constraints

Journal of Chemical Physics

Volumn 121, Issue 24, 2004, Pages 12708-12720

  Patriciu, Alexandru ^a,b   Chirikjian, Gregory S ^a,b   Pappu, Rohit V ^a,b  

^a Johns Hopkins University   (United States)

^b WASHINGTON UNIVERSITY IN ST LOUIS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHAIN CONFORMATIONS; CHAIN LENGTH; JOHN HOPKINS UNIVERSITY; MASS-METRIC TENSOR DETERMINANTS;

ALGORITHMS; COMPUTER SIMULATION; CONFORMATIONS; MONTE CARLO METHODS; PHASE EQUILIBRIA; PHASE TRANSITIONS; POTENTIAL ENERGY; TENSORS;

POLYMERS;

EID: 22944493028     PISSN: 00219606     EISSN: None     Source Type: Journal    
DOI: 10.1063/1.1821492     Document Type: Article

References (74)

1. A. Yu. Grosberg and A. R. Khokhlov, Statistical Physics of Macromolecules, AIP Series in Polymers and Complex Materials (AIP, New York, 1994).
2. M. Rubinstein and R. H. Colby, Polymer Physics (Oxford University Press, New York, 2003).
3. C. L. Brooks, M. Karplus, and B. M. Pettitt, Adv. Chem. Phys. 71, 19 (1988).
4. F. Müller-Plathe, ChemPhysChem 3, 754 (2003).
5. D. Frenkel and B. Smit, Understanding Molecular Simulation, from Algorithms to Applications, Computational Science Series (Academic, New York, 2000).
6. M. P. Allen and D. J. Tildesley, Computer Simulation of Liquids (Oxford Science, Oxford, UK, 1987), Chap. 2.
7. J. Baschnagel, K. Binder, P. Doruker et al., Adv. Polym. Sci. 152, 41 (2000).
8. D. L. Ermak and J. A. McCammon, J. Chem. Phys. 69, 1352 (1978).
9. M. Fixman, J. Chem. Phys. 69, 1527 (1978).
10. D. A. Beard and T. Schlick, J. Chem. Phys. 112, 7313 (2000).
11. C. F. Wong and J. A. McCammon, Annu. Rev. Pharmacol. Toxicol. 43, 31 (2003).
12. H. A. Carlson and J. A. McCammon, Mol. Pharmacol. 57, 213 (2000).
13. M. Mihailescu and M. K. Gilson, Biophys. J. 87, 23 (2004).
14. E. Leontidis, B. M. Forrest, A. H. Widmann, and U. W. Suter, J. Chem. Soc., Faraday Trans. 91, 2355 (1995).
15. B. M. Forrest and U. W. Suter, J. Chem. Phys. 101, 2616 (1994).
16. K. Binder and D. W. Heerman, Monte Carlo Simulation in Statistical Physics (Springer, Berlin, 1997).
17. N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, and E. Teller, J. Chem. Phys. 21, 1087 (1953).
18. J. Fernandez-Recio, M. Totrov, and R. Abagyan, Proteins: Struct., Funct., Genet. 52, 113 (2003).
19. V. Katritch, M. Totrov, and R. Abagyan, J. Comput. Chem. 24, 254 (2003).
20. J. D. Schieber, P. Biller, and F. Petruccione, J. Chem. Phys. 94, 1592 (1991).
21. A macroscopically serial chain is either a linear chain of point masses or equivalently a macromolecule that may contain local branches - local articulation - but appears serial over long length scales.
22. H. A. Kramers, J. Chem. Phys. 14, 415 (1946).
23. W. F. van Günsteren and M. Karplus, Macromolecules 15, 1528 (1982).
24. J. J. Erpenbeck and J. G. Kirkwood, J. Chem. Phys. 29, 909 (1956).
25. M. Fixman, Proc. Natl. Acad. Sci. U.S.A. 74, 3050 (1974).
26. H. J. C. Berendsen and W. F. van Günsteren, The Physics of Superionic Conductors and Electrode Materials, NATO Advanced Studies Institute, Series B: Physics, edited by J. W. Perram (Plenum, New York, 1980), Vol. 92, Chap. 12, p. 221.
27. M. Fixman and J. Kovac, J. Chem. Phys. 61, 4939 (1974).
28. N. Gō and H. A. Scheraga, Macromolecules 9, 535 (1976).
29. E. Helfand, J. Chem. Phys. 71, 5000 (1979).
30. M. R. Pear and J. H. Weiner, J. Chem. Phys. 71, 212 (1979).
31. D. Chandler and B. J. Berne, J. Chem. Phys. 71, 5386 (1979).
32. E. Helfand, Z. R. Wasserman, and T. A. Weber, Macromolecules 13, 526 (1980).
33. J. Skolnick and E. Helfand, J. Chem. Phys. 72, 5489 (1980).
34. E. Helfand, Z. R. Wasserman, T. A. Weber, J. Skolnick, and J. R. Runnels, J. Chem. Phys. 75, 4441 (1981).
35. W. F. van Günsteren, Mol. Phys. 40, 1015 (1980).
36. M. Karplus and J. Kushick, Macromolecules 14, 325 (1981).
37. A. Mazur, V. Dorofeev, and R. Abagyan, J. Comput. Phys. 92, 261 (1991).
38. A. Jain, J. Comput. Phys. 136, 289 (1997).
39. L. Brillouin, Tensors in Mechanics and Elasticity (Academic, New York, 1964).
40. H. M. Chun, C. E. Padilla, D. N. Chin et al., J. Comput. Chem. 21, 159 (2000).
41. M. Pasquali and D. C. Morse, J. Chem. Phys. 116, 1834 (2002).
42. A. K. Mazur, J. Comput. Chem. 18, 1354 (1997).
43. H. M. Ådland and A. Mikkelsen, J. Chem. Phys. 120, 9848 (2004).
44. W. L. Jorgensen, BOSS (Yale University Press, New Haven, CT, 1997).
45. J. Schofield and M. A. Ratner, J. Chem. Phys. 109, 9177 (1998).
46. Y.-H. Lin and Z.-H. Luo, J. Chem. Phys. 112, 7219 (2000).
47. L. R. Dodd, T. D. Boone, and D. N. Theodorou, Mol. Phys. 78, 961 (1993).
48. D. Hoffmann and E.-W. Knapp, Phys. Rev. E 53, 4221 (1996).
49. s).
50. S. K. Saha, IEEE Trans. Rob. Autom. 13, 301 (1997).
51. S. K. Saha, Int. J. Robot. Res. 18, 116 (1999).
52. A. F. Vereshcagin, Eng. Cybernet. 12, 65 (1974).
53. D. S. Bae and E. J. Haug, Mech. Struct. Mach. 15, 359 (1987).
54. K. S. Anderson and J. H. Critchley, Multibody Syst. Dyn. 9, 185 (2003).
55. W. W. Armstrong, Proceedings of the Fifth World Conference on Theory of Machines and Mechanics, edited by the American Society of Mechanical Engineers, New York, 1979, p. 1343.
56. M. W. Walker and D. E. Orin, ASME J. Dyn. Syst., Meas., Control 104, 205 (1982).
57. G. E. Stewart, Introduction to Matrix Computations (Academic, New York, 1973).
58. G. Rodriguez and K. Kreutz-Delgado, IEEE Trans. Rob. Autom. 8, 65 (1992).
59. G. Rodriguez, IEEE Trans. Rob. Autom. 3, 624 (1987).
60. A. Vaidehi, A. Jain, and W. Goddard, J. Phys. Chem. 100, 10508 (1996).
61. A. Jain, N. Vaidehi, and G. Rodriguez, J. Comput. Phys. 106, 258 (1993).
62. B. D. O. Anderson and J. B. Moore, Optimal Filtering (Prentice-Hall, Englewood Cliffs, NJ, 1979).
63. For more information regarding Newton-Euler Inverse Mass Operator (NEIMO) software package for torsional space molecular dynamics simulations of large macromolecules, see http://dartslab.jpl.nasa.gov/NEIMO/index.php
64. H. Goldstein, Classical Mechanics, 2nd ed. (Addison Wesley, Reading, 1980).
65. In the ZXZ convention, the matrix for transformations form a space-fixed set of axes to a frame of reference attached to a mass point is written as A = cosγcosα-cosβsinαsinγ -sinγcosα- cosβsinαsinγ sinβsinγ cosγcosα+cosβ sinαsinγ -sinγcosα+cosβsinαsinγ -sinβcosα sinγsinα cosγsinα cosβ (Ref. 64). Goldstein (Ref. 64) refers to the ZXZ convention as the x convention.
66. 1 0.
67. J. Angeles and S. Lee, ASME J. Appl. Mech. 55, 243 (1988).
68. G. S. Chirikjian and A. B. Kyatkin, Engineering Applications of Noncommutative Harmonic Analysis - with Emphasis on Rotation and Motion Groups (CRC, Boca Raton, 2001).
69. C. T. Kelley, Iterative Methods for Optimization, Frontiers in Applied Mathematics SIAM, Philadelphia, PA, Chap. 8, p. 145.
70. Ordered and disordered conformations can be distinguished based on the relationship between the values of successive torsion angles. If all of the torsion angles assume roughly equivalent values, an ordered or regular helical conformation results. However, if the torsion angle values are completely dissimilar and irregular conformation results and we use the term random-coil to denote this state of static disorder.
71. M. Laso, J. J. de Pablo, and U. W. Suter, J. Chem. Phys. 97, 2817 (1992).
72. S. Consta, T. J. H. Vlugt, J. Wichers Hoeth, B. Smit, and D. Frenkel, Mol. Phys. 97, 1243 (1999).
73. M. Bishop, D. Ceperley, H. L. Frisch, and M. H. Kalos, J. Chem. Phys. 72, 3228 (1980).
74. D. Perchak, J. Skolnick, and R. Yaris, Macromolecules 18, 519 (1985).