Conformational dynamics of biomolecules: Reconciling simulation and experimental data

• Applicant: Professor Dr. Frank Noé
• Subject Area: Biophysics
• Term: from 2008 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 104734058

This line of research develops theory and methodology for reconciling biophysical experiments and simulations, with the aim at bridging between these methods, obtaining detailed models of the behavior of biomolecules that include both structures and kinetics, and thereby enhance our understanding of biophysics.In the previous funding period we have focused at reconciling molecular dynamics simulation with kinetics ensemble experiments via Markov state models and new theory. The results have been published and applied to various biomolecular processes.In the forthcoming funding period we plan to develop methods to estimate complex kinetic models directly from single-molecule experimental data. In its spirit, our approach is related to Hidden Markov modeling but goes much beyond that and resolves some of the fundamental limitations of Hidden Markov modeling for the context of biophysical systems. The result of this approach will be a model of the conformational substates present in the data, their interconversion rates, and the distribution of values in the molecular observable(s) each conformation is associated with. In contrast to Hidden Markov models, neither the form of these distributions nor the number of hidden states must be pre-defined. The method planned is applicable to all kinds of single-molecule data, including force probe experiments and single-molecule fluorescence experiments. In addition, it will also enhance the construction of Markov state models from simulated data. We plan to apply the method to optical tweezer data and to extensive molecule dynamics simulation data. In order to illustrate the generality of the method, various different molecular processes will be used as application examples. The methods will be implemented in our publicly available EMMA software.

• DFG Programme: Research Grants