Seminar2007 – 2011

Horse liver alcohol dehydrogenase is a homodimer, the protomer having a coenzyme-binding domain and a catalytic domain. Using all available X-ray structures and molecular dynamics simulations, the mechanism of NAD⁺-induced domain closure was investigated.[1] When the well-known loop at the domain interface is in the "open" conformation the domains are unable to close. However, when the loop was modelled to its "closed" conformation, the NAD⁺-induced domain closure from the open structure could be simulated with remarkable accuracy. Further simulations and a careful analysis of X-ray structures suggest that the loop prevents domain closure in the absence of NAD⁺, and a cooperative mechanism operates between the subunits for domain closure. This cooperative mechanism explains the role of the "switch loop" as a block to closure, as in the absence of NAD⁺ it would prevent the occurrence of an unliganded closed subunit when the other subunit closes upon NAD⁺.
The switch loop comprises a rare ProPro motif suggesting a possible role in creating a rigid arm for communicating the presence of NAD⁺ to the region that blocks domain closure. This was confirmed using a linear inverse-kinematics technique developed for loop modelling.[2]

References
[1]. S. Hayward and A. Kitao, "Molecular dynamics simulations of NAD⁺-induced domain closure in horse liver alcohol dehydrogenase", Biophysical Journal, 91: 1823-1831, 2006.
[2]. S. Hayward and A. Kitao, "Effect of end constraints on protein loop kinematics", Biophysical Journal, 98(9), 1976-1985, 2010.

Biological environments provide complex physiochemical environments due to heterogeneity and crowding. This presents challenges for fully understanding the functionally-relevant structure and dynamics of biological macromolecules in vivo from both experimental and computational studies. In this talk, novel computational approaches are presented that allow the effects of cellular environments to be included efficiently in molecular dynamics simulations. A particular focus is on multiscale methodologies including mean-field formalisms and a new transferable coarse-grained model. Such simulations were applied to the study of the conformational dynamics of membrane-interacting peptides and peptides in crowded protein environments. More specifically, conformational sampling of viral membrane peptides and the membrane-spanning peptide phospholamban are described and discussed in the context of experimental data. Furthermore, the computational sampling of melittin in crowded cellular environments is discussed.

Due to the potential applications in semiconductor industries, the surface chemical reactions particularly on semiconductor surface have gained enormous popularity and the interest is still growing.[1]　With the help of traditional organic and organometallic chemistry, a wide variety of new chemically modified silicon surfaces can be synthesized to provide fine tailoring of surface characteristics for a broad range of applications. To gain the control needed to fabricate an organic function into existing semiconductor technologies and ultimately to make new molecule-scale devices, a detailed understanding of the adsorbate surface as well as interfacial chemical reactions and their products at the atomic/molecular level is critical. To accomplish this, theoretical investigations need to play a significant role in the advance of this field. This talk begins with the theoretical methodologies adapted for surface studies and then proceeds to a consideration of the unique features of clean silicon surfaces. Then, the main focus is directed to the characteristics of surface structures and reaction mechanisms that have been theoretically accumulated for the last several years. The key understandings of surface cyloadditions, nuleophilc additions, and surface thermal decompositions shall be discussed.
[1] a) Choi, C. H.; Gordon, M. S. “Computational Materials Chemistry: Methods and Applications”, L.A. Curtiss and M.S. Gordon, Eds., Kluwer Academic Publishers, Ch. 4, pp. 125-190, 2004. “Theoretical Studies of Silicon Surface Reactions with Main Group Absorbates” b) Journal of Physical Chemistry C (2010), 114(33), 14187-14192.

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The free-energy analysis is essential to understand and control a chemical process in condensed phase. The current status of theoretical/computation chemistry is, however, that the free energy remains a most difficult quantity to compute. For the fast computation and molecular understanding of the free energy, a new theory of solutions is introduced and is combined with molecular simulation. This theory is called the method of energy representation, and constructs the solvation free energy as a functional of distribution functions of the solute-solvent pair interaction energy. The method of energy representation greatly expands the scope of solution theory and is amenable to such frontline topics of physical chemistry and biophysics as ionic liquid, supercritical fluid, flexible molecules with intramolecular degrees of freedom, inhomogeneous system, and quantum-mechanical/molecular-mechanical (QM/MM) system. We present a brief introduction to the distribution-function theory of solutions, and describe the method of energy representation with its performance. As an application to inhomogeneous system involving flexible species, the molecular binding into micelle and lipid membrane is analyzed by treating micelle and membrane as a mixed solvent system consisting of water and amphiphilic molecule. The free energy of protein hydration is also evaluated with explicit solvent, and the roles of excluded volume and hydrogen bonding are quantitatively discussed.

Over the last three decades, considerable efforts have been made to generalize and enhance the computational methodologies and techniques to model and simulate macromolecules of biological interest. In particular, molecular dynamics simulations have provided deeper insights into not only how they interact with the surrounding environment at the atomic level, but also the microscopic driving forces of their functions, especially when the simulations are combined with sophisticated free energy calculations. In this seminar, I would like to present the challenges of current molecular modeling and simulations in terms of their accessibility to general users including experimentalists, issues with the system size and time scale, and finally accuracy. Several case studies will be presented with some preliminary results in my research group to go possibly beyond the challenges.

The ribosome is a stochastic molecular machine responsible for protein synthesis, a process central to all organisms. During the decoding step of protein synthesis (tRNA selection), the ribosome must discriminate between correct and incorrect tRNAs. The process by which tRNAs move from the partially bound (‘A/T state’) to fully bound (‘A/A’) state is rate-limiting in the case of correct (cognate) tRNAs. This large conformational change (~70 Angstrom tRNA movement) is known as accommodation and is the subject of our study. We use several different large-scale molecular simulation techniques to study the process of accommodation. Explicit solvent targeted molecular dynamics simulations allow us to define the accommodation corridor for tRNA on the large subunit of the ribosome. All-atom structure-based simulations using a Go-like potential allow us extend our approximate timescale to hundreds of milliseconds, revealing stochastic reversible excursions of the tRNA from the A/T state towards the A/A state and back to the A/T state, consistent with similar events observed in single molecule FRET studies. These structure-based simulations are cross-validated against equilibrium explicit solvent simulations (3.2 million atoms) with one microsecond of total sampling. Reasonable agreement is obtained between structure-based simulation, explicit solvent simulation, and crystalographic B-factors. The Encanto and RoadRunner supercomputers were used.

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Principal component analysis (PCA) of molecular dynamics (MD) simulations is a powerful tool for investigating the collective motions of biomolecules. Due to the roughness of a protein’s energy landscape, the large-amplitude collective modes resulting from PCA are typically anharmonic. Here we decompose the PCA space to sub-PCA spaces by using the expectation-maximization (EM) algorithm. Each of these sub-PCA spaces represents a conformational state and the distribution of each state is described by a multivariate Gaussian distribution. The dynamics of the protein on the PCA space is then described as a diffusion/jumping process between different conformational states. We have applied this procedure to the MD trajectories of two proteins: crambin (1 μs simulation) and profilin (440 ns simulation). The number of states predicted initially increased with the dimensionality of PCA modes, but reached a plateau for dimensions greater than five. Furthermore, conformations can be divided into states based on the Gaussian mixture models and the transition network between states can be determined. The main advantage of this EM procedure is that it is significantly fast. However the method does not guarantee to find the optimal solutions for higher dimensions. This procedure is especially useful to do conformational clustering on the low-dimensional anharmonic "essential space". In order to determine such an "essential space", we have developed a statistical protocol involving estimation of the relaxation time of each individual mode, bootstrap analysis of the independent data based on the relaxation time, and application of a statistical goodness-of-fit test on the data to quantify normality. Using a simple model system of harmonic springs, we demonstrate the application and sensitivity of this technique and its ability to correctly identify the harmonic and anharmonic modes of the system.

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生体分子など複雑な自由エネルギー地形を持つ物質の分子動力学シミュレー ションを素朴におこなうと，自由エネルギー極小状態にトラップされてしまい広い範囲 の構造を探索できない．そこで近年，拡張アンサンブル法と総称される方法がよく用 いられるようになってきた．その１つであるマルチカノニカル法は強力な方法だが体 積を 一定に保つため圧力を指定できないし体積変化をともなう現象を扱うこともできない．またシミュレーションを始める前に重み因子を決定しなければならないが，大きな系では重み因子を決めるのが難しくなる．これらの問題を解決するため２つの方法を最近提案した．第１の問題を解決するためにマルチバーリック・マルチサーマル法を提案した [1-5]．この方法はエネルギー空間上と体積空間上の両方でランダムウォークを実現する．この方法を水中のアラニンジペプチドに適用し，これまでの方法と比較した [6,7]．従来の定温定圧法では自由エネルギーの極小値にとらわれ，多くの構造をサン プル することができなかった．一方，マルチバーリック・マルチサーマル法では自由エネルギーの極小値にとらわれることなく多くの構造をサンプルできた．また，これらの構造の温度，圧力変化を調べ，各構造間の部分モルエンタル ピー差， 部分モル体積差を計算したところ，ラマン散乱の実験結果とよく一致した．部分モルエンタルピー差，部分モル体積差は各構造の存在確率がそれぞれ温度，圧力とともにどのように変化するかを示す重要な物性値である．しかし，分子シミュレーションでこれらの量を計算する方法はこれまでなかった．この手法により生体分子の部分モルエンタルピー差，部分モル体積差を分子シミュレーションで計算することが初めて可能になった．第２の問題を解決するために部分的マルチカノニカル法[8]を提案した．この方法では多くの構造をサンプルするのに必要なポテンシャルエネルギー項についてだけ広くサンプルする．このため重み因子を決定するた めの労力を節約 できるので，より効率的に構造サンプリングができる．この方法を水 中のアラニンジ ペプチドに適用して，カノニカル法およびマルチカノニカル法と比較し たところ，カノニカル法よりもマルチカノニカル法の方が，さらに部分的マルチカノニカ ル法の方がより多くの構造を効率的に探索できることが示された．
[1] H. Okumura and Y. Okamoto: Chem. Phys. Lett. 383 (2004) 391-396.
[2] H. Okumura and Y. Okamoto: Phys. Rev. E 70 (2004) 026702(14pages).
[3] H. Okumura and Y. Okamoto: J. Phys. Soc. Jpn. 73 (2004) 3304-3311.
[4] H. Okumura and Y. Okamoto: Chem. Phys. Lett. 391 (2004) 248-253.
[5] H. Okumura and Y. Okamoto: J. Comput. Chem. 27 (2006) 379-395.
[6] H. Okumura and Y. Okamoto: Bull. Chem. Soc. Jpn. 80 (2007)1114-1123.
[7] H. Okumura and Y. Okamoto: J. Phys. Chem. B 112 (2008),12038-12049.
[8] H. Okumura: J. Chem. Phys. 129 (2008) 124116 (9 pages).

Molecular Dynamic (MD) simulations have been successfully used to study molecular events like structural stability and molecular interaction but many of the molecular mechanism which takes place in the cell are acting on a timescale beyond the capacity of a traditional MD simulation. Such an event is the ligand unbinding from the Nuclear Receptors (NR). The NRs functions as a transcription regulator and can be activated upon ligand binding. Consequently ligand binding and unbinding constitutes a fundamental process in the regulation of genes. Even though both biochemical and structural data of NR are available, the actual mechanism of the ligand binding/unbinding remains elusive. We have performed ligand unbinding studies on NRs with modified the MD methods (1) Random Acceleration MD (RAMD) (2) and Steered MD (SMD) (3) which speed up the timescale. The results show that agonist ligand unbinding can take place from the receptor without causing major conformational changes in the receptor, while antagonist unbinding cannot. Further on ligand selectivity and method sampling were discussed.
Allosteric properties have previously been studied with covariance correlation analysis and normal mode analysis. However, these methods requires long MD simulation trajectory to detect the signal. Recently publication presented the Anisotropic Thermal Diffusion method (4) which increases the signal-noise ratio within the protein and therefore makes it possible to detect an allosteric signal. The method was used to study allosteric properties in the NR Liver X Receptor (LXR) and succeeded to map out a pathway from the AF-2 region and the ligand. The signaling pathway detected is both intra- and intermolecular and is transmitted through amino acids side chains and the backbone. Although promising results were achieved, the method contains some drawbacks which will also be discussed.
1. Carlsson, P., S. Burendahl and L. Nilsson. (2006) Unbinding of retinoic acid from the retinoic acid receptor by random expulsion molecular dynamics. Biophys J 91, 3151-61.

2. Ludemann, S. K., V. Lounnas and R. C. Wade. (2000) How do substrates enter and products exit the buried active site of cytochrome P450cam? 1. Random expulsion molecular dynamics investigation of ligand access channels and mechanisms. Journal of Molecular Biology 303, 797-811.

3. Isralewitz, B., M. Gao and K. Schulten. (2001) Steered molecular dynamics and mechanical functions of proteins. Curr Opin Struct Biol 11, 224-30.

4. Ota, N. and D. A. Agard. (2005) Intramolecular signaling pathways revealed by modeling anisotropic thermal diffusion. J Mol Biol 351, 345-54

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最近の構造あるいは機能バイオインフォマティクス分野の進展により、タンパク質の構造や機能、相互作用について、計算機ベースで新規の仮説を提唱することが可能になってきた。これらの方法を活用し、疾患に潜在的に関与する遺伝子やタンパク質について、各タンパク質がどのような分子機能を発揮し、どのような相手と相互作用し、またどのようなパスウェイに存在するかなどの知識一般を高めることが今後の創薬分野でも有効になると考えられる。我々が開発した、アミノ酸配列からタンパク質立体構造を予測する方法FUGUEの基礎理論と、酵素、膜蛋白質などいくつかの具体的な応用について述べる。

The diffusion of mass and the conductivity of heat take their origin at a molecular scale in the molecular motion and in the interaction between molecules. Molecular dynamics simulation is used to investigate these properties both under equilibrium and out of equilibrium. After a short presentation of these methods and of the transport equations, I will show the results we recently obtained of the transport properties across interfaces in two cases liquid-vapour and zeolite-vapour.

Analytical fitted potential energy surfaces are a valuable tool for study of reaction dynamics and molecular spectroscopy. In full generality the surface depends on 3N-6 independent coordinates, where N is the number of nuclei, and the construction of such surfaces is a problem of high-dimensional approximation already for small systems, say of 5-9 atoms. For the effective construction of such surfaces we have found it essential to enforce strictly the property of invariance of the surface under permutation of like nuclei; we build this property into the basis of fitting functions expressed in internuclear distances. The construction of these permutationally invariant basis functions (and covariant basis functions for properties such as the dipole moment) is a nontrivial task that cannot well be carried out by hand except for the simplest systems. We rely on computational invariant theory and on the MAGMA computer algebra system to construct suitable bases for each possible molecular permutation symmetry group,and have pursued that approach for systems up to 9 and 10 atoms. Illustrative challenging recent applications in the Bowman group at Emory University include photodissociation of acetaldehyde and spectroscopy of malonaldehyde and the water trimer. In the talk I will describe the mathematical background and highlights of new applications. This work is supported by ONR and USDOE.

Membrane proteins are pharmaceutically important therapeutic targets because of their well-recognized contribution to ion transport, intracellular and intercellular signaling pathways, and critical role in cell-cell recognition.Transmembrane (TM) domains of most membrane proteins consist of helices that interact with each other via inter- and intra-helix-helix interactions as well as with nonprotein membrane constituents. In this talk,I will present the computational/theoretical studies of membrane protein folding processes as insertion, folding, tilting, and assembly of transmembrane helices. If time is allowed, I will also talk about our novel RDC restraint potential and its applications, as well as the CHARMM-GUI development project.

マルチカノニカル法はポテンシャルエネルギー空間上のランダムウォークを実現する。これに対し我々は最近, 新しい拡張アンサンブル法 – マルチバーリック・マルチサーマル法 – を提案した。この方法はエネルギー空間上と体積空間上の両方でランダムウォークを実現する。このため広い範囲の温度と圧力における定温定圧アンサンブルを得ることができる。本研究ではマルチバーリック・マルチサーマル分子動力学法を水中のアラニンジペプチドに応用し,その構造の温度・圧力依存性を調べた[1]。ペプチドの力場にはAmber parm96とAmber parm99を用いた。各状態の存在確率比の温度・圧力依存性をもとに各状態の部分モルエンタルピー差と部分モル体積差を計算した。さらにこれらの結果の力場依存性について議論する。
[1] H. Okumura and Y. Okamoto: Bull. Chem. Soc. Jpn. 80 (2007)1114-1123.

We present a novel approach to the calculation of coulomb and exchange contributions to the total electronic energy in Hartree-Fock and Density Functional Theory.The key numerical procedure is the Cholesky decomposition that previously has been shown to efficiently remove linear dependence in the two-electron integral matrix.The basic idea is to decompose specific matrices that enter the energy expression.In this way we obtain an auxiliary basis (cholesky basis) that is much smaller than currently used in the resolution of identity or density fitting approaches.

Activity coefficients (chemical potential) of urea solutions are calculated to explore the mechanism of its solution properties which form the basis for its well known use as a strong protein denaturant. We perform free energy simulations of urea solutions in different urea concentrations using two urea models (OPLS and KBFF models)to calculate and decompose the activity coefficients. For the case of urea, we clarify the concept of the ideal solution in different concentration scales and standard states and its effect on our subsequent analysis.The analytical form of activity coefficients depends on the concentration units and standard states.For both models studied urea displays a weak concentration dependence for excess chemical potential.However, for the OPLS force field model this results from contributions which are independent of concentration to the van der Waals and electrostatic components whereas for the KBFF model those components are nontrivial but oppose each other.The strong ideality of urea solutions in some concentration scales,implying a lack of water perturbation, is discussed in terms of recent data and ideas on the mechanism of urea denaturation of proteins. [1,2]
[1] H. Kokubo and B. M. Pettitt,Preferential Solvation in Urea Solutions at Different Concentrations: Properties from Simulation Studies,J. Phys. Chem. B 111, 5233 -5242 (2007).
[2] H. Kokubo, J. Roesgen, D. W. Bolen, and B. M. Pettitt,Molecular Basis of the Apparent Near Ideality of Urea Solutions,Biophy. J. (2007) in press.

Polytheonamide B は八丈島産海綿 Theonella swinhoei から単離・精製された強力な細胞毒性を持つ４８残基のポリペプチドである。このペプチドは通常のアミノ酸以外にメチル化、ヒドロキシ化されたアミノ酸７種類を有し、さらにD, L-アミノ酸が交互に配列し、細胞膜中でβ6.3-ヘリックス構造をとることでカチオン選択的チャンネルを形成する。我々のグループは、Polytheonamide B の原子レベルでのチャンネルメカニズムの解明を目指し、基準振動解析に基づき、Polytheonamide B の真空中における分子ダイナミクスを調べた。また、Polytheonamide B の唯一の構造・機能類似体である Gramicidin A についても解析し、それらの結果と比較することで Polytheonamide B のチャンネルメカニズムについて議論する。

Microwaves are low-energy, low-frequency photons, yet they can efficiently and selectively heat polarizable liquid and metallic powders. In this talk, recent molecular dynamics simulation results of the heating process of water, ice and salty water will be presented,with research prospects of microwave heating of metallic powders.
参考：
マイクロ波励起・高温非平衡反応場の科学
Tanaka and Sato, J.Chem.Phys., 126, 034509 (2007).

Computer simulations are ideally suited to study the conformational dynamics of biological macromolecules. Although such methods have been widely used, two major challenges are how to reach biologically relevant time scales and how to represent the effect of biological environments accurately. Implicit solvent models can be used to address both of these issues.The application of continuum electrostatics models for aqueous solvent, dense cellular environments, and biological environments is discussed.Results from implicit solvent simulations of protein G, ubiquitin, and alanine dipeptide are compared to explicit solvent simulations and experiments to demonstrate that implicit solvent treatments can provide a high level of accuracy in dilute aqueous solvent.The conformational sampling of alanine dipeptide, poly-alanine, and melittin is studied in dense cellular environments modeled as reduced dielectric media to understand how realistic biological environments might alter the conformational preferences of biomolecules. Finally, long-time conformational sampling of the transmembrane peptide phospholamban as a function of phosphorylation is discussed to illustrate how implicit membrane models can be applied to study the relation between its dynamics and its function as a regulatory protein of SERCA, a heart muscle ATPase Ca2+ pump.