Characterizing global substates of myoglobin

B. Kim Andrews, Tod Romo, James B. Clarage, Bernard Pettitt, George N. Phillips

Research output: Contribution to journalArticle

37 Citations (Scopus)

Abstract

Background: The massive amount of information generated from current molecular dynamics simulations makes the data difficult to analyze efficiently. Principal component analysis has been used for almost a century to detect and characterize data relationships and to reduce the dimensionality for problems in many fields. Here, we present an adaptation of principal component analysis using a partial singular value decomposition (SVD) for investigating both the localized and global motions of macromolecules. Results: Configuration space projections from the SVD analysis of a variety of myoglobin simulations are used to characterize the dynamics of the protein. This technique reveals new dynamical motifs, which quantify proposed hierarchical structures of conformational substates for proteins and provide a means by which configuration space sampling efficiency may be probed. The SVD clearly shows that solvent effects facilitate transitions between global conformational substates for myoglobin molecular dynamics simulations. Lyapunov exponents calculated from the configuration space divergence of 15 trajectories agree with previous predictions for the chaotic behavior of complex protein systems. Conclusions: Configuration space projections provide invaluable information about protein motions that would be extremely difficult to obtain otherwise. While the configuration space for myoglobin is quite large, it does have structure. Our analysis of this structure shows that the protein hops between a number of distinct global conformational states, much like the local behavior observed for an individual residue.

Original languageEnglish (US)
Pages (from-to)587-594
Number of pages8
JournalStructure
Volume6
Issue number5
StatePublished - May 15 1998
Externally publishedYes

Fingerprint

Myoglobin
Molecular Dynamics Simulation
Principal Component Analysis
Proteins
Humulus

Keywords

  • Conformational substates
  • Molecular dynamics
  • Myoglobin
  • Phase space

ASJC Scopus subject areas

  • Molecular Biology
  • Structural Biology

Cite this

Andrews, B. K., Romo, T., Clarage, J. B., Pettitt, B., & Phillips, G. N. (1998). Characterizing global substates of myoglobin. Structure, 6(5), 587-594.

Characterizing global substates of myoglobin. / Andrews, B. Kim; Romo, Tod; Clarage, James B.; Pettitt, Bernard; Phillips, George N.

In: Structure, Vol. 6, No. 5, 15.05.1998, p. 587-594.

Research output: Contribution to journalArticle

Andrews, BK, Romo, T, Clarage, JB, Pettitt, B & Phillips, GN 1998, 'Characterizing global substates of myoglobin', Structure, vol. 6, no. 5, pp. 587-594.
Andrews BK, Romo T, Clarage JB, Pettitt B, Phillips GN. Characterizing global substates of myoglobin. Structure. 1998 May 15;6(5):587-594.
Andrews, B. Kim ; Romo, Tod ; Clarage, James B. ; Pettitt, Bernard ; Phillips, George N. / Characterizing global substates of myoglobin. In: Structure. 1998 ; Vol. 6, No. 5. pp. 587-594.
@article{7a843070af8f4365af7702aadc768aa9,
title = "Characterizing global substates of myoglobin",
abstract = "Background: The massive amount of information generated from current molecular dynamics simulations makes the data difficult to analyze efficiently. Principal component analysis has been used for almost a century to detect and characterize data relationships and to reduce the dimensionality for problems in many fields. Here, we present an adaptation of principal component analysis using a partial singular value decomposition (SVD) for investigating both the localized and global motions of macromolecules. Results: Configuration space projections from the SVD analysis of a variety of myoglobin simulations are used to characterize the dynamics of the protein. This technique reveals new dynamical motifs, which quantify proposed hierarchical structures of conformational substates for proteins and provide a means by which configuration space sampling efficiency may be probed. The SVD clearly shows that solvent effects facilitate transitions between global conformational substates for myoglobin molecular dynamics simulations. Lyapunov exponents calculated from the configuration space divergence of 15 trajectories agree with previous predictions for the chaotic behavior of complex protein systems. Conclusions: Configuration space projections provide invaluable information about protein motions that would be extremely difficult to obtain otherwise. While the configuration space for myoglobin is quite large, it does have structure. Our analysis of this structure shows that the protein hops between a number of distinct global conformational states, much like the local behavior observed for an individual residue.",
keywords = "Conformational substates, Molecular dynamics, Myoglobin, Phase space",
author = "Andrews, {B. Kim} and Tod Romo and Clarage, {James B.} and Bernard Pettitt and Phillips, {George N.}",
year = "1998",
month = "5",
day = "15",
language = "English (US)",
volume = "6",
pages = "587--594",
journal = "Structure with Folding & design",
issn = "0969-2126",
publisher = "Cell Press",
number = "5",

}

TY - JOUR

T1 - Characterizing global substates of myoglobin

AU - Andrews, B. Kim

AU - Romo, Tod

AU - Clarage, James B.

AU - Pettitt, Bernard

AU - Phillips, George N.

PY - 1998/5/15

Y1 - 1998/5/15

N2 - Background: The massive amount of information generated from current molecular dynamics simulations makes the data difficult to analyze efficiently. Principal component analysis has been used for almost a century to detect and characterize data relationships and to reduce the dimensionality for problems in many fields. Here, we present an adaptation of principal component analysis using a partial singular value decomposition (SVD) for investigating both the localized and global motions of macromolecules. Results: Configuration space projections from the SVD analysis of a variety of myoglobin simulations are used to characterize the dynamics of the protein. This technique reveals new dynamical motifs, which quantify proposed hierarchical structures of conformational substates for proteins and provide a means by which configuration space sampling efficiency may be probed. The SVD clearly shows that solvent effects facilitate transitions between global conformational substates for myoglobin molecular dynamics simulations. Lyapunov exponents calculated from the configuration space divergence of 15 trajectories agree with previous predictions for the chaotic behavior of complex protein systems. Conclusions: Configuration space projections provide invaluable information about protein motions that would be extremely difficult to obtain otherwise. While the configuration space for myoglobin is quite large, it does have structure. Our analysis of this structure shows that the protein hops between a number of distinct global conformational states, much like the local behavior observed for an individual residue.

AB - Background: The massive amount of information generated from current molecular dynamics simulations makes the data difficult to analyze efficiently. Principal component analysis has been used for almost a century to detect and characterize data relationships and to reduce the dimensionality for problems in many fields. Here, we present an adaptation of principal component analysis using a partial singular value decomposition (SVD) for investigating both the localized and global motions of macromolecules. Results: Configuration space projections from the SVD analysis of a variety of myoglobin simulations are used to characterize the dynamics of the protein. This technique reveals new dynamical motifs, which quantify proposed hierarchical structures of conformational substates for proteins and provide a means by which configuration space sampling efficiency may be probed. The SVD clearly shows that solvent effects facilitate transitions between global conformational substates for myoglobin molecular dynamics simulations. Lyapunov exponents calculated from the configuration space divergence of 15 trajectories agree with previous predictions for the chaotic behavior of complex protein systems. Conclusions: Configuration space projections provide invaluable information about protein motions that would be extremely difficult to obtain otherwise. While the configuration space for myoglobin is quite large, it does have structure. Our analysis of this structure shows that the protein hops between a number of distinct global conformational states, much like the local behavior observed for an individual residue.

KW - Conformational substates

KW - Molecular dynamics

KW - Myoglobin

KW - Phase space

UR - http://www.scopus.com/inward/record.url?scp=0032524416&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032524416&partnerID=8YFLogxK

M3 - Article

C2 - 9634696

AN - SCOPUS:0032524416

VL - 6

SP - 587

EP - 594

JO - Structure with Folding & design

JF - Structure with Folding & design

SN - 0969-2126

IS - 5

ER -