Accurate Structural Correlations from Maximum Likelihood Superpositions
Figure 2
PCA Plots of Least-Squares and ML Superpositions of Simulated Structures
The first principal component (PC) is plotted on the mean structure for various calculations. As in Figure 1, the upper row (A–D) uses a covariance matrix in which all correlations are zero (no correlation), whereas the lower row (E–H) uses a covariance matrix with strong correlations. Red regions are self-correlated, as are blue regions, while blue versus red regions are anti-correlated. White regions indicate no correlation.
(A, E) The true first PC, extracted from the known correlation matrices.
(B, F) The first PC based on the all-atom least-squares superposition.
(C, G) The first PC from a least-squares superposition that excluded residues 1–5 with the largest variance in the simulation.
(D, H) The first PC based on the ML superposition.