Efficient calculation of configurational entropy from molecular simulations by combining the mutual-information expansion and nearest-neighbor methods

Journal of Computational Chemistry

Volumn 29, Issue 10, 2008, Pages 1605-1614

  Hnizdo, Vladimir ^a   Jun, Tan ^b   Killian, Benjamin J ^c   Gilson, Michael K ^c  

^a National Institute of Occupational Health and Safety   (United States)

^b WEST VIRGINIA UNIVERSITY   (United States)

^c UNIVERSITY OF MARYLAND BIOTECHNOLOGY INSTITUTE   (United States)

Author keywords

Configurational entropy; Dimension reduction; Many body correlations; Molecular simulations; Mutual information; Nearest neighbor

Indexed keywords

COMBINED METHODS; COMPUTATIONAL CHALLENGES; COMPUTING TIME; CONFIGURATIONAL ENTROPY; CONFORMATIONAL CHANGES; DATA SAMPLES; DEGREES OF FREEDOM; HIGH-DIMENSIONAL SYSTEMS; HIGHER ORDER; HIGHER ORDER CORRELATIONS; HISTOGRAMMING; INTERNAL DEGREES OF FREEDOM; INTERNAL ROTATION (IR); JOINT ENTROPY (JE); MANY-BODY CORRELATIONS; MOLECULAR SIMULATIONS; MUTUAL INFORMATION (MI); NEAREST NEIGHBOR (NN); NN METHOD; NON-PARAMETRIC; NONCOVALENT ASSOCIATION; PROTEIN-FOLDING; SAMPLE SIZES; SIMPLE SYSTEMS; SYSTEMATIC EXPANSION; TARTARIC ACID (TA); THIRD-ORDER;

ASSOCIATION REACTIONS; CALCULATIONS; CORRELATION METHODS; ESTIMATION; MECHANICS; MOLECULAR STRUCTURE; MOLECULES; POLYNOMIAL APPROXIMATION; PROBABILITY DISTRIBUTIONS; PROTEIN FOLDING; ROTATION;

ENTROPY;

TARTARIC ACID; TARTARIC ACID DERIVATIVE;

ARTICLE; CHEMICAL MODEL; CHEMISTRY; COMPUTER SIMULATION; CONFORMATION; ENTROPY;

COMPUTER SIMULATION; ENTROPY; MODELS, CHEMICAL; MOLECULAR CONFORMATION; TARTRATES;

EID: 46449096350     PISSN: 01928651     EISSN: 1096987X     Source Type: Journal    
DOI: 10.1002/jcc.20919     Document Type: Article

References (19)

1. Karplus, M.; Kushick, J. N. Macromolecules 1981, 14, 325.
2. Levy, R. M.; Karplus, M.; Kushick, J.; Perahia, D. Macromolecules 1984, 17, 1370.
3. Chang, C.-E.; Chen, W.; Gilson, M. K. J Chem Theory Comput 2005, 1, 1017.
4. Hnizdo, V.; Darian, E.; Fedorowicz, A.; Demchuk, E.; Li, S.; Singh, H. J Comput Chem 2007, 28, 655.
5. Singh, H.; Misra, N.; Hnizdo, V.; Fedorowicz, A.; Demchuk, E. Am J Math Manag Sci 2003, 23, 301.
6. Goria, M. N.; Leonenko, N. N.; Mergel, V. V.; Novi Inveradi, P. L. J Nonparametr Stat 2005, 17, 277.
7. Scott, D. W. Multivariate Density Estimation: Theory, Practice, and Visualization; John Wiley and Sons: New York, 1992.
8. Killian, B. J.; Kravitz, J. Y.; Gilson, M. K. J Chem Phys 2007, 127, 024107.
9. Matsuda H. Phys Rev E 2000, 62, 3096.
10. Cover, T. M.; Thomas, J. A. Elements of Information Theory; Wiley: New York, 1991.
11. Kraskov A.; Stögbauer, H.; Grassberger P. Phys Rev E 2004, 69, 066138.
12. Lange, O. F.; Grubmüller, H. Proteins 2006, 62, 1053.
13. Hartigan, J. A. Clustering Algorithms; Wiley: New York, 1975.
14. Singh, H.; Hnizdo, V.; Demchuk, E. Biometrika 2002, 89. 719.
15. Knuth, D. E. The Art of Computer Programming, 3rd ed.; Addison-Wesley: New York, 2004. http://www-cs-faculty.stanford.edu/~knuth/ programs.html.
16. Press, W. H.; Teukolsky, S. A.; Vetterling. W. T.; Flannery, B. P. Numerical Recipes in Fortran, 2nd ed.; Cambridge University Press: New York, 1992.
17. Friedman, J. H.; Bentley, J. L.; Finkel, R. A. ACM Trans Math Software 1977, 3, 209.
18. Arya, S.; Mount, D. M. Approximate nearest neighbor searching. In Proceedings of the Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, 1993; p. 271. http://www.cs.umd.edu/~mount/ANN/.
19. Mountain, R. D.; Raveché, H. J. J Phys Chem 1971, 55, 2250.