Microscopic dynamics of proteins: from energy

Published on 2016-05-24 09:09 CEST

Speaker: Dr. David De Sancho (CIC nanoGUNE)

Date & location: Friday 3rd June 2016, 12:30 (CEST). SALA DE CONFERENCIAS, EDIFICIO I+D+i,


Atomistic molecular dynamics (MD) simulations provide a uniquely detailed tool for understanding the dynamics of proteins, the workhorses of living organisms. Analyzing the results from these simulations is however an overwhelming task, as it involves making sense of gigabytes of data consisting of the coordinates of the protein and the surrounding solvent for the many snapshots in time. To help us solve this “big data” problem Markov state models have recently emerged as the method of choice for the analysis of MD simulations. They are able to provide information of the slow, and usually most relevant, transitions of the system (e.g. folding), but without loosing the resolution on the microscopic dynamics. One of their advantages is their fine-grained resolution, which allows for exquisite comparison of the simulation results with experiment.

In my talk I will introduce this approach using a very small peptide as example. Studying this system we have been able to calculate the rate of the most fundamental process in protein folding, helix nucleation (1). Then we will gradually move up in complexity to show how these approaches can help us solve problems posed by experimentalists in the field protein folding, like the molecular origin of “internal friction” in proteins (2,3). Finally I will present applications of this type of approaches to enzyme engineering in systems of industrial interest (4,5) References

  1. 1. De Sancho, D. & Best, R. B. What Is the Time Scale for α-Helix Nucleation? J. Am. Chem. Soc. 133, 6809–6816 (2011).
  2. 2. Zheng, W., De Sancho, D., Hoppe, T. & Best, R. B. Dependence of Internal Friction on Folding Mechanism. J. Am. Chem. Soc. 137, 3283–3290 (2015).
  3. 3. De Sancho, D., Sirur, A. & Best, R. B. Molecular origins of internal friction effects on protein-folding rates. Nat Commun 5, 4307 (2014).
  4. 4. Kubas, A., De Sancho, D., Best, R. B. & Blumberger, J. Aerobic Damage to [FeFe]-Hydrogenases: Activation Barriers for the Chemical Attachment of O2. Angew. Chem. 126, 4165–4168 (2014).
  5. 5. De Sancho, D., Kubas, A., Wang, P.-H., Blumberger, J. & Best, R. B. Identification of Mutational Hot Spots for Substrate Diffusion: Application to Myoglobin. J. Chem. Theory Comput. 11, 1919–1927 (2015).
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