The slow convergence of the ligand-protein systems cannot be attributed simply to their size (∼20,000 atoms), because the free ligand systems (above) have a similar number of atoms (∼18,000), yet converge far more rapidly. We conjectured that slow motions of the protein in the complexes delay convergence by generating long correlation times not present in the free ligand simulations; we used principal component analysis (PCA) to test for such slow motions. For each complex and free ligand system, we combined the two replicate trajectories (runs A and B), computed the covariance matrix for the combined trajectory, and then projected each individual trajectory onto the combined trajectory's first principal component (PC). This is the PC with the largest eigenvalue, which means that captures the greatest structural variance. Graphs of the resulting projections over time, and normalized histograms of these projections, are shown in Figures and. The histograms for the complex simulations (right column of Fig. ) show that the two matched runs, A and B, sampled the leading PC differently. This result points to large-scale, slow motions as a possible factor in the slow convergence of the mean potential energies of the protein-ligand complexes. For the free ligands, in contrast, the Run A and Run B histograms overlap well (right column of Fig. ), indicating that the sampling along their leading PCs is similar between these two independent simulations. This result is consistent with the relatively facile convergence of the free ligand potential energies.