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Research Topics

Detectors The "detector" method of analyzing dynamics has been recently developed, as a means of reducing bias introduced by the analysis of NMR relaxation data using explicit models. Detectors are being further developed also as a means of analyzing  molecular dynamics simulation. This includes comparison of dynamic behavior between experiment and simulation and correlation analysis between different sites of a protein, in order to connect local and overall motion.
Figure: MD-derived detector responses for
HET-s(218-289) fibrils near 1 ns

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Dynamic model development Detectors provide characterization of dynamics without introducing bias via incorrect model choice. However, using the correct model yields a better understanding of the dynamics.

Protein dynamics in structured regions (α-helices, β-sheets, β-barrels, etc.) should exhibit specific dynamic behavior. Multiple correlation times result from a superposition of local- and mid-range dynamics, which yield a well-defined distribution of motion. We use molecular dynamics simulation and NMR experiments over multiple temperatures to develop distributions of motion and test their robustness.
Figure: Correlation of motion as a function of correlation time. Correlation length increases with correlation time

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Membrane dynamics We apply detectors methodology and models of correlation time distributions to study the dynamics of membrane proteins and the membranes themselves. Detectors are well-suited for comparing dynamics between different samples (e.g. receptors with and without bound ligand), or dynamics at different temperatures (simple models introduce biasing that hinders comparison). Dynamics of the membranes themselves are also studied, where complex motion is separated into its components using simulation and comparison to experiment.
Figure: Amplitude of motion for different correlation time windows of POPC

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Unifying dynamics Many experimental and simulated methods that characterize dynamics are sensitive to the correlation time of motion (i.e. rates of motion). These various methods may utilize different models of motion, so that dynamics analysis yields parameters that are not easily compared. Using detectors, we seek to develop parameters that are comparable between different methods. Using FRET, NMR, MD simulation, and dielectric spectroscopy we see to characterize dynamics over broader ranges of correlation times and length scales.
Figure: Correlation time and correlation length for various methods

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