Figure 10.

Structure-based models capture near-native-state fluctuations of both small proteins and large macromolecular assemblies. (A) Comparison of simulated root mean squared fluctuations (rmsf) of each residue in the 23S Ribosomal RNA (PDB codes: 3F1E, 3F1F) between the scaled cutoff map $M_4^{0\ast }$ and the Shadow map $M_6^1$. Overlaid are the rmsf by residue, calculated using the experimental B-factors (using the isotropic approximation, $\text{rmsf}\equiv \sqrt{\langle r_i^2\rangle }\sim \frac{3}{8{\pi }^2}{B}_i$, where r_i is the displacement of atom i and B_i is the experimental B-factor of atom i⁶²). A residue rmsf is computed as the arithmetic average of its constituent atoms’ rmsf. Overall rmsf agreed with the B-factors for $M_4^{0\ast }$ at T = 0.46, and $M_6^1$ at T = 0.71. The discrepancy in stability is likely due to $M_6^1$ including double the Mg²⁺-RNA contacts, which are modeled as harmonic restraints instead of Gaussian contact potentials. Pearson correlation r between $M_6^1$ and B-factors is 0.78. (B) Simulated rmsf of the C_α atoms for three globular proteins at T = 0.9. The overall agreement is very close (r > 0.9) between two different contact maps, $M_4^0$ and $M_6^1$.