The University of Tokyo · Biochemistry, Genetics and Molecular Biology
Professor Takefumi Yamashita's research lab specializes in computational biophysics and molecular simulation, focusing on understanding complex biological processes at the atomic level. The lab employs advanced methods such as molecular dynamics simulations, multistate empirical valence bond (MS-EVB) modeling, and ab initio calculations to study proton transport, electron transfer in respiratory enzymes like cytochrome c oxidase, and the behavior of hydrated protons at biomembrane interfaces. Their work also extends to rational drug design and antibody-antigen interactions, leveraging high-performance computing to predict binding free energies with high accuracy. The lab emphasizes the development and application of multiscale simulation techniques to bridge electronic structure calculations with macroscopic biological phenomena.
Figures are computed from collected data and may differ slightly.
Cytochrome c oxidase (CcO), known as complex IV of the electron transport chain, plays several important roles in aerobic cellular respiration. Electrons transferred from cytochrome c to CcO's catalytic site reduce molecular oxygen and produce a water molecule. These electron transfers also drive active proton pumping from the matrix (N-side) to intermembrane region (P-side) in mitochondria; the resultant proton gradient activates ATP synthase to produce ATP from ADP. Although the existence of t
It is a computationally demanding task to explicitly simulate the electronic degrees of freedom in a system to observe the chemical transformations of interest, while at the same time sampling the time and length scales required to converge statistical properties and thus reduce artifacts due to initial conditions, finite-size effects, and limited sampling. One solution that significantly reduces the computational expense consists of molecular models in which effective interactions between parti
The behavior of the hydrated excess proton near different lipid membranes is studied with the third generation of the multistate empirical valence bond (MS-EVB3) model [Wu, Y. J.; Chen, H. N.; Wang, F.; Paesani, F.; Voth, G. A. J. Phys. Chem. B 2008, 112, 467]. Dioleoylphosphatidylcholine (DOPC), dioleoylphosphatidylethanolamine (DOPE), and dioleoylphosphatidylglycerol (DOPG) are selected as example lipids. In spite of the differences of the head groups, the molecular dynamics simulations show t
Because antibodies have become an important therapeutic tool, rational antibody design is a challenging issue involving various science and technology fields. From the computational aspect, many types of design-assist methods have been developed, but their accuracy is not fully satisfactory. Because of recent advancements in computational power, molecular dynamics (MD) simulation has become a helpful tool to trace the motion of proteins and to characterize their properties. Thus, MD simulation h
The infrared spectrum of phenol-water cationic cluster, [PhOH.H2O]+, taken by Sawamura et al. [J. Phys. Chem. 100, 8131 (1996)] is puzzling in that the peak due to the stretching mode of the phenolic OH (3657 cm-1 for a neutral monomer and 3524 cm-1 for PhOH.H2O) seemingly disappears and instead an extremely broad tail extending down to 2900 cm-1 is observed. The present authors theoretically ascribe this anomalous spectrum to an inhomogeneous broadening of the OH stretching peak caused by the h
In this study, we modified Lennard-Jones (LJ) parameters and point-charge parameters of the DREIDING force field (the modified force-field model is named DREIDING-UT). While the original LJ parameters of DREIDING were derived through an analytical formula to reproduce the potential depths and the equilibrium lengths of the Buckingham potentials of DREIDING/X6, the modified LJ parameters were derived through the least square fitting of the Buckingham potentials. Because the Gasteiger-Marsili (GM)
In this study, we propose a supercomputer-assisted drug design approach involving all-atom molecular dynamics (MD)-based binding free energy prediction after the traditional design/selection step. Because this prediction is more accurate than the empirical binding affinity scoring of the traditional approach, the compounds selected by the MD-based prediction should be better drug candidates. In this study, we discuss the applicability of the new approach using two examples. Although the MD-based
A set of analytical potential energy surfaces (PESs) for six singlet excited states of NOCl are constructed based on multireference configuration interaction calculations. The total absorption cross section at the energy range of 2-7 eV is calculated by quantum dynamics calculations with the present PESs and transition dipole moments. The calculated absorption spectrum agrees well with the experiment. It is also found that the A band with the absorption maximum at 6.3 eV is attributed to the tra
As the evolution of computational technology has now enabled long molecular dynamics (MD) simulation, the evaluation of many physical properties shows improved convergence. Therefore, we can examine the detailed conditions of MD simulations and perform quantitative MD analyses. In this study, we address the quantitative and accuracy aspects of MD simulations using two example systems. First, it is found that several conditions of the MD simulations influence the area/lipid of the lipid bilayer.
The computational structure-based drug design (SBDD) mainly aims at generating or discovering new chemical compounds with sufficiently large binding free energy. In any de novo drug design methods and virtual screening methods, drug candidates are selected by approximately evaluating the binding free energy (or the binding affinity). This approximate binding free energy, usually called "empirical score," is critical to the success of the SBDD. The purpose of this work is to yield physical insigh
We demonstrate that persistent homology (PH) analysis, a new technique of the computational topology, combined with molecular dynamics simulations, can successfully characterize the complex liquid structure. First, we applied PH analysis to an antigen-antibody complex solution, showing that the interfacial water can be automatically detected. Second, we used PH analysis to characterize the structure of a mixture consisting of epoxy resin and amine curing agent, finding that amine nitrogen rings
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