Associate Professor of Chemistry
Ph.D., University of Genoa
M.S., University of Genoa
Member of: Institute of Molecular Biology, Institute of Theoretical Science, Materials Science Institute
phone: 541-346-2877
Research Interests
Modeling Protein Motions with Simulations and Theory
A research focus in the Guenza group is to develop computational and analytical tools for describing protein dynamics across many timescales to relate protein motion to biological function. The development of a general understanding of the relation between protein dynamics and function can provide important insights into many of their physical and biological properties. For example, kinetic processes involving protein-protein or protein-ligand interactions can depend on local conformational fluctuations. Protein stability is dominated by the thermodynamic entropy, which in turn is a function of the density of conformational states explored by the molecule and increases with increasing flexibility. Other subtle ways in which protein flexibility and dynamics are related to their biological activity include allosteric mechanisms of activation, where protein motion leads to structural fluctuations of coupled domains, which can transmit information between distant sites inside the protein. Such fluctuations can be responsible for promoting reactivity by bringing within close proximity catalytic sites that are otherwise distant. Moreover, large cooperative motions are important for protein reactivity, because they can allow substrates to access internal regions of the protein that are sterically hindered.
Because the dynamics of proteins occur over an extended range of timescales, from local bond librational motions (ps), bond re-orientation (ns), to the global tumbling and cooperative inter-domain motions (tens of nanoseconds and longer), and because of the many degrees of freedom available to the molecule, understanding the general principles of protein dynamics is a complicated problem.
Guenza’s group is developing theoretical first-principle approaches to predict protein dynamics from their structure and to understand their relation to protein function. We perform Molecular Dynamic simulations of the protein in solution and extend the timescale of motion using a Langevin approach.
| An example of molecular dynamics simulation of the signal transduction protein CheY in water solvent. Only the backbone of the protein is displayed in the movie. |
Our goal is to develop approaches that are general and free of adjustable parameters. To test their validity we directly compare theoretical predictions with experimental data. For example, in Figure 1 we show theoretical correlation times as a function of the protein primary sequence against those measured by NMR experiments of 1H-15N nuclear Overhauser effect, spin-lattice relaxation, and spin-spin relaxation. A peak in the spin-lattice relaxation (T1 plot) indicates that the specific residue is more mobile than the adjacent residues in the primary sequence and a faster relaxation Proteins investigated so far include the bacterial signal transduction protein CheY, the molecular motor kinesin, and the protein calmodulin.
Theoretical prediction (dark lines) of NMR T1, T2 and NOE relaxation and comparison with experimental data (grey line) from Deutschman and Dahlquist. Figure from Caballero-Manrique et al. Biophys. J. 93 (12) 4128-4140 (2007).
Selected Publications
M. Zamponi, A Wischnewski, M. Monkembusch, L. Willner, D. Richter, P. Falus, B. Farago, M.G.Guenza "Cooperative dynamics in homopolymer melts: a comparison with Neutron Spin Echo experiments" J. Phys. Chem. B 112, 16220-16229 (2008).
P. Debnath, M. G. Guenza "Cooperative dynamics in polymer melts from the unentangled to the entangled regime" Phil. Mag. 88, 33-35 (2008).
M. Guenza "Theoretical models for bridging timescales in polymer dynamics" J. Phys.: Condens. Matter 20, 033101-0331024 (2008).
E. J. Sambriski and M. G. Guenza "Theoretical coarse-graining approach to bridge length scales in diblock copolymer liquids" Phys. Rev. E 76, 051801-051813 (2007). Note: This paper has been selected for the November 12, 2007 issue of Virtual Journal of Nanoscale Science & Technology and for the November 15, 2007 issue of Virtual Journal of Biological Physics Research.
E. Caballero-Manrique, J. K. Bray, W. A. Deutschman, F. W. Dahlquist and M. G. Guenza “A theory of protein dynamics to predict NMR relaxation” Biophysical Journal 93 (12) 4128-4140 (2007).
E. J. Sambriski, G. Yatsenko, M. A. Nemirovskaya, M. Guenza "Bridging length scales in polymer melt relaxation for macromolecules with specific local structures" J. Phys.: Condens. Matter 19, 205115-205126 (2007).
M. C. Fink, K. V. Adair, M. G. Guenza, A. H. Marcus "Translational Diffusion of Fluorescent Proteins by Molecular Fourier Imaging Correlation Spectroscopy", Biophys. J. 91, 3482 (2006).
E. J. Sambriski, G. Yatsenko, M. A. Nemirovskaya, M. Guenza "Analytical coarse-grained description for polymer melts" J. Chem. Phys. 125, 234902 (2006). Note: This paper has been selected for the December 15, 2006 issue of Virtual Journal of Biological Physics Research.
pdf format: G. Yatsenko, E.J. Sambriski, M.A. Nemirovskaya, M. Guenza "Analytical Soft-Core Potentials for Macromolecular Fluids and Mixtures" Phys. Rev. Lett. 93 257803 (2004) Note: this paper has been selected for the December 17, 2004 issue of Virtual Journal of Nanoscience & Technology and for the December 15, 2004 issue of Virtual Journal of Biological Physics Research.
M. Guenza, "Many-Chain Correlated Dynamics in Polymer Fluids," Journal of Chemical Physics, 110, 7574 (1999).
297 Klamath Hall Hall