Quantitative characterization of molecular motions using Rigid Body Transformation in molecular dynamics simulations

Molecular dynamics (MD) simulations provide valuable insights into biomolecular interactions by analyzing atomic-level motion. However, conventional analysis primarily relies on positional metrics, which often fail to capture the relative direction of molecules or potentially degrade the actual molecular motion due to RMSD-based preprocessing. In this study, we introduce a Rigid Body Transformation (RBT)-based approach to assess molecular movements quantitatively. To validate our method, we applied controlled transformations, including translation, rotation, and noise addition, to artificially generated motion data. The RBT-based alignment successfully restored the original configurations with near-zero reconstruction errors, demonstrating its robustness in preserving motion similarity even under noisy conditions. Furthermore, our approach effectively characterized the dynamics of a designed complex, distinguishing positional and orientational linear relationships in motion patterns. Additionally, we applied our method to MD data of the Q108R CRBP(I)-atREA complex. While conventional salt-bridge analysis suggested persistent interactions between Lys-40 and Arg-108, our center of mass (COM) and dipole moment analysis revealed distinct dynamic behaviors, aligning with experimental findings. These results highlight the importance of incorporating both positional and orientational consistency in MD data analysis, offering new insights into biomolecular motion. RBT-based alignment enables precise comparison of molecular trajectories in three dimensions.RBT restores trajectory similarity even under translation, rotation, and significant noise conditions.Linear correlation (R2) analysis provides a robust trajectory similarity measure.RBT-based method distinguishes strong and weak molecular interactions in complex systems.Dipole moment correlation analysis reveals interaction differences not captured by conventional position metrics. RBT-based alignment enables precise comparison of molecular trajectories in three dimensions. RBT restores trajectory similarity even under translation, rotation, and significant noise conditions. Linear correlation (R2) analysis provides a robust trajectory similarity measure. RBT-based method distinguishes strong and weak molecular interactions in complex systems. Dipole moment correlation analysis reveals interaction differences not captured by conventional position metrics.