Principal Component Analysis
The principal component analysis (PCA), also called essential dynamics
analysis is an important statistical analysis tool which helps in
analyzing protein motions by dimensionality reduction. It filters the
trajectories and helps identify the essential motions or the
functionally relevant motions of the protein [41]. We performed PCA
analysis of peptides in each system using the gmx cover & gmx anaeig,
by diagonalizing the covariance matrix of atomic coordinates.
The plot showing the eigenvalues and eigenvectors of the five simulated
systems are given in Figure S3 in supporting information.The 2D
projections of the first two PCs were plotted (Figure 3) , with
each dot representing a conformation space occupied by the protein.