Advanced search
1 file | 3.30 MB Add to list

Comparing normal modes across different models and scales: Hessian reduction versus coarse-graining

(2012) JOURNAL OF COMPUTATIONAL CHEMISTRY. 33(28). p.2250-2275
Author
Organization
Abstract
Dimension reduction is often necessary when attempting to reach longer length and time scales in molecular simulations. It is realized by constraining degrees of freedom or by coarse-graining the system. When evaluating the accuracy of a dimensional reduction, there is a practical challenge: the models yield vectors with different lengths, making a comparison by calculating their dot product impossible. This article investigates mapping procedures for normal mode analysis. We first review a horizontal mapping procedure for the reduced Hessian techniques, which projects out degrees of freedom. We then design a vertical mapping procedure for the implosion of the all-atom (AA) Hessian to a coarse-grained scale that is based upon vibrational subsystem analysis. This latter method derives both effective force constants and an effective kinetic tensor. Next, a series of metrics is presented for comparison across different scales, where special attention is given to proper mass-weighting. The dimension-dependent metrics, which require prior mapping for proper evaluation, are frequencies, overlap of normal mode vectors, probability similarity, Hessian similarity, collectivity of modes, and thermal fluctuations. The dimension-independent metrics are shape derivatives, elastic modulus, vibrational free energy differences, heat capacity, and projection on a predefined basis set. The power of these metrics to distinguish between reasonable and unreasonable models is tested on a toy alpha helix system and a globular protein; both are represented at several scales: the AA scale, a Go-like model, a canonical elastic network model, and a network model with intentionally unphysical force constants.
Keywords
normal mode analysis, chemical kinetics, NMA, effective Hessian, vibrational analysis, entropy, free energy, coarse-grained models, coarse-graining, kinetic tensor, elastic network model, heat capacity, CG, FREQUENCY NORMAL-MODES, ELASTIC NETWORK MODEL, MOLECULAR-DYNAMICS, HARMONIC-ANALYSIS, PROTEIN DYNAMICS, LARGE SYSTEMS, VIBRATIONAL ANALYSIS, SINGLE-PARAMETER, FORCE-FIELDS, MACROMOLECULES

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 3.30 MB

Citation

Please use this url to cite or link to this publication:

MLA
Ghysels, An, Benjamin T Miller, Frank C Pickard IV, et al. “Comparing Normal Modes Across Different Models and Scales: Hessian Reduction Versus Coarse-graining.” JOURNAL OF COMPUTATIONAL CHEMISTRY 33.28 (2012): 2250–2275. Print.
APA
Ghysels, A., Miller, B. T., Pickard, F. C., IV, & Brooks, B. R. (2012). Comparing normal modes across different models and scales: Hessian reduction versus coarse-graining. JOURNAL OF COMPUTATIONAL CHEMISTRY, 33(28), 2250–2275.
Chicago author-date
Ghysels, An, Benjamin T Miller, Frank C Pickard IV, and Bernard R Brooks. 2012. “Comparing Normal Modes Across Different Models and Scales: Hessian Reduction Versus Coarse-graining.” Journal of Computational Chemistry 33 (28): 2250–2275.
Chicago author-date (all authors)
Ghysels, An, Benjamin T Miller, Frank C Pickard IV, and Bernard R Brooks. 2012. “Comparing Normal Modes Across Different Models and Scales: Hessian Reduction Versus Coarse-graining.” Journal of Computational Chemistry 33 (28): 2250–2275.
Vancouver
1.
Ghysels A, Miller BT, Pickard FC IV, Brooks BR. Comparing normal modes across different models and scales: Hessian reduction versus coarse-graining. JOURNAL OF COMPUTATIONAL CHEMISTRY. 2012;33(28):2250–75.
IEEE
[1]
A. Ghysels, B. T. Miller, F. C. Pickard IV, and B. R. Brooks, “Comparing normal modes across different models and scales: Hessian reduction versus coarse-graining,” JOURNAL OF COMPUTATIONAL CHEMISTRY, vol. 33, no. 28, pp. 2250–2275, 2012.
@article{3066364,
  abstract     = {Dimension reduction is often necessary when attempting to reach longer length and time scales in molecular simulations. It is realized by constraining degrees of freedom or by coarse-graining the system. When evaluating the accuracy of a dimensional reduction, there is a practical challenge: the models yield vectors with different lengths, making a comparison by calculating their dot product impossible. This article investigates mapping procedures for normal mode analysis. We first review a horizontal mapping procedure for the reduced Hessian techniques, which projects out degrees of freedom. We then design a vertical mapping procedure for the implosion of the all-atom (AA) Hessian to a coarse-grained scale that is based upon vibrational subsystem analysis. This latter method derives both effective force constants and an effective kinetic tensor. Next, a series of metrics is presented for comparison across different scales, where special attention is given to proper mass-weighting. The dimension-dependent metrics, which require prior mapping for proper evaluation, are frequencies, overlap of normal mode vectors, probability similarity, Hessian similarity, collectivity of modes, and thermal fluctuations. The dimension-independent metrics are shape derivatives, elastic modulus, vibrational free energy differences, heat capacity, and projection on a predefined basis set. The power of these metrics to distinguish between reasonable and unreasonable models is tested on a toy alpha helix system and a globular protein; both are represented at several scales: the AA scale, a Go-like model, a canonical elastic network model, and a network model with intentionally unphysical force constants.},
  author       = {Ghysels, An and Miller, Benjamin T and Pickard, Frank C, IV and Brooks, Bernard R},
  issn         = {0192-8651},
  journal      = {JOURNAL OF COMPUTATIONAL CHEMISTRY},
  keywords     = {normal mode analysis,chemical kinetics,NMA,effective Hessian,vibrational analysis,entropy,free energy,coarse-grained models,coarse-graining,kinetic tensor,elastic network model,heat capacity,CG,FREQUENCY NORMAL-MODES,ELASTIC NETWORK MODEL,MOLECULAR-DYNAMICS,HARMONIC-ANALYSIS,PROTEIN DYNAMICS,LARGE SYSTEMS,VIBRATIONAL ANALYSIS,SINGLE-PARAMETER,FORCE-FIELDS,MACROMOLECULES},
  language     = {eng},
  number       = {28},
  pages        = {2250--2275},
  title        = {Comparing normal modes across different models and scales: Hessian reduction versus coarse-graining},
  url          = {http://dx.doi.org/10.1002/jcc.23076},
  volume       = {33},
  year         = {2012},
}

Altmetric
View in Altmetric
Web of Science
Times cited: