Computer Science Department
School of Computer Science, Carnegie Mellon University


Classifying Protein Structural Dynamics via
Residual Dipolar Couplings

Ruben Valas*, Christopher James Langmead

December 2004


Keywords: Computational biology, structural biology, Nuclear Magnetic Resonance, NMR, Residual Dipolar Couplings, RDCs, dynamics

Recent advances in Nuclear Magnetic Resonance (NMR) spectroscopy present new opportunities for investigating the conformational dynamics of proteins in solution. In particular, tensors for motions relevant to biological function can be obtained via experimental measurement of residual dipolar couplings (RDCs) between nuclei. These motion tensors have been used by others to characterize the magnitude and anisotropy of the dynamics of individual bond vectors. Here, we extend these results and demonstrate that RDCs can also be used to characterize the global nature of the protein s motion (e.g., hinge motions, shear motions, etc.). In particular, we introduce the first method for classifying protein motions from RDC data. Our classifier consists of a discriminative model trained on 2,454 different molecular dynamics trajectories spanning seven categories of motion. The classifier achieves precision and recall accuracy of 90.6% and 90.9%, respectively, using 10-fold cross-validation over these seven categories.

17 pages

*Department of Biological Sciences, Carnegie Mellon University

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