This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.Correlated protein motions are of great functional significance and have been the target of various experimental and computational studies. Both molecular dynamics (MD) simulation and normal mode analysis (NMA) are able to provide information about the internal protein dynamics. Starting from a limited sampling of the protein conformation space, usually a section of MD simulation trajectory, principal component analysis (PCA, or essential dynamics) teases out the correlation motions through a diagonalization of the covariance matrix for the relevant atom group. The direction and amplitude of the vibrational modes are represented by the resulting eigenvectors and the corresponding eigenvalues, respectively. On the other hand, based on a harmonic assumption of the protein energy surface, normal mode analysis (NMA) yields the direction and amplitude of the correlated motion through diagonalization of the Hessian matrix, which contains the second derivative of the protein energy surface. Due to a limitation of computational resources, NMA approaches at different resolutions, from simplest elastic network model (ENM), block normal mode (BNM), to the classical all-atom normal mode methods, have been used more often than the time consuming MD-based PCA approach. However, the harmonic assumption of the energy surface and the implicit treatment of solvent make the NMA difficult to reproduce the often diffusive and anharmonic nature of protein dynamics. Here I propose to carry out parallel NMA and MD simulations on selected high resolution X-ray structures and comparing the results from both computational approaches to the experimentally determined parameters, including the isotropic vibrational amplitudes and anisotropic vibrational directionality. It is expected that MD-based PCA would bring a closer match to the experimental observations than does NMA.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR006009-18
Application #
7723369
Study Section
Special Emphasis Panel (ZRG1-BCMB-Q (40))
Project Start
2008-08-01
Project End
2009-07-31
Budget Start
2008-08-01
Budget End
2009-07-31
Support Year
18
Fiscal Year
2008
Total Cost
$473
Indirect Cost
Name
Carnegie-Mellon University
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
052184116
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
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