Hokkaido University · Biochemistry, Genetics and Molecular Biology
Professor Tamiki Komatsuzaki's research lab specializes in theoretical and computational biophysics, focusing on the dynamical behavior of complex molecular systems such as proteins and small clusters. The lab develops advanced methods to extract free energy landscapes, state space networks, and reaction pathways from single-molecule time series, emphasizing multiscale analysis and the identification of hidden conformational states. Key interests include the role of dynamical invariance, transition state dynamics, and the interplay between structure, energy, and kinetics in biomolecular systems.
Figures are computed from collected data and may differ slightly.
Conformational dynamics of proteins can be interpreted as itinerant motions as the protein traverses from one state to another on a complex network in conformational space or, more generally, in state space. Here we present a scheme to extract a multiscale state space network (SSN) from a single-molecule time series. Analysis by this method enables us to lift degeneracy--different physical states having the same value for a measured observable--as much as possible. A state or node in the network
We scrutinize the saddle crossings of a simple cluster of six atoms to show (a) that it is possible to choose a coordinate system in which the transmission coefficient for the classical reaction path is unity at all energies up to a moderately high energy, above which the transition state is chaotic; (b) that at energies just more than sufficient to allow passage across the saddle, all or almost all the degrees of freedom of the system are essentially regular in the region of the transition stat
How a reacting system climbs through a transition state during the course of a reaction has been an intriguing subject for decades. Here we present and quantify a technique to identify and characterize local invariances about the transition state of an N-particle Hamiltonian system, using Lie canonical perturbation theory combined with microcanonical molecular dynamics simulation. We show that at least three distinct energy regimes of dynamical behavior occur in the region of the transition stat
A scheme for extracting an effective free energy landscape from single-molecule time series is presented. This procedure uniquely identifies a non-Gaussian distribution of the observable associated with each local equilibrium state (LES). Both the number of LESs and the shape of the non-Gaussian distributions depend on the time scale of observation. By assessing how often the system visits and resides in a chosen LES and escapes from one LES to another (with checking whether the local detailed b
A scheme to approximate the multidimensional potential energy landscape in terms of a minimal number of degrees of freedom is proposed using a linear transformation of the original atomic Cartesian coordinates. For one particular off-lattice model protein the inherent frustration can only be reproduced satisfactorily when a relatively large number of coordinates are employed. However, when this frustration is removed in a Go-type model, the number of coordinates required is significantly lower,
We use Raman microscopic images with high spatial and spectral resolution to investigate differences between human follicular thyroid (Nthy-ori 3-1) and follicular thyroid carcinoma (FTC-133) cells, a well-differentiated thyroid cancer. Through comparison to classification of single-cell Raman spectra, the importance of subcellular information in the Raman images is emphasized. Subcellular information is extracted through a coarse-graining of the spectra at high spatial resolution (∼1.7 μm<sup>2
Reaction trajectories reveal regular behavior in the reactive degree of freedom and unit transmission coefficients as the system crosses the saddle region separating reactants and products. The regularity persists up to moderately high energies, even when all other degrees of freedom are chaotic. This behavior is apparent in a representation obtained by transformation with Lie canonical perturbation theory. The dividing surface in this representation is analogous to the conventional dividing sur
A method to scrutinize ‘‘regularity’’ of barrier recrossing dynamics of chemical reactions in the vicinity of the transition state is developed by using Lie canonical perturbation theory (LCPT). As an example, the recrossing dynamics of a four-degrees of freedom Hamiltonian regarded as a model of proton transfer reaction of malonaldehyde is investigated. It is shown that the second order LCPT is essential to describe frequent saddle recrossings whose total number of crossings is greater than thr
We recently developed a new method to extract a many-body phase-space dividing surface, across which the transmission coefficient for the classical reaction path is unity. The example of isomerization of a 6-atom Lennard-Jones cluster showed that the action associated with the reaction coordinate is an approximate invariant of motion through the saddle regions, even at moderately high energies, at which most or all the other modes are chaotic [J. Chem. Phys. 105, 10838 (1999); Phys. Chem. Chem.
Histopathology requires the expertise of specialists to diagnose morphological features of cells and tissues. Raman imaging can provide additional biochemical information to benefit histological disease diagnosis. Using a dietary model of nonalcoholic fatty liver disease in rats, we combine Raman imaging with machine learning and information theory to evaluate cellular-level information in liver tissue samples. After increasing signal-to-noise ratio in the Raman images through superpixel segment
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