|
|
|
 Full Correlation Analysis |
|
|
|
|
Full Correlation Analysis of Conformational Protein Dynamics
|
|
Oliver F. Lange and Helmut Grubmüller
Collective coordinates for protein motions can be extracted from MD
simulations with established methods, mainly via calculation of the
covariance matrix and subsequent principal component analysis (PCA) [1]. This
established approach, however, relies on quasi-harmonic treatment of
the configurational ensemble and, therefore, detects only linearly
correlated motions. Full Correlation Analysis (FCA)
utilizes an information theoretical approach that detects and
quantifies any correlated motion [2]. In this way, FCA yields a
low dimensional representation of protein dynamics that often features
more functional details than a representation obtained with PCA [3].
The g_fca tool allows to perform a full correlation analysis and can be used within the GROMACS
framework. To use it, you also need to install GROMACS; please read the file INSTALL file for instructions.
The software is free for everyone. However, if you use it for
publications or presentations I ask you to cite the original
publication [3]. Please note that the software is distributed with NO WARRANTY OF ANY KIND. The author
is not responsible for any losses or damages suffered directly or
indirectly from the use of the software. Use it at your own risk. (C) Oliver Lange, 2005
|
| |
|
Literature
|
|
- Amadei A, Linssen ABM, Berendsen HJC: Essential dynamics of proteins. Proteins 17, 412-425 (1993)
- Lange O, Grubmülller H: Generalized Correlation for Biomolecular Dynamics. Proteins 62, 1053-1061 (2006)
[pdf]
- Lange O, Grubmülller H: Full Correlation Analysis of Conformational Protein Dynamics. Proteins 70, 1294-1312 (2008)
[pdf]
|
| |
|
|
|
Top