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Correlating Biomolecular Experimental Measurements with Computational Simulations
Published: March 21, 2011
Posted: April 06, 2011

Understanding the structural changes a biomolecule undergoes during processing is important in the design of, for example, new routes to convert biomass to biofuels. However, when studying these processes it often is difficult to correlate kinetic experiments with computer simulations. Both the experiments and the simulations provide a time-ordered understanding of the biological process at hand, but the results are often hard to compare. Research by an international consortium that includes Jeremy Smith of Oak Ridge National Laboratory has developed a new mathematical method, “Dynamical Fingerprints,” that allows researchers to visualize the essential kinetic features of an experiment and compare these features directly to computational simulation results. Structural changes present in the simulation can be assigned to experimentally observed processes. The new method enables enhanced interpretation of experiments ranging from neutron scattering to fluorescence correlation spectroscopy and Förster resonance energy transfer efficiency. Combining simulations and experiments will enable progress in areas such as biofuel production and design of advanced materials, which require a clear understanding of how molecules move and interact. The research was supported by DOE SciDAC funding and was just published online in the Proceedings of the National Academy of Sciences (USA).

Reference: Noe, F., S. Doose, I. Daidone, M. Löllmann, M. Sauer, J. Chodera and J. Smith. 2011. “Dynamical Fingerprints for Probing Individual Relaxation Processes in Biomolecular Dynamics with Simulations and Kinetic Experiment,” Proceedings of the National Academy of Sciences (USA), Early Edition March 2, 2011 (DOI: 10.1073/pnas.1004646108).

Contact: Christine Chalk, SC-21.1, (301) 903-5152, Susan Gregurick, SC-23.2, (301) 903-7672
Topic Areas:

  • Research Area: Sustainable Biofuels and Bioproducts
  • Research Area: Computational Biology, Bioinformatics, Modeling
  • Research Area: Structural Biology, Biomolecular Characterization and Imaging
  • Cross-Cutting: Scientific Computing and SciDAC

Division: SC-33.2 Biological Systems Science Division, BER

 

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