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How Molecular Size Impacts RMSD Applications in Molecular Dynamics Simulations

Journal of Chemical Theory and Computation · 2017 · Vol. 13(4) · pp. 1518–1524
Karen SargsyanCédric GrauffelCarmay Lim

Abstract

The root-mean-square deviation (RMSD) is a similarity measure widely used in analysis of macromolecular structures and dynamics. As increasingly larger macromolecular systems are being studied, dimensionality effects such as the "curse of dimensionality" (a diminishing ability to discriminate pairwise differences between conformations with increasing system size) may exist and significantly impact RMSD-based analyses. For such large bimolecular systems, whether the RMSD or other alternative similarity measures might suffer from this "curse" and lose the ability to discriminate different macromolecular structures had not been explicitly addressed. Here, we show such dimensionality effects for both weighted and nonweighted RMSD schemes. We also provide a mechanism for the emergence of the "curse of dimensionality" for RMSD from the law of large numbers by showing that the conformational distributions from which RMSDs are calculated become increasingly similar as the system size increases. Our findings suggest the use of weighted RMSD schemes for small proteins (less than 200 residues) and nonweighted RMSD for larger proteins when analyzing molecular dynamics trajectories.

Protein Structure and DynamicsEnzyme Structure and FunctionRNA and protein synthesis mechanismsCurse of dimensionalityMolecular dynamicsPairwise comparisonSimilarity (geometry)MacromoleculeStatistical physicsBiological systemComputer scienceChemistryComputational chemistry

MeSH terms

Molecular WeightProtein ConformationProteinsMacromolecular SubstancesMolecular Dynamics Simulation

Funding

  • National Science Council
  • Academia Sinica
Citations
628
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