Abstract
Biomolecular function is based on a complex hierarchy of molecular motions. While biophysical methods can reveal details of specific motions, a concept for the comprehensive description of molecular dynamics over a wide range of correlation times has been unattainable. Here, we report an approach to construct the dynamic landscape of biomolecules, which describes the aggregate influence of multiple motions acting on various timescales and on multiple positions in the molecule. To this end, we use 13C NMR relaxation and molecular dynamics simulation data for the characterization of fully hydrated palmitoyl-oleoyl-phosphatidylcholine bilayers. We combine dynamics detector methodology with a new frame analysis of motion that yields site-specific amplitudes of motion, separated both by type and timescale of motion. In this study, we show that this separation allows the detailed description of the dynamic landscape, which yields vast differences in motional amplitudes and correlation times depending on molecular position.
Highlights
Biomolecular function is based on a complex hierarchy of molecular motions
|S| does not provide timescale resolution, whereas Nuclear magnetic resonance (NMR) relaxation rate constants are proportional to ð1 À S2Þ5–8 and are selective for motions having correlation times matched to the eigenfrequencies (ω) of the spin system; these frequencies can be varied by choice of the experiment
This is best described by a dynamic landscape in which the crucial parameters are the correlation times of motion, their distribution widths, and the motional amplitude, where multiple motions yield a product of distributions
Summary
Biomolecular function is based on a complex hierarchy of molecular motions. While biophysical methods can reveal details of specific motions, a concept for the comprehensive description of molecular dynamics over a wide range of correlation times has been unattainable. |S| does not provide timescale resolution, whereas NMR relaxation rate constants are proportional to ð1 À S2Þ5–8 and are selective for motions having correlation times (τc) matched to the eigenfrequencies (ω) of the spin system (ωτc % 1); these frequencies can be varied by choice of the experiment (strictly speaking jSj2 obtained from residual couplings may not exactly equal S2, which determines relaxation behavior, unless an axis of symmetry for the motion exists) This timescale selectivity helps in separating motions, but for complex systems, a complete parameterization is rarely possible, and parameterization using simplified models often creates bias[9]. Lipid molecules are characterized by a highly dynamic structural polymorphism resulting in a well-balanced equilibrium of order and disorder[14] This is best described by a dynamic landscape in which the crucial parameters are the correlation times of motion, their distribution widths, and the motional amplitude, where multiple motions yield a product of distributions. The method is based on dynamic detectors[9,23,24], which describe the timescale-specific generalized amplitude of motion of the C–H bonds of the POPC molecule
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