About the human resources expected by pharmaceutical industry, following two are raised as latest keyword in pharmaceutical industry ((1)Globalization (2) Open innovation). Conventionally, the pharmaceutical industry was called conservative industry and research staffs were adopted by the teaching recommendation from specific laboratories of an almost specific universities in many cases. Such things are completely lost now and use is decided according to the man's person. In that case, the points with important No. 1 said recently are communications skills, and it is important for them how regardless of Japanese and English, it tells against its opinion, and he is convinced. Although it is that it is natural although it is said that it is good and English language is indispensable, it is required to be able to convey own opinions clearly also in Japanese language.

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The HPCI (High Performance Computing Infrastructure) project aims to build the research network infrastructure that is to interconnect Japan's high-performance computer, including the K computer. We, RIKEN HPCI Program for Computational Life Sciences are as a part of the HPCI Strategic Program (FY 2010-2015) of the Ministry of Education Culture, Sports, Science and Technology (MEXT), is to resolve challenging problems in the area of medical science, life science and drug discovery. Our goal is to create a computational life-science environment and human network for drug discovery and medical development using the K computer and HPCI network. We aim to innovate for significant social and academic breakthroughs in four research themes: Theme 1: Simulations of biomolecules under cellular environments, Theme 2: Simulation applicable to drug design, Theme 3: Hierarchical integrated simulation for predictive medicine, Theme 4: Large-scale analysis of life data. In this talk, we make a presentation that feature details of theme 2: simulation applicable to drug design, which is simulation for drug design using massively parallel binding free energy calculations. After that, we explain how to build in-silico drug discovery infrastructure towards by using supercomputer infrastructure.

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Computational drug design is a growing field in recent drug discovery research. For example, lead compounds, which will have high activity, can be computationally discovered in efficient ways on the first stage of development of new drugs. In this case, various lead compounds are needed since some of them may not satisfy the conditions as medical supplies such as ADMET. Thus we focus on chemical spaces around which highly active compounds exist. New compounds close to those spaces will show the same degree of activity as the highly active compounds. Therefore we develop a new system of structure generation for searching a target area in chemical spaces, which are defined by structural descriptors. First, highly active compounds are manually selected as initial seeds. Then, those seeds are entered to our generator and structures slightly different from the seeds are generated and pooled. Next seeds are selected from the new structure pool with the scores calculated from two indices for each pooled structure. One index is distance from the center of the compounds surrounding a target area, and the other is predicted activity. We used GVK data of ligand binding affinity and showed that the proposed system performed appropriate structure generation.

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Enumeration of chemical graphs (molecular graphs) satisfying given constraints is one of the fundamental problems in chemoinformatics and bioinformatics since it leads to a variety of useful applications including structure determination of novel chemical compounds and drug design. We consider the problem of enumerating chemical graphs of monocyclic structure (a graph structure that contains exactly one cycle) from a given set of feature vectors which is specified by a pair of upper and lower feature vectors, where a feature vector represents frequency of prescribed paths in a chemical compound to be constructed. To enumerate all tree-like (acyclic) chemical graphs from a given set of feature vectors, Shimizu et al. and Suzuki et al. have already proposed efficient branch-and-bound algorithms based on a fast tree enumeration algorithm. In this study, we devise a novel method for extending the efficient algorithms of enumerating tree-like chemical graphs to enumeration of chemical graphs of monocyclic structure by designing a fast algorithm for testing canonicality of monocyclic structures.

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The stereoisogram approach (S. Fujita, J. Org. Chem., 69, 3158--3165 (2004), Tetrahedron, 60, 11629--11638 (2004)) has been applied to comprehensive discussions on geometric aspects and stereoisomeric aspects of stereochemistry, where a prismane skeleton has been selected as a rigid skeleton for the underlying proligand-promolecule model. The existence of five types of stereoisograms (Types I--V) has been demonstrated by using prismane derivatives as illustrative examples in a consistent way with a general proof using the group theory (S. Fujita, MATCH Commun. Math. Comput. Chem., 54, 39--52 (2005)).

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Non-destructive testing of food quality with Near-Infrared Spectroscopy (NIR) is becoming common. The prediction models are constructed between NIR spectra and quality parameters. Many investigations have been done for the construction of high predictive models. Although some models indeed have suitably predictive accuracy, those models work well in only limited data domains and the accuracy decreases with time. Hence the models should be reconstructed with new data by wasting samples of objective foods and measuring the quality. To perform both the reduction of the loss of the food and the high performance of the models, overlapped peaks of NIR spectra should be considered because the overlapped peaks make relationships between NIR spectra and quality parameters unclear. Derivation of spectra is generally used to solve this problem. An adequate order of derivative changes depending on how peaks are overlapping, but the dependence of an adequate derivative order on the number of training samples remains to be clarified. Therefore we propose a method using some kinds of derivative order of spectra according to the number of samples for the construction of regression models. The effectiveness of the proposed method was confirmed thorough the analyses of simulation data and real data.

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In chemical plants, soft sensors are widely used to estimate process variables that are difficult to measure online. The predictive accuracy of soft sensors decreases over time because of changes in the state of chemical plants, and soft sensor models based on time difference (TD) have been constructed to reduce the effects of deterioration with time, such as drift. However, many details of models based on TD remain to be clarified. In this study, TD models are discussed in terms of noise in data, auto-correlation in process variables, and degree of model accuracy, among others. We theoretically clarify and formulate the differences of predictive accuracy between normal models and TD models. The relationships and the formulas of TD were verified by analyzing simulation data. Furthermore, we analyzed data obtained by dynamic simulation of an existing full-scale depropanizer distillation column and examined various TD intervals and the predictive ability of TD models. It was confirmed that the predictive accuracy of TD models increased when TD intervals were optimized.

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There is a long-standing controversy on the residual entropy of glasses. As a contribution to the residual entropy debate for glasses, the configurational entropy of an Ising-type model is evaluated in non-equilibrium from thermodynamic (calorimetric) formula and the other based on statistical thermodynamics. And then the values are compared quantitatively. It is shown that the statistical thermodynamic entropy becomes greater than the calorimetric entropy upon cooling so that the real residual entropy is greater than the calorimetrically estimated value, at least the value is non-zero. Moreover, the statistical thermodynamic entropy which originated from macroscopic ‘thermodynamic degeneracy’ is thought to be a good approximation to the thermodynamic (valorimetric) entropy originated from microscopic structural disorder. Finally, it is concluded that non-zero entropy value is a real entity and it has the useful physical and chemical meanings in real crystal and glasses.

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The cis-trans isomerization rate of 4-dimethylamino-4'-nitroazobenzene (DNAB) was analyzed using molecular dynamics (MD) simulation for long runs. In high viscosity solvents, the reaction rate is retarded gradually as the system pressure approaches ten MPa (Kramers turnover). The interesting behavior was theoretically modeled based on the reaction rate theories in condensed phase, i.e., Kramers theory, Kramers-Grote-Hynes theory, Pollak-Glabert-Hanggi theory. The rate computationally evaluated using Accelerated MD (AMD), which can boost the isomerization process to directly obtain the reaction rate.

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The intramolecular motions such as conformational transformations affect intermolecular interactions in an ionic liquid, because the so-called "ionic liquid" is a molecular liquid. Itoh et al. reported that modification of the side-chain in the 1-butyl-3-methylimidazolium salt could reduce the glass transition point and the viscosity coefficient, even though it approximately maintained the size of the imidazolium cation. This fact suggests that the intramolecular motions play an important role in the interaction between the imidazolium cations. We performed DFT calculations to study molecular structures of the imidazolium cations in ionic liquids, but the results on the one-body problem gave little information about macroscopic properties of ionic liquids. This fact suggests that there is no way to investigate the problem on ionic liquids without the viewpoint of the many-body problem. Now I employ the three-states Potts model to formulate intermolecular interactions between two ion-pairs with their conformations. The interaction energy between the Potts spins is estimated by DFT calculations of the ion-pair dimer in the imidazolium ionic liquids.

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Two-bond ¹³C-¹H NMR spin-spin coupling constants can be described by the rotational angles of adjacent hydroxyl groups attached to pyranosyl ring, and those values can be used for structural constraints in the conformational determination of sugar chain in chemical and biochemical environment. In this study, to reproduce the experimental NMR coupling values and to predict sugar conformations in aqueous solution, two approaches have been examined. One is an exhaustive conformational analysis by using all conformers of α-D-galactose in aqueous solution. Energy and NMR coupling constant calculations for each conformation were performed by using high-level ab initio MO calculations with solvent effects. Although some conformers that comparatively reproduced the experimental ²J_CH values were found, these were not predominant conformers in the ab initio calculations. Another approach is a combination of MD calculations of sugar ensemble in experimental conditions of NMR measurement and new equations of NMR-²J_CH coupling values like as Karplus ³J_HH equation. Averaged NMR-²J_CH values applied the equations to the snapshot structures can reproduce the experimental slightly better than the former approach.

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Monosaccharide such as glucose exists as a pyranose form. Hexopyranose has C1 asymmetric carbon atom and has a stereoisomer which is called an anomer (α or β). In aqueous solution at room temperature, glucopyranose exists as a mixture of about 64% β-anomer and 36% α-anomer. However, mannopyranose exists as a mixture of about 68% α-anomer and 32% β-anomer. In this study, we reveal structures and stabilities of glucopyranose and mannopyranose in vacuo and in aqueous solution. In vacuo, geometry optimization calculations were carried out to obtain the structures of α- and β-anomers of glucopyranose and mannopyranose. It was shown that glucopyranose is more stable than mannopyranose and that α-anomer is more stable than β-anomer. In aqueous solution, QM/MM-MD simulations were performed to clarify solvation stabilization energy. For glucopyranose, solvation stabilization energy of β-anomer is more than that of α-anomer and β-anomer is more stable than α-anomer. As to mannopyranose, due to the large difference in the intrinsic energy between α-anomer and β-anomer, α-anomer is more stable than β-anomer in aqueous solution.

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The objective of this study is to construct a model which can predict mutagenicity of organic compounds with high accuracy. For this end, we propose a novel ensemble modeling method in which a lot of support vector machine (SVM) models are constructed as a sub-model and integrated to predict mutagenicity. For constructing sub-models, a part of data matrix is randomly selected from the original data matrix. After the construction of sub-models, a certain number of models which have high accuracy rate are selected and integrated to predict mutagenicity. We constructed an ensemble model using a data set of reverse mutation test which was collected by Hansen et al. to estimate the proposed method. As a result, the ensemble models with accuracy rate of 79.6% and 80.9% were successfully obtained. Moreover, we carried out reverse mutation test in order to verify correctness of the database. Five compounds, which are registered as negative in database but are predicted as positive by our model, were systematically selected and mutagenicity of these compounds was estimated. As a result, it is found that three of five compounds have mutagenicity.

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In the autumn of 1978 the First CSJ Symposium of Information Chemistry was held in the old building of CSJ in Tokyo but under a different title, "Symposium on Chemistry and Information", which was formally organized by the present author asked by Shin’ichi Sasaki, Prof. of Miyagi University of Education. The symposium ended successfully with as many as forty participants including the two research groups of Sasaki and Prof. Shizuo Fujiwara, University of Tokyo. The names of Hideaki Chihara and Takehiko Shimanouchi can be seen in the program of this symposium. Soon after this event Sasaki moved to Toyohashi University of Technology and Science, and the CSJ official monogram, "Information Chemistry" was published, followed by the establishment of the Division of Information Chemistry in CSJ. All the history around the birth of CSJ Symposium of Information Chemistry will be told by the author with the help of old documents and records.

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We have calculated ionization potential (IP) for K-Shell single core hole (SCH) creation and double ionization potential (DIP) for K-Shell double core hole creation of XH_m-YH_n (X, Y = C, N, O, F, m,n=0-3), and C₆₀ within the framework of density functional theory (DFT). For these molecules, we estimated the relaxation energies (a measure of the electron density flow to the core-hole site) and the interatomic relaxation energies (a measure of the electron density flow to the two core-hole sites) from the calculated IPs and DIPs. For XH_m-YH_n, we find that the interatomic relaxation energy for the DCH states having two holes at X and Y atoms decreases with increasing in the bond order between X and Y. For DCH states having two holes at two carbon atoms in C₆₀, we find that the interatomic relaxation energy decreases with increasing in the hole-hole distance.

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There have been many theoretical studies which used quantum chemical calculations. Supporting information including optimized structures, energies and so on are summarized and freely accessed via homepages of scientific journals. It is, however, difficult to find data which we want to see and use in our works or education. We have been developing a data base concerning with results of quantum chemical calculations called QMRDB. The data base includes (1) name of molecule and its chemical structure, (2) keywords for data searches, and (3) outputs of the Gaussian03 program. The outputs were stored after new calculations with the same keywords which specify molecular orbitals, MKS charges, frequency calculations and so on. It is possible to search desired data using of keywords as well as the structure of molecules specified by SMILES word, MDL Mol File and input of the Gaussian03 program.

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Proton transfer (PT) in ammonia-nitric acid system is studied by ab initio calculations in this work. PT does not occur in global-minimum structure of a single ammonium nitrate unit (monomer). The compulsory occurrence of PT in the monomer causes the formation of large dipole moment, whereas the total energy is destabilized. However, with the extent of intensive external electric field, PT spontaneously occurs in the monomer and moreover the total energy becomes lower than that of the global-minimum structure due to the dipole-electric field interaction energy. In two ammonium nitrate units (dimer), PT does occur to enhance internal dipole moments. On the basis of these results, it is revealed that the dipole-dipole interaction between the monomers in dimer not only promotes the occurrence of PT but also contributes to stabilize the total energy of the system.

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It is important to know whether or not mixtures form an azeotrope for the design of distillation processes since azeotropes cannot be separated by ordinary distillation. Thus, there have been many methods to predict the presence of azeotropy, e.g. equation of state, quantitative structure-property relationships, non-random two-liquid model, UNIFAC, UNIQUAC, thermodynamic equations and so on. In this study, to construct a model predicting the azeotropic formation and improve the prediction performance, we propose a novel method based on σ-profiles. The σ-profiles are major information of a COSMO-RS theory and the distribution of molecular surface areas which have charge density σ. Since the σ-profiles are characteristic of not only an objective molecule but also a relationship between the molecule and a solvent, they will be able to be used as descriptors to express interaction between solvents. The model predicting the presence of azeotropic formation is constructed with support vector machine (SVM).Through the analysis of data from the Dortmund Data Bank, it was confirmed that the proposed model has higher prediction performance compared to previous ones where structure descriptors are used as explanatory variables. Moreover, the performance of the SVM model was improved by adding structure descriptors to σ-profile descriptors.

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In experimental design for functional molecules, materials or products, complicated relationships exist between various experimental parameters and objective physical and chemical properties. Regression analysis with experimental data is a useful way for understanding those relationships, and a constructed regression model can be used to search for functional products effectively. However, although those products can be found in domains out of existing data, the predictive ability of the model tends to be low in regions where data density is low, and new candidates whose predicted values of a property are unreliable will not achieve desired values of the property. Therefore to search for new candidates in appropriate extrapolation domains, we consider the probability that a new candidate will have intended values of a property and the reliability of a predicted value of the property for the candidate. The probability is calculated from a predicted value and its estimated prediction error, and the reliability is based on data density. The proposed method is applied to simulation data and aqueous solubility data, and the efficiency of the method could be confirmed. In addition, we could automatically select an appropriate regression method in each step of the search according to features of existing data.

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In the field of chemical information, various structural descriptors have been developed for representing chemical compounds. The fingerprint method is one of the structural descriptor by using a Boolean array representing the presence or absence of chemical substructures. As the processing speed for calculating the similarity score between two Boolean array is fast, the fingerprint method is used in similarity search of chemical compounds and in clustering of chemical structures for the screening. There are various definitions in fingerprint method, because characteristics are represented by the difference of chemical substructure. It is important to select the definition of the fingerprint method in consideration of data sets and in obtaining expected results. To evaluate the features of those definitions, we evaluated the use of bits by analysis using the several values in the database, and evaluated the comparison of retrieval results.

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We have proposed a mechanism counting and holding computational accuracy of all the variables in the quantum-chemical calculations, and found to be taken into account not only the accuracy-decreasing factor but also accuracy-increasing factors. On applying the mechanism to the tri-diagonalization of the overlap matrix of Rn atom, good agreements are found for counted accuracy and the actual accuracy of all the elements of the tri-diagonalized matrix.

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The behavior of a homologous series of polycyclic aromatic hydrocarbons, the linear acenes, poses many unsolved problems. The interesting topic of debate in linear acenes is the evolution of aromaticity when going from the outer to inner rings. Anthracene, which has contrasting inner and outer rings, exhibits opposite results as to whether the central ring is the most or least aromatic according to some aromatic indexes. Recently, we defined the center ring is more aromatic than the outer one for anthracene by the combination method between asymmetric Kekulé structures (CMAK). This was also indicated by the index of deviation from aromaticity (IDA). The behavior of the aromaticity of the central ring for linear acenes was characterized by the CMAC. On the other hand, anthracene is protonated, adds bromine, and undergoes Diels-Alder reactions at the center ring. To study the reactivity and aromaticity for linear acenes and [n]phenacenes, we calculated the hydrogen addition energy for these compounds. In this conference, we will propose the reactivity points of these compounds from the hydrogen addition energy.

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The Diels-Alder reactions may be the most important class of organic reactions. There reactions have high regio- and stereo-selectivity. In this study, we have studied the reaction mechanisms between 1,1-substituted ethylene and butadiene. As substituent groups of 1,1-substituted, electron donor group (CH₃, C₂H₅, OH, OCH₃, NH₂) and electron attractive groups (F, Cl, CN, CHO, NO₂) are chosen. All equilibrium and transition state structures were determined with analytically calculated energy gradients at the CASSCF method with 6-31G(d) basis set. To interpret the mechanism of the concerted pathway, CiLC analysis was performed along the IRC pathway. The reactions between butadiene and substituted ethylene with electron donor groups have lager activation energy barriers than these with electron attractive groups. Generally, F and Cl substitution groups are classified into electron attractive groups. But, these substitution groups look like electron donor groups from the activation energy barriers. Accordingly, the electronic state of substituted ethylene was characterized by using the CiLC method. This analysis implies that F, Cl have electron donating ability under Diels-Alder reactions. From above result, we revealed a correlation that the class of the substituted ethylene on the basis of the CiLC analysis might adopt either the concerted or stepwise reaction pathways.

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A hydrophobic interaction is one of the most known interactions observed between a protein and a ligand. In general, it is well known that the hydrophobic atoms of a ligand locating on a hydrophobic pocket provide stabilization of the protein and ligand complex. On the other hand, recently, an argadin was discovered as one of the chitinase inhibitor and the binding pose was observed with X-ray crystallographic analysis (PDB ID: 1H0G). In the X-ray analysis, the very interested binding pose was observed. In the hydrophobic pocket formed by aromatic amino acid residues, two hydrophilic charged fragments of argadin forms the intramolecule hydrogen bonding. To our knowledge, however, the role of argadin intramolecule hydrogen bonding in the chitinase hydrophobic pocket is not known, yet. So, in the study, we performed ab initio molecular orbital and density functional theory calculations including the contribution of dispersion interaction to research of the role of argadin intramolecular hydrogen bonding and to reveal the characteristic features of intermolecular interactions.

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We reported that simple alkyl- and arylpyrazines were showed the 50% inhibitory concentration towards arachidonic acid-induced and collagen-induced aggregation of rabbit blood platelet in vitro. Among the 48 pyrazine derivatives, 2,3-bis(p-methoxyphenyl)pyrazines showed the most potent inhibitory activity. Molecular dynamics (MD) simulations of the complexes of 2OYU with compound 42 and 1HT5 with flurbiprofen methyl ester were performed. From the MD simulation results, the binding modes, structural changes, and intermolecular hydrogen bonds have revealed the molecular interactions explaining the differences in the cavity size of the active site by ligands used. In order to clearly the interaction of the COX-Ligands, the InterFragment Interaction Energy (IFIE) analysis was calculated by Fragment Molecular Orbital method. Consequently, relatively strong interaction energies of the ARG120-ligand calculated to be -19.4 kcal/mol, SER353-ligand calculated to be -12.9 kcal/mol and ILE523-ligand calculated to be -11.9 kcal/mol.

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Fourier grid Hamiltonian (FGH) method is applied to calculate vibrational energy levels of hydrogen molecule. Meyer's method and Balint-Kurti's method are briefly described. Difference of these methods is grid point range. Grids used in Meyer's method range from -pi to pi. On the other hand, Balint-Kurti's method uses distance L as grid range. Balint-Kurti's method with very accurate potential energies of hydrogen molecule by Pachuckis is applied to calculate vibrational energy levels of hydrogen molecule. Because of the equal grid space in the theory, 36 grid points range from 0.5 to 4.0 bohr of nuclear distances (space length is 0.1 bohr) are selected from Pachuckis's results as potential energies of FGH. Lowest 14 vibrational energy levels are calculated by FGH. Good agreement between theoretical and experimental results obtained for energy difference between vibrational energy levels from v = 0 to 10. However, beyond v=11, errors become large because of neighbor of dissociation limit.

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Adamantane has many interesting physical and chemical properties because of the high symmetry. We chose five adamantane derivatives as the model molecule of hydrophobic hydration. The target molecule of simulation is adamantane, 1-adamantyl chloride, 1-adamantyl fluoride, amantadinium cation and perfluoroadamantane. Perfluoroadamantane is adamantane that hydrogen is substituted with fluorine. We simulate the hydration around the solute molecule by molecular mechanics and canonical Monte Carlo method. The water model is TIP3P. The radius of the simulation sphere is about 15.3Å. A solute molecule and 500 water molecules exist in the simulation sphere. We compare the radial distribution functions of water molecules around the solute molecule. In the case of 1-adamantyl chloride, the first peak of the radial distribution is lower than the case of adamantane. In the case of perfluoroadamantane, the first peak is farther and higher than the case of adamantane. The peaks of 1-adamantyl fluoride and amantadinium cation are quite similar to the peak of adamantane.

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γ Poly glutamic acid (γ-PGA) has attracted great attention in various areas such as cosmetics because of its high water holding ability. Since the γ-PGA has one stereogenic center, there are L-γ PGA, D-γ-PGA and the mixed L,D-γ-PGA. It is believed that the secondary structure of L-γ-PGA is helical and that of the mixed D,L-γ-PGA is non-helical, although the structural detail of helix has not been disclosed. In this study, we investigate the helical structures of L-γ PGA and D,L-γ-PGA in detail. To this end, several helix models were constructed and compared. As a result, the helix which has 5 residues/helical cycle is the most stable in L-γ-PGA helices. It has been suggested experimentally that the viscosity of L-γ-PGA is higher than that of D,L-γ-PGA; that is, the distribution of L-γ-PGAs might be uniform in aqueous solution, and that of D,L-γ-PGA might not. We confirmed the difference in the distribution by using Monte Carlo (MC) simulation. We programmed our original MC simulation, and the interaction energy functions used in the MC simulation are simply Lennard-Jones' 6-12 potential and dipole-dipole interaction.

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We suggest a new grid-free approach for the local exchange-correlation (XC) calculation using Cholesky Decomposition (CD) in density functional theory (DFT). The conventional grid-based method for the XC calculation involves numerical approximations because of the complexity of the XC functional, and it may causes numerical instabilities. On the other hand, a grid-free approach, which uses matrix representation of the density and matrix operations to represent any density functional, can describe the XC term to avoid these instabilities in the grid-based approach. However, in order to get the matrix representation of the density, the four-center overlap integrals require much computational resource, which becomes the bottleneck of the grid-free method. Meanwhile, it attracts much attention to apply the CD method into the electron repulsion integral calculations of the Coulomb and exchange Fock matrices, recently. Thus, in order to solve the difficulty of the grid-free XC calculation, we introduced the CD method into the four-center overlap integrals of a grid-free XC calculation. The suggested method is expected to realize the practically analytical integral of XC calculation and perform effectively in large system.

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Toxicity of arsenic is significantly variable depending on its speciation and it is important to understand the migration behaviors of this speciation, where diffusion can control transport mechanism in the impermeable layer such as in the pore waters of sediments and rocks. Diffusion coefficients of arsenite, arsenate, methylarsonic acid (MMA), and phenylarsonic acid (PAA) as a function of pH were determined in this study for the first time, which contributes to the better understanding of transport of various arsenic speciation in the environment. By aid of ab initio MO calculations and Monte Carlo simulations, this study sheds light on the origin of pH dependence on the diffusion coefficients for the arsenic compounds. For the neutral speciation at low pH, the diffusion is dominated not only by the molecular size but also by charge distribution in the molecule (degree of polarization). On the other hand, for the dissociated speciation at high pH, the diffusion is dominated by charged oxyanion due to high association of water molecules regardless their functional groups. This effect is common for all the arsenic species, which causes that the differences in their diffusion coefficients become smaller as the pH increases, especially for arsenate, MMA, and PAA.

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Protection of the hydroxyl group is essential for multi-step syntheses of structurally-complex chemicals such as natural products. Moreover, the protective group removal in those molecules under mild conditions is significant especially when the molecules are not so stable. We have reported mild deprotection method of methoxymethyl ether using the combination of TMSOTf and pyridine derivatives in dichloromethane. The reaction has two steps; the first step is the formation of a pyridinium salt from the reaction of pyridine derivatives and TMSOTf, and the second step is the hydrolysis between the pyridinium salt and water molecule. In the second step, we found that the reaction rate and the yield depended on the pyridine derivatives. For example, although the reaction was succeeded in the case of 2,2'-bipyridyl, 2,4,6-collidinium salt made it fail. In order to reveal the major reasons of the variation, we successfully carried out DFT computations in order to find the transition state structures of the hydrolysis reactions. In this study, B3LYP was used as a functional and 6-311G* basis set was adopted.

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The reaction path of the acetyl acetone method (or Nash reagent), from acetyl acetone (pentane-2,4-dione) to lutidine derivative, that is the reaction to measure the concentration of the formaldehyde and became very important in these days, was calculated at the HF/3-21G + ZPC level（ZPC=zero point energy correction), and MP2/6-31G** + ZPC level. In order to study the difference of the reaction environment, as a model for porous glass, H₂Si=O and (OH)₂Si=O are added to the systems, however, the silicon atom makes chemical bonds or strong complex with the oxygen atom of FLUORAL-P. We also found the formation of the chemical bond decreases the activation energy of a H₂O elimination reaction. On the other hands, the carbon analogous H₂C=O and water molecule H₂O do not make a chemical bond with FLUORAL-P and the activation energy of a H₂O elimination reaction does not decrease. Difference between the carbon and silicon atom is considered to be the difference of their LUMO levels.

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A rooted digraph is regarded as a protonated water (PW) cluster, and a hydrogen bond (H-B) matrix can represent a rooted digraph. All possible topology-distinct patterns corresponding to PW clusters containing up to 8 water molecules were enumerated by using H-B matrices. We apply the Hamiltonian algorithm combined with ab initio molecular orbital calculations to the optimization of molecular structures for PW clusters up to hexamers.

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We examine natural products which can be the ligand of nuclear receptor, PPARγ. The nuclear receptor PPARγ is activated by making a covalent bond with an electrophilic natural compound. As candidates of the PPARγ's ligands, we consider butenoic acid, cinnamic acid and decenoic acid, each of which is alpha, beta-unsaturated carboxylic acid. We find that they bind covalently to a cysteine residue in the PPARγ ligand binding pocket through a Michael addition reaction.

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We have developed a system that automatically identifies the reaction models involved in the deposition of films on substrates with nanometer- or micrometer-sized trenches by Chemical Vapor Deposition (CVD) processes using Real-Coded Genetic Algorithms (RCGA). The reaction models, which comprise various deposition species and surface reactions with different values of sticking coefficient, were determined both quantitatively and qualitatively on the basis of chemical kinetics. Automatic modeling is achieved by the system through the analysis of the experimental data of the cross-sectional shapes of the deposited films. We investigated the influence of RCGA methods on the performance of the system. We tried two RCGA methods, that is, REX(φ, n+k) (Real-Coded Ensemble Crossover) + JGG (Just Generation Gap) and REX^star + JGG. Although the system successfully identified the appropriate reaction models both quantitatively and qualitatively using both the methods, REX^star + JGG showed better performance with regard to calculation cost. Therefore, we believe that REX^star + JGG is more promising for the analysis of the complicated reaction models.

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Fast and accurate calculation of the predicted results of Chemical Vapor Depositions (CVD) is very helpful to the R&D of the CVD processes. Therefore, we have developed a novel calculation method, by which accurate calculations along with reduced computing cost were achieved, to reproduce deposition profiles in three types of reactors. Mass balance equations in the reactors with complicated reaction models were divided into simple equations with single deposition species, in order to identify a few basis functions, with which all the deposition profiles can be synthesized. Accordingly all the deposition profiles were calculated from the linear combinations which consisted of the basis functions. The coefficients of the linear combinations were optimized by Real-Coded Genetic Algorithms (RCGA). In addition, we investigated the influence of three methods of RCGA, that is, BLX-α (Blend Crossover) + tournament selection, REX(φ, n+k) (Real-Coded Ensemble Crossover) + JGG (Just Generation Gap) and REX^star + JGG on the calculations of the profiles. REX^star showed the best overall performance for the calculations.

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We propose a new form of penalty function to constrain molecular structural chirality or planelity in molecular mechanics calculation. By using the signed volume of tetrahedral structure spanned with four unit vectors arround centered chiral carbon atom as a single variable index of the chirality, all chemical bonds are treated as symmetrically equivalent, and any form of single variable function is available for the constraint penalty function. The index of chirality can be extended for the three chemical bond case, and can be used as symmetrical planer constraint penalty functions.

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A four-body statistical pseudo-potential has been developed for discriminating native and non-native protein conformations by Krishnamoorthy and co-workers. Recently, Aita and Nishigaki, two of us, have applied the potential to a fast blind docking of some peptides to a target protein. In this paper, we propose a development of new four-body statistical pseudo-potentials considering the only interactions between the amino residues to be found around protein surface. Technique of solvent excluding surface area analysis was used for this development. We expect that new four-body statistical pseudo-potential can be applied to studies of the next generation antibody and peptide drug developments.

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Trimethylamine oxide and Urea are known as osmolytes. Marine organisms hold these in their intracellular fluid to control osmotic pressure. In this study, we focus on the hydration of TMAO and Urea. We optimized the geometries of TMAO, Urea, TMAO-nH₂O and urea-mH₂O complexes with the theoretical level of MP2/6-31G*. We found TMAO (or Urea) had much larger dipole moment than that of water molecule. From electrostatic potential (ESP) maps, positive and negative charges are separated in TMAO and Urea. We also found there are three spots in TMAO, and two spots in Urea, to which water molecules are bound very strongly. These facts indicate TMAO and urea have the capability to capture water molecules electrostatically and spatially, and there are strong interactions between TMAO (or Urea) and water molecules. We found the hydration stabilization energy of TMAO (or Urea) was much larger than the interaction energy between water molecules. It indicates the interaction between TMAO (or Urea) and water molecule creates very large stabilization. From the above results, we propose why TMAO and Urea play an important role as osmolytes is due to their capability to capture water molecules strongly.

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