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.