How Molecular Size Impacts RMSD Applications in Molecular Dynamics Simulations

Area of Science:

• Computational biology
• Structural bioinformatics
• Molecular dynamics

Background:

• Root-mean-square deviation (RMSD) is a key metric for comparing macromolecular structures.
• The
• curse of dimensionality
• may hinder discrimination of conformations in large systems.
• Its impact on RMSD analysis for large biomolecules was previously unaddressed.

Purpose of the Study:

• To investigate the effects of dimensionality on RMSD calculations for large biomolecular systems.
• To determine if RMSD loses its discriminatory power with increasing system size.
• To provide recommendations for appropriate RMSD schemes based on protein size.

Main Methods:

• Analysis of dimensionality effects on both weighted and nonweighted RMSD schemes.
• Application of the law of large numbers to explain the emergence of the
• curse of dimensionality
• in RMSD.
• Examination of conformational distributions as a function of system size.

Main Results:

• Dimensionality effects were observed for both weighted and nonweighted RMSD.
• Increasing system size leads to more similar conformational distributions, impacting RMSD.
• The
• curse of dimensionality
• emerges from the law of large numbers.

Conclusions:

• RMSD analysis can be significantly affected by dimensionality in large biomolecular systems.
• Weighted RMSD is recommended for small proteins (<200 residues).
• Nonweighted RMSD is recommended for larger proteins when analyzing molecular dynamics trajectories.